Subjects -> INSTRUMENTS (Total: 62 journals)
Showing 1 - 16 of 16 Journals sorted alphabetically
Annali dell'Istituto e Museo di storia della scienza di Firenze     Hybrid Journal  
Applied Mechanics Reviews     Full-text available via subscription   (Followers: 27)
Bulletin of Social Informatics Theory and Application     Open Access   (Followers: 1)
Computational Visual Media     Open Access   (Followers: 4)
Devices and Methods of Measurements     Open Access  
Documenta & Instrumenta - Documenta et Instrumenta     Open Access  
EPJ Techniques and Instrumentation     Open Access  
European Journal of Remote Sensing     Open Access   (Followers: 9)
Experimental Astronomy     Hybrid Journal   (Followers: 39)
Flow Measurement and Instrumentation     Hybrid Journal   (Followers: 18)
Geoscientific Instrumentation, Methods and Data Systems     Open Access   (Followers: 4)
Geoscientific Instrumentation, Methods and Data Systems Discussions     Open Access   (Followers: 1)
IEEE Journal on Miniaturization for Air and Space Systems     Hybrid Journal   (Followers: 2)
IEEE Sensors Journal     Hybrid Journal   (Followers: 103)
IEEE Sensors Letters     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Imaging & Microscopy     Hybrid Journal   (Followers: 9)
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan     Open Access  
Instrumentation Science & Technology     Hybrid Journal   (Followers: 7)
Instruments and Experimental Techniques     Hybrid Journal   (Followers: 1)
International Journal of Applied Mechanics     Hybrid Journal   (Followers: 7)
International Journal of Instrumentation Science     Open Access   (Followers: 40)
International Journal of Measurement Technologies and Instrumentation Engineering     Full-text available via subscription   (Followers: 2)
International Journal of Metrology and Quality Engineering     Full-text available via subscription   (Followers: 4)
International Journal of Remote Sensing     Hybrid Journal   (Followers: 274)
International Journal of Remote Sensing Applications     Open Access   (Followers: 43)
International Journal of Sensor Networks     Hybrid Journal   (Followers: 4)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Journal of Applied Remote Sensing     Hybrid Journal   (Followers: 83)
Journal of Astronomical Instrumentation     Open Access   (Followers: 3)
Journal of Instrumentation     Hybrid Journal   (Followers: 32)
Journal of Instrumentation Technology & Innovations     Full-text available via subscription   (Followers: 1)
Journal of Medical Devices     Full-text available via subscription   (Followers: 5)
Journal of Medical Signals and Sensors     Open Access   (Followers: 3)
Journal of Optical Technology     Full-text available via subscription   (Followers: 5)
Journal of Sensors and Sensor Systems     Open Access   (Followers: 11)
Journal of Vacuum Science & Technology B     Hybrid Journal   (Followers: 2)
Jurnal Informatika Upgris     Open Access  
Measurement : Sensors     Open Access   (Followers: 3)
Measurement and Control     Open Access   (Followers: 36)
Measurement Instruments for the Social Sciences     Open Access  
Measurement Science and Technology     Hybrid Journal   (Followers: 7)
Measurement Techniques     Hybrid Journal   (Followers: 3)
Medical Devices & Sensors     Hybrid Journal  
Medical Instrumentation     Open Access  
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microscopy     Hybrid Journal   (Followers: 8)
Modern Instrumentation     Open Access   (Followers: 50)
Optoelectronics, Instrumentation and Data Processing     Hybrid Journal   (Followers: 4)
PFG : Journal of Photogrammetry, Remote Sensing and Geoinformation Science     Hybrid Journal  
Photogrammetric Engineering & Remote Sensing     Full-text available via subscription   (Followers: 29)
Remote Sensing     Open Access   (Followers: 54)
Remote Sensing Applications : Society and Environment     Full-text available via subscription   (Followers: 8)
Remote Sensing of Environment     Hybrid Journal   (Followers: 93)
Remote Sensing Science     Open Access   (Followers: 24)
Review of Scientific Instruments     Hybrid Journal   (Followers: 22)
Sensors and Materials     Open Access   (Followers: 2)
Solid State Nuclear Magnetic Resonance     Hybrid Journal   (Followers: 3)
Standards     Open Access  
Transactions of the Institute of Measurement and Control     Hybrid Journal   (Followers: 13)
Труды СПИИРАН     Open Access  
Similar Journals
Journal Cover
Transactions of the Institute of Measurement and Control
Journal Prestige (SJR): 0.41
Citation Impact (citeScore): 1
Number of Followers: 13  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0142-3312 - ISSN (Online) 1477-0369
Published by Sage Publications Homepage  [1097 journals]
  • Variational method-based distributed optimal guidance laws for
           multi-attackers’ simultaneous attack
    • Authors: Xiaoqian Wei, Jianying Yang, Xiangru Fan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      To solve the problem of cooperative encirclement and simultaneous attack of multiple unmanned aerial vehicles, variational method and Hamiltonian optimization are utilized to design an optimal attack trajectory of multiple attackers pursuing a single target that has fixed initial relative state, fixed final relative state and fixed duration of the attack under condition that the acceleration of the target being estimable. When terminal relative state and attack duration are unknown, online calculation algorithm is used to compute a chain of key intermediate points to create the guidance law and ensure successful deliverance of multiple attackers’ simultaneous attack of the target. The only requirement for the multi-attacker communication network is that it contains a directed spanning tree. The guidance laws can function properly as long as one or more attacker can observe the target. The novel guidance laws practicability are verified by simulation results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-11T07:59:46Z
      DOI: 10.1177/0142331220981430
       
  • Control and synchronization for two Chua systems based on intuitionistic
           fuzzy control scheme: A comparative study
    • Authors: Mohamed Hamdy, Mohamed Magdy, Salah Helmy
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents control and synchronization for two nonlinear chaotic systems in the presence of uncertainties and external disturbances based on an intuitionistic fuzzy control (IFC) scheme. Two classes of Chua and cubic Chua oscillators have been formulated as master and slave respectively. The master and slave systems have different initial conditions and parameters, which leads to the butterfly effect that rules the chaotic systems’ behaviour. IFC scheme is chosen as a different method that has not been used before to control and synchronize Chua and cubic Chua oscillators. The main objective of the IFC scheme is to collect more information about the system and provide flexibility for the controller that increases the robustness of the control system to uncertainties in the structure of the chaotic systems. The stability analysis of the overall system is guaranteed using Routh-Hurwitz and Lyapunov criteria. The simulation results accomplished to evaluate the effectiveness of the proposed control and to demonstrate its reliability to control Chua’s circuit system with a comparative study.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-11T07:58:03Z
      DOI: 10.1177/0142331220981425
       
  • Robust finite frequency [math] control for Lipschitz nonlinear systems
    • Authors: Wajdi Saad, Anis Sellami
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the [math] control problem for Lipschitz nonlinear systems in the finite-frequency domain. Both parameter uncertainties and external disturbances are considered. In contrast to existing full-frequency methods, the proposed approach takes into account of the frequency information of disturbances during the design proceeding. Sufficient analysis conditions for the closed-loop system are firstly derived. Then, synthesis conditions are formulated in terms of linear matrix inequalities (LMIs). In fact, the control gain is designed to attenuate the influence of disturbances in different frequency ranges (low, middle and high). Finally, the model of the Chua circuit is used to validate the effectiveness of the proposed finite-frequency approach and to prove its superiority compared to the full-frequency counterpart.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-11T07:55:24Z
      DOI: 10.1177/0142331220981326
       
  • Robust adaptive observer-based finite control set model predictive current
           control for sensorless speed control of surface permanent magnet
           synchronous motor
    • Authors: Muhammad Usama, Jaehong Kim
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The objective of the paper is to present the efficient and dynamic sensorless speed control of a surface permanent magnet synchronous motor (SPMSM) drive at a wide speed range. For high-performance speed sensorless control, a finite control set model predictive current control (FCS-MPCC) algorithm based on a model reference adaptive system (MRAS) is proposed. With the FCS-MPCC algorithm, the inner current control loop is eliminated, and the limitations of the cascaded linear controller are overcome. The proposed speed sensorless control algorithm provides an efficient speed control technique for the SPMSM drive owing to its fast dynamic response and simple principle. The adaptive mechanism is adopted to estimate the rotor shaft speed and position used in FCS-MPCC for dynamic sensorless control. FCS-MPCC uses a square cost function to determine the optimal output voltage vector (VV) from the switching states that give the low cost index. A discrete-time model of a system is used to predict future currents across all the feasible VVs produced by the voltage source inverter. The VV that reduced the cost function is adopted and utilized. Simulation results showed the efficacy of the presented scheme and the viability of the proposed sensorless speed control design under various load conditions at a wide speed operation range.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-11T07:53:44Z
      DOI: 10.1177/0142331220979264
       
  • Deadband feedback-based scheduling approach for networked control system
           with variable sampling period
    • Authors: Zhongda Tian
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Reasonable information scheduling strategies in the networked control system (NCS) can improve the quality of service of the network, reduce the conflict of information transmission in the network, and improve the overall performance of the NCS. In order to improve the performance of the NCS, a deadband feedback-based scheduling approach for the NCS with a variable sampling period is proposed. For the NCS with multi control loops, considering the limitation of network bandwidth resources, the dynamic real-time adjustment of a multi-loop sampling period is achieved through network utilization prediction, network bandwidth configuration and sampling period calculation. Furthermore, deadband feedback scheduling is combined with a variable sampling period algorithm. Deadband is set in the sensor and controller nodes to effectively adjust the information flow of the forward channel and the feedback channel. The proposed scheduling approach can reduce the impact of network conflict and network delay on system stability, make the network resources allocated reasonably, save network data traffic, and improve the overall performance of the NCS. A NCS with five control loops is used as the simulation object and carried out by True Time toolbox. The simulation results show that the proposed scheduling approach can improve output control performance of the system, reduce integral absolute error value of the control loops, and improve network utilization. The overall control performance of the system is improved.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-08T09:28:36Z
      DOI: 10.1177/0142331220981427
       
  • Stability analysis of connected vehicles with V2V communication and time
           delays: CTCR method via Bézout’s resultant
    • Authors: Sirin Akkaya, Onur Akbati, Ali Fuat Ergenc
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is focused on the distributed control of connected vehicles via vehicle-to-vehicle (V2V) communication. A mixed predecessor following topology with a virtual leader under constant time headway policy is analysed in case of communication and input delays. The longitudinal dynamics of each vehicle in the platoon is represented by a third-order linear model. Unavoidable communication and input delays are introduced into the platoon structure which converts the characteristic equation of the system into a transcendental type. The stability regions of the system in delay space are obtained by utilizing the cluster treatment of characteristic root (CTCR) method in the case of single and multiple time delays. A new Bézout resultant matrix-based approach is proposed to determine the kernel and offspring hypersurfaces of the CTCR method. The determination of these kernel and offspring hypersurfaces becomes computational costly as the number of vehicles increases in the platoon due to the increasing degree of characteristic equation. However, the proposed method reduces the dimensions of the coefficient matrix which is created by using the characteristic equation. It is concluded that the proposed method confirms the internal stability of the connected vehicles with both generic information flow topologies and formation between vehicles under single and multiple time delays. Thereafter, a local string stability definition is proposed in terms of spacing errors. Sufficient conditions to obtain string stability under mixed predecessor following topology for the existence and nonexistence of time delay are given. Finally, several simulation studies with different scenarios are conducted to display the effectiveness of the proposed model and method for internal and string stabilities.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-08T09:16:10Z
      DOI: 10.1177/0142331220981426
       
  • Integral barrier Lyapunov functions-based integrated guidance and control
           design for strap-down missile with field-of-view constraint
    • Authors: Bin Zhao, Zhenxin Feng, Jianguo Guo
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The problem of the integrated guidance and control (IGC) design for strap-down missile with the field-of-view (FOV) constraint is solved by using the integral barrier Lyapunov function (iBLF) and the sliding mode control theory. Firstly, the nonlinear and uncertainty state equation with non-strict feedback form for IGC design is derived by using the strap-down decoupling strategy. Secondly, a novel adaptive finite time disturbance observer is proposed to estimate the uncertainties based on an improved adaptive gain super twisting algorithm. Thirdly, the special time-varying sliding variable is designed and the iBLF is employed to handle the problem of FOV constraint. Theoretical derivation and simulation show that the IGC system is globally uniformly ultimately bounded and the FOV angle constraint is also guaranteed not only during the reaching phase but also during the sliding mode phase.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-08T08:35:47Z
      DOI: 10.1177/0142331220981329
       
  • Add-on integration module-based proportional-integration-derivative
           control for higher precision electro-optical tracking system
    • Authors: Qianwen Duan, Yao Mao, Hanwen Zhang, Wenchao Xue
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper concerns the improvement on proportional-integration-derivative (PID) control for the electro-optical tracking system for high-mobility targets. To achieve higher tracking precision and stronger disturbance rejection while fully utilizing the existing PID loop, the add-on integration module is proposed and seamlessly integrated into the conventional PID loop. It is proven that for any given conventional PID controller parameters, the add-on integration module based PID control can improve the ability of error attenuation at low frequency and keep the stability of resulting closed-loop system. More importantly, the feasible set of all parameters in the added module is explicitly given. Based on the feasible set, the non-dominated sorting genetic algorithm II (NSGA-II) is adopted to obtain the globally optimal controller’s parameter under certain performance indices. The experiments are carried out for a typical electro-optical tracking test bed with several reference signals. It is shown that the proposed method has much smaller tracking errors than the existing PID method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-05T05:09:48Z
      DOI: 10.1177/0142331220975892
       
  • Nonlinear output path following control using a two-loop robust model
           predictive control approach
    • Authors: Mohammad Ghassem Farajzadeh-Devin, Seyed Kamal Hosseini Sani
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, output tracking of a geometric path for a nonlinear uncertain system with input and state constraints is considered. We propose an enhanced two-loop model predictive control approach for output tracking of a nonlinear uncertain system. Additionally, we propose an optimal version of output path following control problem to improve the controller synthesis. Satisfaction of the dynamical constraints of a system such as velocity, acceleration and jerk limitations is added to the problem introducing a new augmented system. The recursive feasibility of the proposed method is demonstrated, and its robust stability is guaranteed such that relaxation on the terminal constraint and penalty are achieved. To validate the theoretical benefits of the proposed controller, it is simulated on a SCARA robot manipulator and the results are compared with a two-loop model predictive controller successfully.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-05T04:38:26Z
      DOI: 10.1177/0142331220971423
       
  • Improved wavelet packet denoising algorithm using fuzzy threshold and
           correlation analysis for chaotic signals
    • Authors: Yunxia Liu, Xiao Lu, Guangxia Bei, Zhongyun Jiang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The research of an effective denoising algorithm for the actual obtained signals with chaotic characteristics is of great interest to all fields of the subject. To show the true chaotic state and analyze the dynamic characteristics of the chaotic system more accurately, an improved denoising algorithm using wavelet packet is proposed in this paper. Wavelet packet decomposition has an optimal sub-band tree structure, which can be used for local analysis of chaotic signals. Based on the correlation function value differences of wavelet packet coefficients, the algorithm determines the optimal decomposition layer, while the optimal wavelet packet basis is obtained with logarithmic energy entropy as the cost function. Furthermore, on the one hand, it makes efforts to divide wavelet packet coefficients into approximate parts, fuzzy parts and detail parts. On the other, it carries out singular spectrum analysis, the fuzzy threshold and the correlation analysis for the select of these three different types of coefficients in order to retain the dynamic performance of chaotic signals in the greatest extent. To verify the effectiveness of the algorithm, the Lorenz chaotic model is employed to analyzed. Simulation results verify the practicability of the improved denoising algorithm, which can also be well applied to various chaotic signals denoising with different noise levels.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T11:08:55Z
      DOI: 10.1177/0142331220979229
       
  • Finite-time boundedness of two-dimensional positive continuous-discrete
           systems in Roesser model
    • Authors: Shipei Huang, Zhengbing Yan, Zhengjiang Zhang, Guoqiang Zeng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the finite-time boundedness of two dimensional (2-D) positive continuous-discrete systems in Roesser model. By constructing an appropriate co-positive type Lyapunov function, sufficient conditions of finite-time stability for the nominal 2-D positive continuous-discrete system are established. Sufficient conditions of finite-time boundedness for the addressed system with external disturbances are also proposed. The proposed results are then extended to uncertain cases, where the interval and polytopic uncertainties are considered respectively. Finally, three examples are provided to illustrate the effectiveness of the proposed results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T11:07:47Z
      DOI: 10.1177/0142331220980883
       
  • Fuzzy descriptor tracking control with guaranteed [math] error-bound for
           robot manipulators
    • Authors: Anh-Tu Nguyen, Antoine Dequidt, Van-Anh Nguyen, Laurent Vermeiren, Michel Dambrine
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the nonlinear tracking control design for robot manipulators. In spite of the rich literature in the field, the problem has not yet been addressed adequately due to the lack of an effective control design. Using a descriptor fuzzy model-based framework, we propose a new approach to design a feedback-feedforward control scheme for robot manipulators in a general form. The goal is to guarantee a small level of an [math] gain specification to improve the tracking performance while significantly reducing the numerical complexity for real-time implementation. Based on Lyapunov stability arguments, the control design is formulated as a convex optimization problem involving linear matrix inequalities. Numerical experiments performed with a high-fidelity manipulator benchmark model, embedded in the Simscape MultibodyTM environment, demonstrate the effectiveness of the proposed control solution over existing standard approaches.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T10:48:08Z
      DOI: 10.1177/0142331220979262
       
  • The optimal displacement control for fractional incommensurate mass-spring
           oscillators by Shifted Legendre polynomials
    • Authors: Yitong Jin, Xingde Zhou, Xianzeng Shi, Chunxiu Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Based on the Riemann–Liouville fractional derivative, an optimal displacement control strategy for fractional incommensurate mass-spring oscillators has been presented. According to the calculus of variations and the Lagrange multiplier technique, the optimality conditions for the given problem are obtained. Using Shifted Legendre polynomials, the problem of solving differential equations is transformed into the problem of solving a set of algebraic equations. The validity, high efficiency and applicability of the proposed method are demonstrated through the simulation results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T10:42:13Z
      DOI: 10.1177/0142331220978141
       
  • Chiral metamaterial-based sensor applications to determine quality of car
           lubrication oil
    • Authors: Şekip Dalgaç, Faruk Karadağ, Mehmet Bakır, Oğuzhan Akgöl, Emin Ünal, Muharrem Karaaslan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Motor oils have to be changed periodically in a period of 10.000–20.000 km according to the motor types. A chiral metamaterial sensor that operates in X band is developed to determine the quality of motor oils, numerically analyzed and experimentally tested in this study. The proposed design has square and circular shaped resonators that are printed on IS680 substrate. Reflection coefficient parameters of S11 and S22 are employed for the verification of sensor. The physical principle behind the structure in this study is based on the degradation of motor oil, which changes dielectric constant and causes resonance frequency shifts. According to S11 reflection coefficient data, 40 MHz(0 km–10000 km) and 60 MHz(0 km–5000 km) resonant frequency shifts are observed between clear and dirty motor oils samples. These shifts have the values of 30 MHz(0 km–10000 km) and 120 MHz(0 km–5000 km), when we look at S22. The simulated and experimental study results are complying with each other. The novel side of this study is to have high sensitivity and higher quality factor when it is compared with similar study results. Furthermore, no such studies have been conducted so far in the literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T10:35:51Z
      DOI: 10.1177/0142331220976104
       
  • Event-triggered [math] filtering for uncertain networked control systems
           with multiple sensor fault modes
    • Authors: Ji Qi, Yanhui Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Considering the influence of sensor fault modes on the system performance in communication network, under the discrete event-triggered communication scheme (DETCS), the problems of the robust [math] filtering for a class of uncertain networked control systems (NCSs) with multiple sensor fault modes and persistent and amplitude-bounded disturbance constraints are investigated. A set of stochastic variables are adopted to describe the sensor faults, the filtering error system is established, which characterizes the effects of sensor faults and DETCS. By constructing an appropriate delay-dependent Lyapunov-Krasovskii functional, new results on stability and robust [math] performance are proposed for the filtering error system according to Lyapunov theory and the integral inequality method, and the co-design method for gaining the desired [math] filter parameters and event-triggering parameters is given in terms of linear matrix inequalities (LMIs). We notice that with the structrue of Lyapunov-Krasovskii functional which considers the piecewise-linear sawtooth structure characteristic of transmission delay, a less conservative result is obtained. Finally, three examples are provided to illustrate the feasibility of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T10:21:51Z
      DOI: 10.1177/0142331220974478
       
  • Adaptive state-feedback stabilization of stochastic nonholonomic systems
           with an unknown time-varying delay and perturbations
    • Authors: Qinghui Du
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The problem of adaptive state-feedback stabilization of stochastic nonholonomic systems with an unknown time-varying delay and perturbations is studied in this paper. Without imposing any assumptions on the time-varying delay, an adaptive state-feedback controller is skillfully designed by using the input-state scaling technique and an adaptive backstepping control approach. Then, by adopting the switching strategy to eliminate the phenomenon of uncontrollability, the proposed adaptive state-feedback controller can guarantee that the closed-loop system has an almost surely unique solution for any initial state, and the equilibrium of interest is globally asymptotically stable in probability. Finally, the simulation example shows the effectiveness of the proposed scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-29T10:17:29Z
      DOI: 10.1177/0142331220974171
       
  • Coordinated optimization control of shield machine based on dynamic fuzzy
           neural network direct inverse control
    • Authors: Xuanyu Liu, Wentao Wang, Yudong Wang, Cheng Shao, Qiumei Cong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      During shield machine tunneling, the earth pressure in the sealed cabin must be kept balanced to ensure construction safety. As there is a strong nonlinear coupling relationship among the tunneling parameters, it is difficult to control the balance between the amount of soil entered and the amount discharged in the sealed cabin. So, the control effect of excavation face stability is poor. For this purpose, a coordinated optimization control method of shield machine based on dynamic fuzzy neural network (D-FNN) direct inverse control is proposed. The cutter head torque, advance speed, thrust, screw conveyor speed and earth pressure difference in the sealed cabin are selected as inputs, and the D-FNN control model of the control parameters is established, whose output are screw conveyor speed and advance speed at the next moment. The error reduction rate method is introduced to trim and identify the network structure to optimize the control model. On this basis, an optimal control system for earth pressure balance (EPB) of shield machine is established based on the direct inverse control method. The simulation results show that the method can optimize the control parameters coordinately according to the changes of the construction environment, effectively reduce the earth pressure fluctuations during shield tunneling, and can better control the stability of the excavation surface.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-24T08:28:15Z
      DOI: 10.1177/0142331220980274
       
  • Characteristic model-based adaptive control for cryogenic wind tunnels
    • Authors: Chenhui Yu, Fei Liao, Haibo Ji, Wenhua Wu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      With the increasing requirement of Reynolds number simulation in wind tunnel tests, the cryogenic wind tunnel is considered as a feasible method to realize high Reynolds number. Characteristic model-based adaptive controller design method is introduced to flow field control problem of the cryogenic wind tunnel. A class of nonlinear multi-input multi-output (MIMO) system is given for theoretical research that is related to flow field control of the cryogenic wind tunnel. The characteristic model in the form of second-order time-varying difference equations is provided to represent the system. A characteristic model-based adaptive controller is also designed correspondingly. The stability analysis of the closed loop system composed of the characteristic model or the exact discrete-time model and the proposed controller is investigated respectively. Numerical simulation is presented to illustrate the effectiveness of this control method. The modeling and control problem based on characteristic model method for a class of MIMO system are studied and first applied to the cryogenic wind tunnel control field.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-24T08:23:55Z
      DOI: 10.1177/0142331220960652
       
  • Adaptive attitude-tracking control of spacecraft considering on-orbit
           refuelling
    • Authors: Yiqi Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the attitude-tracking control problem of spacecraft considering on-orbit refuelling. A time-varying inertia model is developed for spacecraft on-orbit refuelling, which actually includes two processes: fuel in the transfer pipe and fuel in the tank. Based upon the inertia model, an adaptive attitude-tracking controller is derived to guarantee the stability of the resulted closed-loop system, as well as asymptotic convergence of the attitude-tracking errors, despite performing refuelling operations. Finally, numerical simulations illustrate the effectiveness and performance of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-23T05:32:27Z
      DOI: 10.1177/0142331220973132
       
  • On the approximate inverse Laplace transform of the transfer function with
           a single fractional order
    • Authors: Ali Yüce, Nusret Tan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The history of fractional calculus dates back to 1600s and it is almost as old as classical mathematics. Although many studies have been published on fractional-order control systems in recent years, there is still a lack of analytical solutions. The focus of this study is to obtain analytical solutions for fractional order transfer functions with a single fractional element and unity coefficient. Approximate inverse Laplace transformation, that is, time response of the basic transfer function, is obtained analytically for the fractional order transfer functions with single-fractional-element by curve fitting method. Obtained analytical equations are tabulated for some fractional orders of [math]. Moreover, a single function depending on fractional order alpha has been introduced for the first time using a table for [math]. By using this table, approximate inverse Laplace transform function is obtained in terms of any fractional order of [math] for [math]. Obtained analytic equations offer accurate results in computing inverse Laplace transforms. The accuracy of the method is supported by numerical examples in this study. Also, the study sets the basis for the higher fractional-order systems that can be decomposed into a single (simpler) fractional order systems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-21T10:37:04Z
      DOI: 10.1177/0142331220977660
       
  • A near-optimal decentralized control approach for polynomial nonlinear
           interconnected systems
    • Authors: Mohamed Sadok Attia, Mohamed Karim Bouafoura, Naceur Benhadj Braiek
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article tackles the decentralized near-optimal control problem for the class of nonlinear polynomial interconnected system based on a shifted Legendre polynomials direct approach. The proposed method converts the interconnected optimal control problems into a nonlinear programming one with multiple constraints. In light of the formulated NLP optimization, state and control coefficients are used to design a nonlinear decentralized state feedback controller. Overall closed-loop system stability sufficient conditions are investigated with the help of Grönwall lemma. The triple inverted pendulum case is considered for simulation. Satisfactory results are obtained in both open-loop and closed-loop schemes with comparison to collocation and state-dependent Riccati equation techniques.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-21T10:34:46Z
      DOI: 10.1177/0142331220977433
       
  • On fractional optimal control problems with an application in fractional
           chaotic systems using a Legendre collocation-optimization technique
    • Authors: Safiye Ghasemi, Alireza Nazemi, Raziye Tajik, Marziyeh Mortezaee
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an intelligence method based on single layer legendre neural network is proposed to solve fractional optimal control problems where the dynamic control system depends on Caputo fractional derivatives. First, with the help of an approximation, the Caputo derivative is replaced to integer order derivative. According to the Pontryagin minimum principle for optimal control problems and by constructing an error function, an unconstrained minimization problem is then defined. In the optimization problem, trial solutions are used for state, costate and control functions, where these trial solutions are constructed by using Legendre polynomial based functional link artificial neural network. In the following, error back propagation algorithm is used for updating the network parameters (weights). At the end, some illustrative examples are included to demonstrate the validity and capability of the proposed method. Three applicable examples about chaos control of Malkus waterwheel, finance fractional chaotic models and fractional-order geomagnetic field models are also considered.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-15T06:26:32Z
      DOI: 10.1177/0142331220969583
       
  • Robust sliding model control-based adaptive tracker for a class of
           nonlinear systems with input nonlinearities and uncertainties
    • Authors: Jiunn-Shiou Fang, Jason Sheng-Hong Tsai, Jun-Juh Yan, Shu-Mei Guo
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A robust adaptive tracker is newly proposed for a class of nonlinear systems with input nonlinearities and uncertainties. Because the upper bounds of input nonlinearities and uncertainties are difficult to be acquired, the adaptive control integrated with sliding mode control (SMC) and radial basis function neural network (RBFNN) are utilized to cope with these undesired problems and effectively complete the robust tracker design. The main contributions are concluded as follows: (1) new sufficient conditions are obtained such that the proposed adaptive control laws can avoid overestimation; (2) A smooth [math] function is introduced to eliminate the undesired chattering phenomenon in the traditional SMC systems; (3) A robust tracker is proposed such that the controlled system outputs can robustly track the pre-specified trajectories directly, even when subjected to unknown input nonlinearities and uncertainties. Finally, the numerical simulation results are illustrated to verify the proposed approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-14T08:35:26Z
      DOI: 10.1177/0142331220976114
       
  • Cluster consensus of multi-agent systems with general linear and nonlinear
           dynamics via intermittent adaptive pinning control
    • Authors: Yunlong Zhang, Guoguang Wen, Ahmed Rahmani, Zhaoxia Peng, Wei Hu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the cluster consensus of multi-agent systems (MASs) with general linear and nonlinear dynamics via intermittent adaptive pinning control, where each cluster has a virtual leader whose state can be sensed by only a small part of followers on some disconnected time intervals because of communication constraints. The communication topology is considered to be weakly connected, that is, it is not necessary to be in-degree balanced, strongly connected or contain a directed spanning tree. To realise the cluster consensus, a class of intermittent adaptive pinning control protocols is proposed according to difference that the agents receive information source. The pinning gains are designed to be intermittent adaptive and with an exponential convergence rate, which will effectively reduce communication costs, avoid the pinning gains being larger than those needed in practice. Meanwhile, it guarantees that the pinning gains quickly converge to steady value. Correspondingly, some sufficient consensus criteria are derived to guarantee that the agents in the same cluster asymptotically can reach consensus while the agents in different clusters can reach different consensus. Rigorous proofs are given by the aid of Lyapunov stability theory and matrix theory. Finally, a numerical simulation example is presented to validate the main results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-14T08:33:45Z
      DOI: 10.1177/0142331220975254
       
  • The effect of measurement errors on the performance of the homogenously
           weighted moving average [math] monitoring scheme
    • Authors: Maonatlala Thanwane, Jean-Claude Malela-Majika, Philippe Castagliola, Sandile Charles Shongwe
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Monitoring schemes are typically designed under the assumption of perfect measurements. However, in real-life applications, data tend to be subjected to measurement errors, that is, a difference between the real quantities and the measured ones mostly exist even with highly sophisticated advanced measuring instruments. Thus, in this paper, the negative effect of measurement errors on the performance of the homogenously weighted moving average (HWMA) scheme is studied using the linear covariate error model for constant and linearly increasing variance. Monte Carlo simulations are used to evaluate the performance of the proposed HWMA scheme in terms of the run-length characteristics. It is observed that as the smoothing parameter increases, measurement errors have a higher negative effect on the performance of the HWMA [math] scheme. More importantly, it is shown that the negative effect of measurement errors is reduced by using multiple measurements and/or by increasing the slope coefficient of the covariate error model. Moreover, the performance of the HWMA [math] scheme is compared with the corresponding exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) [math] schemes. An illustrative example is provided to help in implementing this monitoring scheme in a real-life situation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-14T07:31:00Z
      DOI: 10.1177/0142331220973569
       
  • Consensus stability in multi-agent systems with periodically switched
           communication topology using Floquet theory
    • Authors: Mohammad Maadani, Eric A Butcher
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The stability of consensus in linear and nonlinear multi-agent systems with periodically switched communication topology is studied using Floquet theory. The proposed strategy is illustrated for the cases of consensus in linear single-integrator, higher-order integrator, and leader-follower consensus. In addition, the application of Floquet theory in analyzing special cases such as switched systems with joint connectivity, unstable subsystems, and nonlinear systems, including the use of feedback linearization and local linearization in the Kuramoto model, is also studied. By utilizing Floquet theory for multi-agent systems with periodically switched communication topologies, one can simultaneously evaluate the effects of each subsystem’s convergence rate and dwell time on overall behavior. Numerical simulation results are presented to demonstrate the efficacy of the proposed approach in stability analysis of all these cases.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-09T08:53:26Z
      DOI: 10.1177/0142331220969055
       
  • A novel order reduction method for linear dynamic systems and its
           application for designing of PID and lead/lag compensators
    • Authors: Arvind Kumar Prajapati, Rajendra Prasad
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a new model order reduction technology for the simplification of the complexity of large scale models. The proposed technique is focused on the Mihailov stability approach that guarantees the stability of the reduced model constrained that the complex system is stable. In this scheme, the denominator coefficients of the approximated simplified system are computed by using the Mihailov stability algorithm and the truncation method is used for the determination of coefficients of the numerator polynomial. The effectiveness and efficiency of the proposed approach are illustrated by comparing the step responses of the given system and approximated lower order models. The error indices such as integral square error (ISE), relative integral square error (RISE), integral absolute error (IAE) and integral time weighted absolute error (ITAE) are used as performance indices for comparing the proposed scheme with other existing standard reduced order modeling methods. The obtained reduced model is used for the designing of controllers for the original complex system. A new scheme for the determination of controllers is also proposed for the large scale models with help of reduced order modeling. The proposed technique is validated by applying it to an eighth order flexible-missile control system and a third order fuel control system. The simulation results show the dominance of the proposed methodologies over the latest model diminution techniques available in the literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-07T11:21:15Z
      DOI: 10.1177/0142331220974173
       
  • Uniform robust exact differentiator-based output feedback adaptive robust
           control for DC motor drive systems
    • Authors: Zhangbao Xu, Qingyun Liu, Xiaolei Hu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies a high-accuracy motion control method named output feedback adaptive robust control for a dc motor with uncertain nonlinearities and parametric uncertainties, which always exist in physical servo systems and deteriorate their tracking performance. As only position signal is measurable, a uniform robust exact differentiator (URED) for the unmeasurable states and adaptive control for the parametric uncertainties are integrated in the model compensation term; and the robust control is applied to handle uncertain nonlinearities and stabilize the system. Then, the stability of the closed-loop system is proved theoretically. Finally, simulation and experimental results are studied for a dc motor system to prove the control performance of the proposed control method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-07T11:19:50Z
      DOI: 10.1177/0142331220974139
       
  • A switch-source cell-based cascaded multilevel inverter topology with
           minimum number of power electronics components
    • Authors: Ali Seifi, Majid Hosseinpour, Abdolmajid Dejamkhooy
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Multilevel inverters are a new generation of DC–AC converters at medium and high voltage and power levels. In this paper, a new single-phase cascaded multilevel inverter is presented. For this purpose, a new basic cell is presented at first. Then, the new multilevel inverter structure is yielded by series connection of these cells. The proposed new cell is only capable of generating positive voltage levels, and therefore, to produce zero and negative voltage levels, the proposed structure is constructed based on H-bridge module. In order to reduce the maximum blocking voltage especially on H-bridge switches, the cascaded connection of the proposed converter is investigated. A comprehensive comparison is carried out between the proposed multilevel inverter with the classical and recently introduced structures in terms of the number of switching devices, the number of drivers, the total blocking voltage of the switches as well as the loss and efficiency. The accuracy of the proposed inverter’s performance is simulated in MATLAB/Simulink in symmetric and asymmetric topologies for a 17-level and 23-level output voltage respectively, and then evaluated by the laboratory prototype.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-07T11:17:08Z
      DOI: 10.1177/0142331220974137
       
  • Nonlinear vector model control of underactuated air cushion vehicle based
           on parameter reduction algorithm
    • Authors: Shuang Gao, Jingjing Xue
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Due to the serious drift phenomenon of underactuated air cushion vehicle, the actual trajectory is determined by the total speed and course angle. In this paper, the course angle and total speed model are derived from the general four degrees of freedom air cushion vehicle model and named nonlinear vector model. Nonlinear vector model can be used to directly design the course and total speed controllers for underactuated air cushion vehicle. Adaptive radial basis function neural network is introduced to deal with the strong nonlinearity and uncertainty of air cushion vehicle’s complex dynamics. However, the adaptive weights to be calculated and updated may be too many in each sampling period. For the relief of the burden caused by the online computing, parameter reduction algorithm is designed in this paper. It gives us a power to choose the number of online update parameters freely. Then the new trajectory tracking control method with independent total speed and course controller is designed based on nonlinear vector model and parameter reduction algorithm. The designed controller ensures that the tracking errors are uniformly ultimately bounded. Also, only a few weights need to be updated online. The effectiveness and superiority of the designed controller is verified by simulation results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-07T11:15:27Z
      DOI: 10.1177/0142331220974136
       
  • Observability analysis of combined finite automata based upon semi-tensor
           product of matrices approach
    • Authors: Zengqiang Chen, Yingrui Zhou, Zhipeng Zhang, Zhongxin Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      As a fundamental subject, the state estimation of deterministic finite automata has received considerable attention. Especially, it is increasingly necessary to study various problems based on more complex systems. In this paper, the observability of three kinds of combining automata, structured in parallel, serial and feedback manners, are investigated based on an algebraic state space approach. Compared with the formal language method, the matrix approach has great advantages in problem description and solution. Because of inconsistent frameworks of these combined automata, we optimize structure matrices by pseudo-commutation of semi-tensor product and power-reducing matrix. In addition, we construct corresponding incidence matrices by labelling to avoid superfluous null elements in the logical matrix occupying storage space. It follows that the observability analysis could be carried out under two polynomial matrices, established from the above algebraic form. Meanwhile, two algorithms, judging whether a combined automaton is initial state observable or current state observable, are presented. Finally, there are two representative examples to actualize our approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-07T11:13:07Z
      DOI: 10.1177/0142331220972524
       
  • A new approach for security of wireless sensor networks based on
           anti-synchronization of the fractional-order hyper-chaotic system
    • Authors: Hamid Reza Kaheni, Mahdi Yaghoobi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Chaotic systems have wide applications in secure communication engineering and cryptography. In this paper, improved nonlinear predictive control with whale algorithm for anti-synchronization of a fractional-order economic hyper-chaotic system is used for increasing the security of wireless sensor networks and preventing intrusion. By chaotic masking method and the T-S fuzzy model, the message signal is encoded at the wireless sensor side and it is placed along the transmitter route. In the central station, the message signal is decoded using the T-S fuzzy model and the predictive control by anti-synchronizing the fractional-order hyper-chaotic slave system. To reduce the effect of disturbances, a sign function of error is added to the predictive control. Finally, simulation results indicate the proper performance of the proposed nonlinear predictive control for anti-synchronizing the fractional-order hyper-chaotic systems in secure communications.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-07T11:11:08Z
      DOI: 10.1177/0142331220972233
       
  • Three-dimensional sliding mode guidance law for maneuvering target with
           prescribed performance and input saturation
    • Authors: Meng-chen Ma, Li-Guo Tan, Shen-min Song
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The three-dimensional sliding mode guidance laws with prescribed performance and saturation actuator are proposed for maneuvering target. The proposed guidance laws can ensure the line of sight (LOS) angle converges according to the prescribed performance with actuator saturation and the convergence rate, the steady state error and the maximum overshoot can be preset in advance. A novel transformed error function is designed by combining the LOS tracking error with the performance constraint function. Then, to further solve the problem of input saturation, the saturation function and auxiliary system are introduced. Additionally, this paper discusses the problem whereby the upper bound of the aggregate uncertainty, including the target information, is unavailable. An adaptive sliding mode guidance law with prescribed performance is presented for this scenario. Experiments comparisons are conducted with other forms of guidance laws. Simulation results show that the guidance laws proposed in this paper achieve effective performance.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-12-01T12:43:16Z
      DOI: 10.1177/0142331220972021
       
  • Experimental verification of lithium-ion battery prognostics based on an
           interacting multiple model particle filter
    • Authors: Shuai Wang, Wei Han, Lifei Chen, Xiaochen Zhang, Michael Pecht
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A new data-driven prognostic method based on an interacting multiple model particle filter (IMMPF) is proposed for use in the determination of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries and the probability distribution function (PDF) of the uncertainty associated with the RUL. An IMMPF is applied to different state equations. The battery capacity degradation model is very important in the prediction of the RUL of Li-ion batteries. The IMMPF method is applied to the estimation of the RUL of Li-ion batteries using the three improved models. Three case studies are provided to validate the proposed method. The experimental results show that the one-dimensional state equation particle filter (PF) is more suitable for estimating the trend of battery capacity in the long term. The proposed method involving interacting multiple models demonstrated a stable and high prediction accuracy, as well as the capability to narrow the uncertainty in the PDF of the RUL prediction for Li-ion batteries.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-26T06:09:31Z
      DOI: 10.1177/0142331220961576
       
  • Static output feedback control of switched nonlinear systems with
           time-varying delay and parametric uncertainties under asynchronous
           switching
    • Authors: Amin Taghieh, Mohammad Hossein Shafiei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents the design of a static output feedback controller for a class of switched nonlinear systems subject to time-varying delay and uncertainties under asynchronous switching. Based on the Lyapunov-Krasovskii approach and the average dwell time technique, sufficient conditions are derived in the form of linear matrix inequalities to design a static output feedback controller for robust stabilization of a switched system. These conditions rely on the upper bounds of the switching lag between the controllers and subsystems, time-varying delay, and uncertain parameters. Using affine parametric uncertainties leads to a conservatism reduction in the control problem. Simulation results are presented to demonstrate the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-24T06:16:35Z
      DOI: 10.1177/0142331220969056
       
  • Extended state observer-based robust control of an omnidirectional
           quadrotor with tiltable rotors
    • Authors: Kaiwen Lu, Zhong Yang, Luwei Liao, Yuhong Jiang, Changliang Xu, Hao Xu, Qiuyan Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A quadrotor with tiltable rotors is a kind of omnidirectional multirotor aerial vehicle (MAV) that has demonstrated advantages of decoupling control of position from the control of orientation. However, quadrotors with tiltable rotors usually suffer from Coriolis term, modeling error and external disturbance. To this end, the extended state observer (ESO)-based controller is designed to estimate and compensate for the above adverse effects. Especially, the controller involves position and attitude controller in parallel. The attitude controller is made up of cascade control-loops: an outer quaternion-based attitude control-loop and an inner ESO-based Proportional derivative angular velocity control-loop. Similarly, the position controller consists of an outer proportional position control-loop and an inner ESO-based PD velocity control-loop. Besides, a linear control allocation strategy, which allocates the controller outputs to tilting angles and motor speed directly, is proposed to avoid the nonlinear allocation matrix. Extensive simulations and flight tests are carried out to illustrate the effectiveness and robustness of the proposed ESO-based controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-23T06:31:28Z
      DOI: 10.1177/0142331220966427
       
  • A novel mobile agent-based distributed evidential expectation maximization
           algorithm for uncertain sensor networks
    • Authors: Mohiyeddin Mozaffari, Behrouz Safarinejadian, Mokhtar Shasadeghi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel mobile agent-based distributed evidential expectation maximization (MADEEM) algorithm is presented for sensor networks. The proposed algorithm is used for probability density function estimation and data clustering in the presence of uncertainties in sensor measurements. It is assumed that the sensor measurements are statistically modeled by a common Gaussian mixture model. The proposed algorithm maximizes a new generalized likelihood criterion in an iterative and distributed manner. For this purpose, mobile agents compute some local sufficient statistics by using local measurements of each sensor node. After the local computations, the global sufficient statistics are updated. At the end of iterations, the parameters of the probability density function are updated by using the global sufficient statistics. The mentioned process will be continued until the convergence criterion is satisfied. Convergence analysis of the proposed algorithm is also presented in this paper. After the convergence analysis, the simulation results show the promising performance of the proposed algorithm. Finally, the last part of the paper is devoted to the concluding remarks.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-18T11:12:49Z
      DOI: 10.1177/0142331220969580
       
  • Event-triggered robust model predictive control for Lipschitz nonlinear
           networked control systems subject to communication delays
    • Authors: Saeid Ghorbani, Ali Akbar Safavi, S. Vahid Naghavi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the problem of event-triggered robust model predictive control (MPC) was examined for a class of Lipchitz nonlinear networked control systems (NCS) with network-induced delays and subject to external disturbances. An event-triggering scheme for a continuous-time NCS was proposed, which reduced the communication traffic and computational burden of the MPC algorithm simultaneously. In comparison with the existing event-triggered nonlinear MPC (NMPC) approaches, the controller in this paper was designed as a state feedback control law, which minimized a “worst-case” performance index over an infinite horizon subject to constraints on the control input. The controller and event generator parameters were developed as a convex optimization problem, encompassing some linear matrix inequalities (LMIs). Simulation results showed that the proposed event-triggering NMPC scheme preserved closed-loop performance while reducing the communication rate and the computational time.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-18T11:10:44Z
      DOI: 10.1177/0142331220969058
       
  • Robust maximum power point tracking with a novel second order sliding mode
           controller
    • Authors: Javad Jafari Fesharaki, Zahra Heydaran Daroogheh Amnyieh, Vahid Jafari Fesharaki
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a robust second order sliding mode controller as maximum power point tracking (MPPT) technique in a photovoltaic (PV) boost dc-dc converter with applications to stand-alone systems. The proposed method is independent respect to load type, robust against parametric uncertainties and disturbances. By Lyapunov theorem the asymptotic stability of the closed loop control system is proven. The proposed second order sliding mode controller is simulated with Matlab software and experimental set up in presence of sinusoidal disturbances on output voltage.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-18T11:08:27Z
      DOI: 10.1177/0142331220968403
       
  • Robust stability analysis of uncertain incommensurate fractional order
           quasi- polynomials in the presence of interval fractional orders and
           interval coefficients
    • Authors: Majid Ghorbani, Mahsan Tavakoli-Kakhki
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper deals with the robust stability analysis of a class of incommensurate fractional order quasi-polynomials with a general type of interval uncertainties. The concept of the general type of interval uncertainties means that all the coefficients and orders of the fractional order quasi-polynomials have interval uncertainties. Generally, the computational complexity of specifying the robust stability of such a quasi-polynomial is shown in this paper. To this end, the robust stability is studied by Principle of Argument theorem. In fact, by presenting two theorems and three lemmas it is shown that the robust stability of a fractional order quasi-polynomial involving the general type of uncertainty can be simply investigated without needing to plot its value set by heavy computations. Examples are attested the validity of the paper results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-11T10:56:58Z
      DOI: 10.1177/0142331220968965
       
  • Fast battery capacity estimation using convolutional neural networks
    • Authors: Yihuan Li, Kang Li, Xuan Liu, Li Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Lithium-ion batteries have been widely used in electric vehicles, smart grids and many other applications as energy storage devices, for which the aging assessment is crucial to guarantee their safe and reliable operation. The battery capacity is a popular indicator for assessing the battery aging, however, its accurate estimation is challenging due to a range of time-varying situation-dependent internal and external factors. Traditional simplified models and machine learning tools are difficult to capture these characteristics. As a class of deep neural networks, the convolutional neural network (CNN) is powerful to capture hidden information from a huge amount of input data, making it an ideal tool for battery capacity estimation. This paper proposes a CNN-based battery capacity estimation method, which can accurately estimate the battery capacity using limited available measurements, without resorting to other offline information. Further, the proposed method only requires partial charging segment of voltage, current and temperature curves, making it possible to achieve fast online health monitoring. The partial charging curves have a fixed length of 225 consecutive points and a flexible starting point, thereby short-term charging data of the battery charged from any initial state-of-charge can be used to produce accurate capacity estimation. To employ CNN for capacity estimation using partial charging curves is however not trivial, this paper presents a comprehensive approach covering time series-to-image transformation, data segmentation, and CNN configuration. The CNN-based method is applied to two battery degradation datasets and achieves root mean square errors (RMSEs) of less than 0.0279 Ah (2.54%) and 0.0217 Ah (2.93% ), respectively, outperforming existing machine learning methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-06T05:35:23Z
      DOI: 10.1177/0142331220966425
       
  • A mutual approach for profit-based unit commitment in deregulated power
           system integrated with renewable energy sources
    • Authors: T Anbazhagi, K Asokan, R AshokKumar
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a mutual technique for solving the profit-based unit commitment (PBUC) problem in deregulated power system integrated with wind power. The proposed mutual approach is the joined execution of different solution techniques and known by the non-dominated sorting of moth fly optimization (MFO) with levy flight search (NSMFLF) technique. In the proposed approach, the levy flight search and the traditional moth flame optimization looking conduct is prepared in parallel as for the objective function and update the conceivable combination of generation units. The objective function maximizes the profit of the generating companies as for the revenue and total fuel cost in light of the gauge estimations of power demand, price and reserve power. Here, the uncertainty events of the wind power are predicted by utilizing the artificial intelligence techniques. Thus, the system is ensured with the high utilization of wind power. Finally, the non-dominated sorting is performed to choose the optimal solution from the conceivable generated combinations. The optimal combination used to maximize the profit of the generating companies and solve the PBUC problem in light of the objective function. The proposed method is implemented in the matrix laboratory working stage and the outcomes are analyzed with the current strategies.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-04T06:13:20Z
      DOI: 10.1177/0142331220966312
       
  • Fixed-time trajectory tracking control for multiple nonholonomic mobile
           robots
    • Authors: Meiying Ou, Haibin Sun, Zhenxing Zhang, Lingchun Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the fixed-time trajectory tracking control for a group of nonholonomic mobile robots, where the desired trajectory is generated by a virtual leader, the leader’s information is available to only a subset of the followers, and the followers are assumed to have only local interaction. According to fixed-time control theory and adding a power integrator technique, distributed fixed-time tracking controllers are developed for each robot such that all states of each robot can reach the desired value in a fixed time. Moreover, the settling time is independent of the system initial conditions and only determined by the controller parameters. Simulation results illustrate and verify the effectiveness of the proposed schemes.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-02T11:37:58Z
      DOI: 10.1177/0142331220966419
       
  • Constrained cuckoo search algorithm and Takagi-Sugeno fuzzy models for
           predictive control
    • Authors: Adel Taeib, Hichem Salhi, Abdelkader Chaari
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a new predictive control scheme formulated by using the Takagi-Sugeno fuzzy modeling method and a new constrained cuckoo search algorithm. The cuckoo search algorithm is used to determine the predictive controls by minimizing a constrained criterion. The Takagi-Sugeno fuzzy modelling approach is applied to forecast the states of the process. At the optimization stage, the proposed cuckoo search provides the control action taking into account constraints. The performances of the developed method are tested during its application in the three-tank process. Therefore, the experimental results demonstrate that the combination of the philosophy of the fuzzy model and cuckoo search is very good in the controlling of nonlinear processes. In addition, the closed-loop performance of the developed method is compared to approach based with the particle swarm optimisation algorithm and those obtained with fuzzy model predictive controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-02T11:36:18Z
      DOI: 10.1177/0142331220966308
       
  • Distributed control of multi-agents system via static feedback controllers
           under directed networks
    • Authors: Zhikun Luo, Zhifeng Sun, Junmin Peng, Fengli Ma
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      During recent years, a lot of distributed control approaches based on static feedback controllers have been proposed to realize consensus of multi-agents systems with undirected topologies. However, many of these approaches have not been generalized to systems with directed topologies yet. Therefore, in this paper, for first- and second-order multi-agents systems with directed topologies, we propose a series of new nonlinear consensus protocols based on traditional design. With integral Lyapunov functions, we can prove the stability of proposed control protocols and a group of simulation results are also given to testify our theory.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-30T10:07:00Z
      DOI: 10.1177/0142331220965835
       
  • Event-triggered H∞ control for networked control systems under
           denial-of-service attacks
    • Authors: Liruo Zhang, Sing Kiong Nguang, Shen Yan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the event-triggered H∞ control for networked control systems under the denial-of-service (DoS) attacks. First, a novel system model is established considering random, time-constraint DoS attacks. Second, an event-triggered scheme including an off-time is proposed to reduce the unnecessary occupation of network resources, with which a prescribed minimum inter-triggering time is guaranteed and Zeno problem is avoided. Third, sufficient conditions for the existence of an event-triggered controller which ensures the exponential stability of the closed-loop system with desired H∞ performance are formulated in linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed method is examined by two illustrative examples, where a real communication network based on the ZigBee protocol is utilized.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-29T07:57:19Z
      DOI: 10.1177/0142331220966417
       
  • Finite time coverage tracking algorithm of maneuvering target by multiple
           mobile agents
    • Authors: Longbiao Ma, Yongjie Yan, Yang Zhang, Yan Liu, Yungang Tian
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a problem regarding how multiple mobile agents track a high-speed maneuvering target is considered. Due to the uncertainties of the target caused by the background noises, we use a dynamic non-uniform region to describe the location of target. Therefore, the cooperative tracking problem is transformed into a problem to cover a known dynamic non-uniform region. In order to capture the high-speed maneuvering target, the mobile agents with global sensing areas and limited actuation region are designed to track and cover the dynamic region. Also, the probability that the target appear in the circle is denoted by a probability density function and a performance index function is given to describe the effectiveness of covering a moving target. With observer-based estimation and dynamic formation control, a coverage tracking algorithm is proposed so that the group of agents catch the target by a coverage tracking policy in finite time.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-29T07:50:57Z
      DOI: 10.1177/0142331220966307
       
  • Multi-phase flow measurement in a gas refinery using decentralized
           Lyapunov–based adaptive observer
    • Authors: Abolfazl Varvani Farahani, Mohsen Montazeri
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a new Lyapunov-based nonlinear adaptive observer and joint unscented Kalman filter to precisely estimate the states and the parameters for the low-order lumped model of the multi-phase flow at the gas refinery. The main focus of the study is to estimate the discharge coefficient of the orifice meter installed on the interconnection lines of the subsystems (parameters) and the total oil and gas mass flows (states). The adaptive estimation is conducted using the real-time measurements including choke pressure, bottom line pressure, single-phase gas flow, and single-phase liquid flow in the refinery outlet. To check the stability and performance of the system against changes, the Lyapunov theory has been used. In all stages, the investigations were based on the data collected from the actual process in the South Pars Gas Complex, Iran. Using the dynamic HYSYS simulation, it is found that the proposed adaptive observer is capable of estimating the oil and gas flows and identifying the discharge coefficient of the flow meter at issue. To show the performance of the proposed adaptive observer, it is evaluated against and compared with the unscented Kalman filter. The comparison of the results obtained from the proposed observer, unscented Kalman filter, and dynamic HYSYS simulation with data collected from the actual process of the refinery shows the appropriate performance of the both estimation algorithms in detecting the changes in liquid and gas flow rates and the consistency of their results with the real process in the South Pars Gas Complex. The simulations reveal that low-order lumped model is sufficient for estimation of parameters and states of the multiphase flow entering the gas refinery.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-28T08:58:34Z
      DOI: 10.1177/0142331220964978
       
  • On the design of extended state observer-based robust finite controller:
           For underactuated robotic system with multiple sources of uncertainties
    • Authors: Hui Li, Ruiqin Li, Jianwei Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Controlling an underactuated robot is always an important research and engineering issue, especially when the robot is suffering from multiple sources of uncertainties, such as unmodeled dynamics, external disturbance, and parameter uncertainties. To cope with these uncertainties in such uncertain nonlinear systems which is not fully-actuated, this paper proposes a control method that can actively estimate these uncertainties via the extended state observer (ESO), under the scheme of output-feedback control, the lumped uncertainties can be online estimated and actively compensated. Every joint of the underactuated robotic system can robustly reach the pre-given state in finite-time even though there are only fewer joints than the actual number of joints that can be controlled directly. The experimental results demonstrate the control process and validate that the proposed method is feasible for the studied underactuated robotic system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-26T04:01:15Z
      DOI: 10.1177/0142331220966111
       
  • Finite-time observer-based control for Markovian jump systems with
           time-varying generally uncertain transition rates
    • Authors: Mengjun Li, Xiaohang Li, Dunke Lu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper addresses the finite-time observer-based control for Markovian jump systems with time-varying generally uncertain transition rates. In order to estimate the states, a suitable observer is designed, in which both external disturbance and Brownian motion exist. In order to solve the complex time-varying transition rates, a quantization mechanism is raised to prove the closed-loop system and the observer error system be stable. Sufficient conditions of the existences of both the observer and the observer-based controller are derived in terms of linear matrix inequalities. Eventually, two practical examples are given to testify the correctness of the results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-26T03:58:54Z
      DOI: 10.1177/0142331220964706
       
  • Unified power flow controller in grid-connected hybrid renewable energy
           system for power flow control using an elitist control strategy
    • Authors: Raghu Thumu, Kadapa Harinadha Reddy, Chilakala Rami Reddy
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Due to the intermittent nature of renewable sources, miss-matching between power generation and load power causes a deviation from the desired voltage and frequency in power supply. To solve this problem, a new control technique has been proposed for the power flow control with the unified power flow controller (UPFC) in grid-connected hybrid renewable energy systems such as photovoltaic-wind. The proposed control technique combines the binary version of the grey wolf optimization (bGWO) and recurrent neural network (RNN). Here, bGWO is utilized to generate the dataset of control signals for shunt and series converters of the UPFC. Based on the accomplished dataset, the RNN technique performs and predicts the optimal control signals of the UPFC. Likewise, the proposed control scheme regulates the voltage deviation and minimizes the power losses simultaneously. Then, the proposed model is executed in Matrix Laboratory/Simulink working stage and the execution is assessed with the existing techniques such as fuzzy logic controller, improved particle swarm optimization and grey wolf optimization. The optimized gain parameters and elapsed time of the proposed and existing technique is also analysed. The optimized gain parameters such as KpKi of the proposed hybrid technique are 2.5 and 150. The elapsed time of the proposed technique is 30.15sec. Overall, the comparison results demonstrate the superiority of the proposed technique and confirm its potential to solve the above-mentioned problems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-26T03:56:32Z
      DOI: 10.1177/0142331220957890
       
  • Finite-time sliding mode control for a 3-DOF fully actuated autonomous
           surface vehicle
    • Authors: Ali Abooee, Mohammad Hayeri Mehrizi, Mohammad Mehdi Arefi, Shen Yin
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper deals with the finite-time trajectory tracking problem for a typical 3-DOF (degree of freedom) autonomous surface vehicle (ASV) subjected to parametric uncertainties and environmental disturbances. Based on the nonsingular terminal sliding mode control (NTSMC) method, several separate classes of robust control inputs are designed to exactly steer all position states of the 3-DOF AVS to the desired paths during alterable finite times. By exploiting the Lyapunov stability theorem and using mathematical analysis, it is proven that all classes of designed robust control inputs are able to fulfill the mentioned finite-time tracking aim. Moreover, three applicable formulas (represented as several nonlinear inequalities) are extracted to determine the required total finite times for the suggested control schemes. Lastly, all designed control methods are numerically tested onto a benchmark 3-DOF AVS called CyberShip II. Provided computer-based numerical simulations (using MATLAB software) depicted the acceptable performance of the proposed control techniques.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-26T03:54:32Z
      DOI: 10.1177/0142331220957516
       
  • Contactless interactive control technology based on switching filtering
           algorithm
    • Authors: Yifan Fang, Lei Yu, Shumin Fei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In the large-screen interactive system with lidar sensor, due to the low accuracy of the lidar and the instability of the users’ gestures, the system’s recognition and tracking of gesture coordinates cannot be well obtained. Aiming at solving the problems of swaying and drifting gestures of the traditional filtering algorithm with a lidar sensor, this paper proposes a contactless interaction control technology based on switching filtering algorithm, which can realize non-contact high-precision multi-point interaction. The proposed algorithm first recognizes and extracts users’ gestures, and then the gestures are mapped to the screen position. Also, the mouse operation is simulated to realize operations such as selecting, sliding, and zooming in and out. Besides, the algorithm can effectively solve jitter and drift problems caused by scanning defects of radar and instability of the user gesture operations. Experimental results show that by applying the switching filtering algorithm to the contactless human-computer interaction system, the interactive trajectory becomes smoother and more stable compared with the traditional filtering algorithms. The proposed algorithm exhibits excellent accuracy and real-time performance, supporting efficient interaction with multiple people.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-26T03:52:32Z
      DOI: 10.1177/0142331220966132
       
  • Three-dimensional target tracking strategy based on guidance laws and
           optimal information fusion
    • Authors: Yihua Dong, Shulin Feng, Liuchen Tai
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a method for pursuer to track a moving target in a three-dimensional space. The method is based on the guidance laws combined with the kinematics equations of the pursuer and the target. The maneuvers of the target are prior unknown to the pursuer. Guidance laws used for tracking are the deviated pursuit and the proportional navigation, and the method presents a family of navigation laws resulting in a rich behavior for different parameters. For the three-dimensional scenario, two cases-not presenting interference and presenting interference are considered. In the absence of interference, the control strategy is proposed to implement the problem of tracking. In the presence of interference, an optimal information fusion Kalman filter weighted by scalars and guidance laws are combined to improve the trajectory tracking precision, and the combination can enrich the application range of information fusion and guidance laws. Simulations are conducted to demonstrate the effectiveness and reliability of the proposed control strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-20T04:34:52Z
      DOI: 10.1177/0142331220962793
       
  • A hybrid technique used in grid integration of photovoltaic system for
           maximum power point tracking with multilevel inverter
    • Authors: S. Saravanan, T. S. Sivakumaran
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A new hybrid technique for grid integration of solar photovoltaic system using modified incremental conductance maximum power point tracking algorithm with multi-output converter and multilevel inverter is proposed in the paper. The proposed hybrid technique is the joint execution of improved dolphin echolocation algorithm and gradient boosting decision trees and this way the proposed technique is named as IDE-GBDT technique. The novelty of the proposed work is the dolphin echolocation algorithm, which is integrated by the crossover and the mutation function so it is named as IDE. In the proposed technique, the multi-output converter is the combination of boost converter and switched capacitor function to generate different self-balanced output voltages. The utilization of multilevel inverter in the proposed system provides better quality of output voltage and current waveform thereby reducing the size of passive filters. Also, eliminates the requirement of bulky transformers for grid integration. Multicarrier unipolar phase disposition pulse width modulation technique is employed for triggering the switches of the multilevel inverter. The maximum power point tracking algorithm uses the estimated active power output of the generator as its input and generates command speed so that maximum power is transferred to the dc link. This control system also incorporates a loss minimization approach to minimize the losses in the generator and hence to improve the efficiency of the photovoltaic system. Finally, the performance of the proposed maximum power point tracking control of wind and photovoltaic power generation schemes is executed in Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. The proposed technique is compared with the existing techniques and the observed total harmonic distortion of the proposed technique in all the cases is 0.67%, 0.51%, 0.58%, 0.63%, 0.92%, and 1.03% and the total harmonic distortion is found to be very less compared with existing techniques.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-19T05:20:31Z
      DOI: 10.1177/0142331220964101
       
  • Disturbance-observer-based control for semi-Markovian jump systems with
           time-varying delay and generally uncertain transition rate
    • Authors: Tianbo Xu, Xianwen Gao, Wenhai Qi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The analysis result of disturbance-observer-based control (DOBC) for semi-Markovian jump systems (S-MJSs) with time-varying delay and generally uncertain transition rate (TR) is given in this paper. At present, there are still some urgent problems needed to be solved for S-MJSs such that conservative of stability, difficult of obtaining of TR in practical system, and the unexpected transient performance is always inevitable, such as larger overshoots and longer settling time. Unlike the existing methods, the proposed method considers the external disturbance, limitation on domain of control signal, uncertain parameters and time-varying delay in the S-MJSs. The piecewise analysis method for time-varying delay systems is extended to DOBC for S-MJSs. First of all, the sufficient condition of stochastic stability based on S-MJSs with more general TR is derived by piecewise Lyapunov-Krasovskii functional. Then, the disturbance observer is designed for estimating the actual disturbance, and the anti-disturbance controller is designed to deal with the control problem of S-MJSs. Furthermore, the problem of actuator saturation is addressed. Finally, two practical example is employed to testify the correctness of the proposed methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-19T05:18:31Z
      DOI: 10.1177/0142331220963499
       
  • Nonlinear coordinated control design of generator excitation and static
           var compensator for power system via input-output linearization
    • Authors: Salma Keskes, Souhir Sallem, Mohamed Ben Ali Kammoun
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a nonlinear coordinated controller for a single machine infinite bus power system. The later consists of a synchronous generator connected to the infinite bus via transmission lines, which are equipped with a static var compensator. The proposed control strategy aims to control simultaneously the excitation system of the synchronous generator and the static var compensator in order to improve transient stability and voltage regulation. The input output linearization theory and pole-assignment technique are employed to design the nonlinear controller. The controller’s performance in single machine infinite bus power system is then examined using simulation studies when the studied power system is subjected to three-phase short circuit with a 100ms duration. The results validate the efficiency of the proposed controller, which is based mainly on the good regulation of the static var compensator voltage with removing the static error after fault elimination.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-16T04:39:09Z
      DOI: 10.1177/0142331220964361
       
  • A state augmented adaptive backstepping control of wheeled mobile robots
    • Authors: Seyed Mohammad Ahmadi, Mojtaba Behnam Taghadosi, AmirReza Haqshenas M.
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The present paper aims to design an integrated kinematic/dynamic-based tracking controller for wheeled mobile robots (WMRs) considering motors’ dynamics. By defining a reference WMR, the role of kinematic controller is to not only minimize the posture error which indicates the difference between the reference and actual WMRs, but also to generate a desired path for the actual WMR. The kinematic tracking control problem of WMRs is so challenging if motors’ dynamics, parametric and nonparametric uncertainties and external disturbances are considered. Thus, proposing a dynamic control law alongside a kinematic control is unavoidable. In this study, we propose a new dynamic controller, namely, a state augmented adaptive backstepping such that the desired path is asymptotically tracked. Several numerical results accompanied by 3D simulations of trajectory tracking control of a WMR in ‘Simscape Multibody’ environment and comparisons with two well-designed controllers in the literature are reported to show the high performance of proposed control structure.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-13T05:40:36Z
      DOI: 10.1177/0142331220961700
       
  • An efficient optimal power flow management based microgrid in hybrid
           renewable energy system using hybrid technique
    • Authors: P Annapandi, R Banumathi, NS Pratheeba, A Amala Manuela
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the optimal power flow management-based microgrid in hybrid renewable energy sources with hybrid proposed technique is presented. The photovoltaic, wind turbine, fuel cell and battery are also presented. The proposed technique is the combined execution of both spotted hyena optimization and elephant herding optimization. Spotted hyena optimization is utilized to optimize the combination of controller parameters based on the voltage variation. In the proposed technique, the spotted hyena optimization combined with elephant herding optimization plays out the assessment procedure to establish the exact control signals for the system and builds up the control signals for offline way in light of the power variety between source side and load side. The objective function is defined by the system data subject to equality and inequality constraints such as real and reactive power limits, power loss limit, and power balance of the system and so on. The constraint is the availability of the renewable energy sources and power demand from the load side in which the battery is used only for lighting load. By utilizing the proposed method, the power flow constraints are restored into secure limits with the reduced cost. At that point, the proposed model is executed in the Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. In this article, the performance analysis of proposed and existing techniques such as elephant herding optimization, particle swarm optimization, and bat algorithm are evaluated. Furthermore, the statistical analysis is also performed. The result reveals that the power flow of the hybrid renewable energy sources by the proposed method is effectively managed when compared with existing techniques.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-13T05:38:09Z
      DOI: 10.1177/0142331220961687
       
  • Evaluation of response characteristics of thin film gauge for conductive
           heat transfer mode
    • Authors: Tanweer Alam, Rakesh Kumar
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Heat transfer analysis is the one of the most important designing aspects for many engineering systems. The design prospect in the preview of heat transfer focuses on the prediction of heat flux with the help of measured transient temperature data. Thin film gauges are one of the most predominant method for the heat flux prediction especially for short duration transient temperature measurement. Thin film gauges are usually exposed to the heated environment for the measurement purpose. However, there are some prominent research areas like ablation phenomenon met to spacecraft thermal shields during re-entry to the atmosphere, for which direct exposure of the thin film gauge to the heated environment causes the functional and working difficulties associated with the gauge. In the present study, it is aimed to investigate the suitability of thin film gauge for the conduction-based short duration measurement. An experimental set up is fabricated, which is used to supply the heat load to the hand-made thin film gauge using platinum as sensing element and quartz as a substrate. The transient temperature data is recorded during experiment is further compared with the simulated temperature histories obtained through finite element analysis. The heat flux estimation for both the analysis is made using measured transient temperature data by convolute integral of one- dimensional heat conduction equation. The estimated heat flux value for the experimental and numerical result is found to be in excellent agreement.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-13T05:34:48Z
      DOI: 10.1177/0142331220960665
       
  • A nonlinear method for monitoring industrial process
    • Authors: Yuan Li, Chengcheng Feng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Aiming at fault detection in industrial processes with nonlinear or high dimensions, a novel method based on locally linear embedding preserve neighborhood for fault detection is proposed in this paper. Locally linear embedding preserve neighborhood is a feature-mapping method that combines Locally linear embedding and Laplacian eigenmaps algorithms. First, two weight matrices are obtained by the Locally linear embedding and Laplacian eigenmaps, respectively. Subsequently, the two weight matrices are combined by a balance factor to obtain the objective function. Locally linear embedding preserve neighborhood method can effectively maintain the characteristics of data in high-dimensional space. The purpose of dimension reduction is to map the high-dimensional data to low-dimensional space by optimizing the objective function. Process monitoring is performed by constructing T2 and Q statistics. To demonstrate its effectiveness and superiority, the proposed locally linear embedding preserve neighborhood for fault detection method is tested under the Swiss Roll dataset and an industrial case study. Compared with traditional fault detection methods, the proposed method in this paper effectively improves the detection rate and reduces the false alarm rate.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-12T09:15:31Z
      DOI: 10.1177/0142331220959232
       
  • An efficient modified dragonfly algorithm and whale optimization approach
           for optimal scheduling of microgrid with islanding constraints
    • Authors: K.S Kavitha Kumari, R. Samuel Rajesh Babu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presented an effective technique for considering optimal scheduling of microgrid (MG) with islanding constraints. The proposed optimal scheduling approach is the combination of both the modified dragonfly algorithm (MDA) and whale optimization algorithm (WOA)-based approach named as (MDAWO). In this work, the searching conduct of the dragonflies is altered by the effective WOA approach. This WOA is used to the optimal scheduling of MG and also significantly reduces the computational burden. In this paper, the MDAWO is the appraisal technique used to set up the definite schedule of the MG coupling subject to the power assortment. The equality and inequality constraints are utilized to characterize the target capacity of a projected approach using the system information. Batteries act as an energy source to adjust the MG with continual running at an unfaltering and stable output control. Finally, the performance of the proposed technique is executed through the MATLAB/Simulink working platform with two different scenarios. With these two different scenarios, the proposed technique performance is compared with existing techniques such as dragonfly algorithm, firefly and gravitational search algorithm. Furthermore, the statistical analysis of the proposed technique based on cost and fitness are analyzed. Numerical simulations demonstrate the effectiveness of the proposed MG optimal scheduling model and explore its economic and reliability merits.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-07T08:20:33Z
      DOI: 10.1177/0142331220961657
       
  • Energy management and damping improvement of a DC microgrid with constant
           power load using interconnection and damping assignment-passivity based
           control
    • Authors: Soumya Samanta, Saumitra Barman, Jyoti Prakash Mishra, Prasanta Roy, Binoy Krishna Roy
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper deals with (i) damping improvement and (ii) energy management of a DC microgrid for improvement of its stability. The direct current (DC) microgrid has a solar-photovoltaic system as a renewable source and fuel cell-battery combination as a backup system to supply power to constant power loads (CPLs). The presence of CPLs in a DC microgrid makes the stability problem more challenging since the negative impedance characteristics of CPLs bring instability into the system. A control approach using interconnection and damping assignment-passivity based control (IDA-PBC) is proposed in this paper to address both the objectives. The proposed control approach provides an efficient energy management, the required damping and also maintains the stability by making the system passive. The tuning parameters of the control laws are adapted incorporating the state of charge (SoC) for the effective energy management. In addition, an integral action is added with the proposed control laws to eliminate the steady-state error in the voltage level of the DC bus and load bus. The proposed IDA-PBC control along with an integral action is compared with four other control approaches, and reveals its better performances. The MATLAB/Simulink results show that the proposed control technique provides better responses in terms of providing damping and effective energy management.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-01T07:20:02Z
      DOI: 10.1177/0142331220960828
       
  • The instrument fault detection and identification based on kernel
           principal component analysis and coupling analysis in process industry
    • Authors: Yanjie Liang, Zhiyong Gao, Jianmin Gao, Guangnan Xu, Rongxi Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the fault detection problem of instruments in process industry. Considering the difficulty of fault identification and the problems of multivariable and large computation complexity based on traditional kernel principal component analysis (KPCA), this paper presents a new method for fault detection and identification, which combines the coupling analysis with kernel principal component for multivariable fault detection and employed the local outlier factor (LOF) for multivariable fault identification. The new method consists of three parts. Firstly, according to nonlinear correlation of multivariable, coupling analysis and module division of variables based on detrended cross-correlation analysis (DCCA) are considered to reduce false alarm rate (FAR) and missed detection rate (MDR) in fault detection and identification. Secondly, KPCA is employed to detect fault in each sub-module of variables. Finally, for the sub-module which has the fault detected in second step, the LOF is adopted to calculate abnormal contribution of each variable in sub-modules to realize fault identification. To prove that the new method has the better capability of processing multivariable fault detection and the more accuracy rate on fault detection and identification than the conventional methods of KPCA, a case study on Tennessee process is carried out at the end.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-10-01T07:16:39Z
      DOI: 10.1177/0142331220960247
       
  • Identification of switched linear systems based on
           expectation-maximization and Bayesian algorithms
    • Authors: Xiujun Chai, Hongwei Wang, Xinru Ji, Lin Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study aims to determine how to deal with the identification from input and output data of switched linear systems (SLSs) with Box and Jenkins models. The identification difficulties of this system are that there exist unknown switched signal, unknown middle variables, and colored noise terms in the identification process. To address these issues, the proposed identification method proceeds in two stages, including the estimation of the switched signal of SLSs and the identification of the parameters of all subsystems. First, the Gaussian mixture model is established to represent the distribution of the input and output data of SLSs. Then, the posterior probability is calculated by the expectation-maximization (EM) algorithm and the naive Bayes classifier, and the switched signal is estimated according to the maximum probability criterion. Next, the auxiliary model based multi-innovation generalized extended least square (AM-MI-GELS) algorithm is used to estimate the parameters of all subsystems. Finally, the effectiveness of the proposed method is verified through the simulation example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-28T10:04:56Z
      DOI: 10.1177/0142331220960249
       
  • Robust [math] control for nonlinear course system of unmanned surface
           vessel with polytopic uncertainty based on sum of squares
    • Authors: Yanwei Huang, Zhenyi Liu, Wenchao Huang, Shaobin Chen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the nonlinear robust [math] control is investigated for nonlinear course control systems of unmanned surface vessel (USV) with uncertain parameters and external disturbance. Firstly, we suppose that the part or all of the system parameters are unknown but within some ranges, due to the effect of different conditions such as the loading of ship. Then, the course system is modeled as a polynomial one with time invariant polytopic uncertainty. With the aid of parameter dependent Lyapunov function method and positive polynomial theory, the sufficient conditions are given for stability and stabilization with [math] performance. These conditions are formulated in terms of parameter-dependent nonlinear matrix inequalities which can be verified by semidefinite programming relaxations based on the sum of squares technique. Finally, simulation results show the effectiveness of the approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-25T07:22:12Z
      DOI: 10.1177/0142331220957750
       
  • Delay dependent [math] control of wind energy conversion systems via
           singular perturbation theory
    • Authors: Yan Zhang, Zhong Yang, Zhenzhong Yu, Xingliu Hu, Yizhi Wang, Hao Shen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the maximum power point tracking problem of variable-speed wind turbine systems is studied. Both mechanical part and electromagnetic part of the wind energy conversion system are taken into consideration. In view of the different time scales between the mechanical part and electromagnetic part, singular perturbation theory is applied to model the system in order to cope with the stiffness caused by the two-time-scale characteristic. Then, linear parameter varying (LPV) model is developed to approximate the nonlinear singularly perturbed model. In consideration of data detection time of the state variables, in practice, the control inputs are dependent on the states with a small time delay. Therefore, a novel delay dependent [math] controller is designed to make the rotor speed track the reference rotor speed. Furthermore, it is proved that the closed-loop system under control is asymptotically robust stable using Lyapunov theory. In the end, an example simulation verifies the effectiveness and advantages of the developed method by means of comparison with optimal torque control.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-25T07:19:13Z
      DOI: 10.1177/0142331220952302
       
  • [math] control for a class of two-dimensional linear systems with fading
           measurements
    • Authors: Wei Yu, Rui Wang, Xuhui Bu, Jiaqi Liang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the [math] control problem for a class of two-dimensional (2-D) linear discrete-time systems with fading measurements is investigated, where the 2-D systems are described by a Roesser model. The Rice fading model is applied to describe the fading phenomenon and the coefficients of the model satisfy the independent identical Gaussian distributions. The main objective of this paper is to design a controller such that both the 2-D closed-loop system is exponentially mean-square stable and the prescribed [math] performance is guaranteed under the condition of applying the attenuation signals. By utilizing the Lyapunov stability theory and the linear matrix inequalities (LMIs) techniques, sufficient conditions are conducted to guarantee the desired tracking performance. Based on such conditions, the gain matrix of the proposed controller is obtained. Finally, the effectiveness of the proposed control schemes is illustrated with a numerical example and a Darboux equation example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-25T07:16:33Z
      DOI: 10.1177/0142331220944621
       
  • Sliding mode prediction fault-tolerant control method for multi-delay
           uncertain discrete system with sensor fault
    • Authors: Pu Yang, Zhangxi Liu, Dejie Li, Bin Jiang, Jiaqi Zhu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, we design a novel sliding mode prediction fault-tolerant control algorithm for multi-delays discrete uncertain systems with sensor fault. The global sliding surface is designed to replace the traditional linear sliding surface as a predictive model to ensure the global robustness of the system. For sensor fault and sliding mode buffeting, a power-dependent function reference trajectory with fault compensation is designed to attenuate chattering and achieve better stability. In the process of rolling optimization, an improved whale optimization algorithm is developed. On the premise of obtaining good convergence speed and accuracy, the optimization process can avoid falling into the local minimum value and solve the problem of premature convergence. Finally, the comparison experiments on the quad-rotor simulation platform prove the rationality and superiority of the algorithm.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-23T05:30:47Z
      DOI: 10.1177/0142331220953334
       
  • Dynamic positioning for underactuated surface vessel via L1 adaptive
           backstepping control
    • Authors: Huizi Chen, Yan Peng, Dan Zhang, Shaorong Xie, Huaicheng Yan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the problem that fast-transient response and excellent robustness cannot be satisfied simultaneously in the process of dynamic positioning (DP) for underactuated surface vessel (USV) in shallow water. By combing the improved L1 adaptive control with backstepping method, a novel control scheme is designed, which can ensure a fast adaptation with a guaranteed smooth transient response without any overshoot and chattering phenomenon. System uncertainties and disturbances are estimated by the nonlinear observer. Moreover, the optimized extremum seeking control (ESC) is employed to reduce energy consumption under environmental disturbances. Rigorous theoretical analysis shows that all closed-loop signals are bounded-input bounded-state. Simulation and sea test results are presented to illustrate the effectiveness and the robustness of the proposed strategy under the condition of external disturbances and parametric uncertainties.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-22T10:48:36Z
      DOI: 10.1177/0142331220952960
       
  • Nonlinear optimal control for synchronization of distributed hydropower
           generators
    • Authors: Gerasimos Rigatos, Pierluigi Siano, Masoud Abbaszadeh
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Synchronization of distributed hydropower units is necessary for ensuring the quality of the electric power produced by renewable sources. In this article, a nonlinear optimal control approach is proposed for stabilization and synchronization of distributed hydropower generators. The dynamic model of the interacting hydropower generation units undergoes approximate linearization with the use of first-order Taylor series expansion and the computation of the associated Jacobian matrices. The linearization point is updated at each time-step of the control method. For the approximately linearized model of the distributed hydropower system an H-infinity feedback controller is designed. This controller achieves solution of the related optimal control problem under model uncertainty and external perturbations. For the computation of the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control algorithm. The global asymptotic stability properties of the control method are proven through Lyapunov analysis. Finally, to achieve state estimation-based control for the system of the distributed hydropower generators the H-infinity Kalman Filter is used as a robust state estimator.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-17T09:29:03Z
      DOI: 10.1177/0142331220950036
       
  • Chaos synchronization of brushes direct current motors for electric
           vehicle: Adaptive fuzzy immersion and invariance approach
    • Authors: Ardashir Mohammadzadeh, Ali Ahmadian, Ali Elkamel, Falah Alhameli
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel control technique on basis of adaptive immersion and invariance (I&I) theorem and fuzzy systems is proposed to control the brushless direct current motors (BLDCMs) for electric vehicles. The chaotic behaviour of the BDCMs is synchronized with the desired chaotic system. The parameters of the chaotic model are considered to be unknown and are online estimated with tuning rules that are derived through the I&I stability theorem. The effects of the adaptation errors are compensated by the adaptive fuzzy systems. The fuzzy systems are online learned to insure the robustness and stability. The effectiveness and desirable performance of the suggested methodology is verified with both normal simulations and real-time examination. The simulation outcomes of the presented methodology are compared with the some other adaptive methods and it is shown that the presented methodology is more effective.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-16T12:29:50Z
      DOI: 10.1177/0142331220953667
       
  • Adaptive finite-time consensus for multiple mechanical systems with
           unknown backlash nonlinearity and uncertain dynamics
    • Authors: Jiabo Ren, Baofang Wang, Mingjie Cai
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the problem of finite-time consensus (FTC) for uncertain multiple mechanical systems with unknown backlash nonlinearity and external disturbance. Combining finite-time control technique and graph theory, a distributed adaptive FTC protocol is proposed. Radial basis function neural networks are employed to approximate the unknown functions. If the designed parameters of control algorithms and adaptive laws are appropriately chosen, then it can be proved that the position errors between arbitrary two mechanical systems will converge to a small region of zero in finite time as well as the velocity errors. Finally, the effectiveness of the proposed control scheme is verified by numerical simulation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-16T12:27:05Z
      DOI: 10.1177/0142331220952964
       
  • Sliding mode fault-tolerant control for Takagi-Sugeno fuzzy systems with
           local nonlinear models: Application to inverted pendulum and cart system
    • Authors: Riadh Hmidi, Ali Ben Brahim, Slim Dhahri, Fayçal Ben Hmida, Anis Sellami
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes fault-tolerant control design for uncertain nonlinear systems described under Takagi-Sugeno fuzzy systems with local nonlinear models that satisfy the Lipschitz condition. First, by transforming sensor faults as ‘pseudo-actuator’ faults, an adaptive sliding mode observer is designed in order to simultaneously estimate system states, actuator and sensor faults despite the presence of norm-bounded uncertainties. Second, an adaptive sliding mode controller is suggested to provide a solution to stabilize the closed-loop system, even in the event of simultaneous occurrence of faults in actuators and sensors. Next, the main objective of the fault-tolerant control strategy is to compensate for the effects of fault based on the feedback information. Therefore, using the LMI optimization method, sufficient conditions are developed with [math] to calculate the gains of the observer and the controller. Then, particular attention is paid to the simultaneous maximization, by convex multi-objective optimization, of the Lipschitz nonlinear constant in Takagi-Sugeno fuzzy modelling and uncertainties attenuation level. The results of the simulation illustrate the effectiveness of our fault-tolerant control approach using a nonlinear inverted pendulum with a cart system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-16T12:25:13Z
      DOI: 10.1177/0142331220949366
       
  • Event-triggered control of positive Markov jump systems without/with input
           saturation
    • Authors: Xuanjin Deng, Junfeng Zhang, Shuo Li, Shizhou Fu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes an event-triggered control for positive Markov jump systems without/with input saturation. First, an event-triggering condition is established in the form of 1-norm for positive Markov jump systems. Under the event-triggering condition, the term related to error signal between the sample state and the actual state is transformed into a form of interval uncertainty. Then, the positivity and stability of the systems are discussed by using the lower and upper bounds of interval uncertain systems, respectively. An event-triggered control law for the underlying systems is proposed by decomposing controller gain matrix into non-positive and non-negative parts. For positive Markov jump systems with input saturation, a design approach to the controller gain matrices and the corresponding controller auxiliary gain is presented. All conditions are described in terms of linear programming. Furthermore, the obtained approaches are developed for the discrete-time case. Finally, the effectiveness of the proposed design is verified via three examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-16T12:22:40Z
      DOI: 10.1177/0142331220950872
       
  • Algebraic estimator of Parkinson’s tremor frequency from biased and
           noisy sinusoidal signals
    • Authors: Claudia F. Yaşar
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Tremor is an uncontrolled trembling movement or shakes, which are defined as an involuntary, rhythmic oscillatory movement of the body. The dominant features of Parkinsonism are the motor task and its frequency. This paper presents studies on the tremor parameter identification to be used for obtaining the frequency as a dynamical feature of the tremor. The method is based on the analysis of time-varying signals for identification of the tremor’s frequency from unknown noisy harmonic signals with an offset, using time-varying unstable filters and low-pass Butterworth filters. This approach uses an algebraic derivative method, in the frequency domain, to obtain the main frequency of tremors in the time domain. The first frequency mode of the tremor is one of the main characteristics to represent the low vibrational dynamics of Parkinson’s tremor. The proposed frequency estimation is performed in less than a period of the slower component of the measured signal. Real tremor signals were used to experimentally validate the proposed method and the algorithm proved to be fast and robust to high-frequency noises tracking the time variation of the tremor accurately.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-16T06:54:37Z
      DOI: 10.1177/0142331220957231
       
  • Fuzzy logic controller-based boost and buck-boost converter for maximum
           power point tracking in solar system
    • Authors: A Rajavel, N Rathina Prabha
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Due to the concern with energy emergencies, the energy obtained from the sunlight is considered as the most capable conventional resources. Hence, the maximum power point tracking approach is necessary for obtaining the enhanced efficiency from the solar panels. In the case of direct current (DC) application, the output obtained from the photo-voltaic (PV) array cannot be directly connected to the electronic devices. For regulating the output from the PV array, the DC-DC converter is provided in between the load and the array. The converter design plays a significant role to track the maximum power point of the solar panel. This paper describes the design of three converters, namely the boost, buck-boost and buck converter, along with the fuzzy logic controller. It varies the time for switching ON and OFF of the converter concerning changes in the solar panel power. The result of converter power and solar panel for different irradiation is compared for various DC-DC converters. The fuzzy logic controller is employed in the generation of optimal control pulse for the DC-DC converter. Moreover, in the solar photovoltaic system, the steady-state operation is performed and the various solar irradiance results are analyzed. The proposed approach is compared with the various DC-DC converters like buck-boost converter, buck converter and boost converter to prove the efficiency. Then, the performance analysis of the current, voltage and power of PV is analyzed.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T08:58:02Z
      DOI: 10.1177/0142331220938211
       
  • Robust dynamic sliding mode observer design for a class of nonlinear
           systems
    • Authors: Mahnoosh Shajiee, Seyed Kamal Hosseini Sani, Mohammad Bagher Naghibi-Sistani, Saeed Shamaghdari
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel method for the design of robust nonlinear observer in the [math] framework for Lipschitz nonlinear systems is proposed. For this purpose, a new dynamical structure is introduced that ensures the stability of observer error dynamics. Design innovation is the use of dynamic gain in the sliding mode observer. The additional degree of freedom provided by this dynamic formulation is exploited to deal with the nonlinear term. The performance of this stable [math] observer is better than conventional static gain observers and the dynamic Luenberger observer. The compensator is designed in such a way that, while ensuring the stability of the closed-loop system, it prevents performance loss in the presence of the nonlinearities. By the proposed approach, the observer is robust to nonlinear uncertainties because of increasing the Lipschitz constant. Also, the design procedure in the presence of system and measurement noises is addressed. Finally, the simulation of our methodology is conducted on a nonlinear system to illustrate the advantage of this work in comparison with other observers.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T08:55:41Z
      DOI: 10.1177/0142331220952201
       
  • A smooth polynomial shaped command for sloshing suppression of a suspended
           liquid container
    • Authors: Abdullah Alshaya, Dima Almujarrab
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A smooth polynomial shaped command with an adjustable command time length is proposed for eliminating the residual vibrations of a multi-mode system. The ability of eliminating jerks and vibrational modes, regardless of their number, offers the most advantage of the proposed command. A numerical simulation is conducted to test the command’s effectiveness by eliminating the residual sloshing oscillations of a liquid-filled container conveyed by an overhead crane in a rest-to-rest manoeuvre. The governing equations of the liquid free-surface level are derived by modelling the sloshing dynamics by a series of mass–spring–damper harmonics. The proposed model accounts for the coupling between the pendulum dynamics and the sloshing equivalent mechanical model. The command’s robustness to the system parameters’ uncertainties, liquid depth and cable length, are investigated as well. The ability of adjusting the command length and retaining higher sloshing modes in command-designing are also outlined.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T08:49:40Z
      DOI: 10.1177/0142331220949304
       
  • Memory type control charts with inverse-Gaussian response: An application
           to yarn manufacturing industry
    • Authors: Muhammad Amin, Tahir Mahmood, Summera Kinat
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Control charts are commonly applied for monitoring and controlling the performance of the manufacturing process. Usually, control charts are designed based on the main quality characteristics variable. However, there exist numerous other variables which are highly associated with the main variable. Therefore, generalized linear model (GLM)-based control charts were used, which are capable of maintaining the relationship between variables and of monitoring an abrupt change in the process mean. This study is an effort to develop the Phase II GLM-based memory type control charts using the deviance residuals (DR) and Pearson residuals (PR) of inverse Gaussian (IG) regression model. For evaluation, a simulation study is designed, and the performance of the proposed control charts is compared with the counterpart memory less control charts and data-based control charts (excluding the effect of covariate) in terms of the run length properties. Based on the simulation study, it is concluded that the exponential weighted moving average (EWMA) type control charts have better detection ability as compared with Shewhart and cumulative sum (CUSUM) type control charts under the small or/and moderate shift sizes. Moreover, it is shown that utilizing covariate may lead to useful conclusions. Finally, the proposed monitoring methods is implemented on the dataset related to the yarn manufacturing industry to highlight the importance of the proposed control chart.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T04:10:32Z
      DOI: 10.1177/0142331220952965
       
  • Multi-lagged-input information enhancing quantized iterative learning
           control
    • Authors: Huimin Zhang, Ronghu Chi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Quantization is a significant technique in network control to save limited bandwidth. In this work, two new multi-lagged-input-based quantized iterative learning control (MLI-QILC) methods are proposed by using output quantization and error quantization, respectively. The multi-lagged-input iterative dynamic linearization method (MLI-IDL) is introduced to build a linear data model of nonlinear systems using additional control inputs in lagged time instants and multiple parameters where the condition of nonzero input change is not required any longer. The MLI-QILC is proposed by designing two new objective functions utilizing the quantized data of the system outputs and tracking errors, respectively. With rigorous analysis, it is shown that the proposed MLI-QILC with output quantization guarantees that the tracking error converges to a bound which is related to the quantization density and the bound of the desired trajectory. Furthermore, an asymptotic convergence can be achieved for the proposed MLI-QILC method with error quantization. The theoretical results are verified by simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T04:07:32Z
      DOI: 10.1177/0142331220951402
       
  • Delay partitioning approach to the robust stability of discrete-time
           systems with finite wordlength nonlinearities and time-varying delays
    • Authors: Kalpana Singh, V Krishna Rao Kandanvli, Haranath Kar
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is associated with the problem of robust stability of discrete-time systems with time-varying delays and finite wordlength nonlinearities. The main contribution of the paper is two-fold. First, this paper presents a new Lyapunov function based on the idea of partitioning the delay interval into subintervals. The approach may be considered as an advancement over the several existing approaches where only the lower delay bound is partitioned. The second is that reciprocally convex inequality (RCI) and Wirtinger-based inequality (WBI) are used to estimate the sum terms involved in the forward difference of Lyapunov function. The intermediate delay is also included in the Lyapunov function to deal with the delay information more effectively. Finally, several examples are provided to illustrate the less conservatism of the proposed approach as compared to several existing results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T04:05:12Z
      DOI: 10.1177/0142331220947566
       
  • Adaptive friction compensations for mechanical systems with measurement
           delay
    • Authors: Caner Odabaş, Ömer Morgül
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Application performance of mechanical positioning systems might not coincide with the theory, mainly due to nonlinearities or imperfections of system models. Although it is sometimes possible to ignore these mismatches, systems generally suffer from performance degradation or even instability eventually. Especially, friction force and time delay are two major factors of these undesired effects. Hence, in this paper, Smith predictor-based controllers and an adaptive Coulomb friction observer are designed to enhance position tracking performance of a mechanical system including time delay. In fact, implemented hierarchical control scheme provides two-degree of freedom to control both velocity and position separately. The proposed observer structure is mainly motivated by the Friedland-Park observer but could be considered as an extension of it which characterizes a general class of nonlinear functions for friction estimation. To assure its functionality with delayed measurements, different velocity predictor schemes are designed and their performances are compared. As a guideline for observer design, some conditions for exponential stability and robustness analysis are presented. Simulation results demonstrate that the proposed control system enhances the tracking performance even when the actual friction is a compound of various static and dynamic terms.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-11T03:52:11Z
      DOI: 10.1177/0142331220947568
       
  • Multi-dimensional Taylor network-based adaptive control for nonlinear
           systems with unknown parameters
    • Authors: Lei Chu, Yuqun Han, Shanliang Zhu, Mingxin Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an adaptive multi-dimensional Taylor network (MTN) control approach for a class of nonlinear systems with unknown parameters. MTN is employed to identify unknown nonlinear characteristics existing in the system, and then a novel adaptive MTN tracking control method is proposed, via backstepping technique. In the controller design, double adaptive laws are designed and appropriate Lyapunov functions are chosen to overcome the difficulties caused by the unknown parameters. The designed controller can guarantee that all the variables in the closed-loop systems are bounded and the tracking error can be arbitrarily small. Finally, simulation results are presented to verify the effectiveness of the proposed approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-10T10:51:08Z
      DOI: 10.1177/0142331220953355
       
  • New fixed-time sliding mode control for a mismatched second-order system
    • Authors: Guo Jianguo, Yang Shengjiang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A fixed-time sliding mode control (FTSMC) method is proposed for a second-order system with mismatched uncertainties in this paper. A new sliding mode, which is insensitive to the mismatched disturbance, is present to eliminate the effect of mismatched uncertainties by adopting the differentiable nonlinear function, and to obtain the fixed time stability independent of initial conditions by using the fraction-order function. In order to improve the performance of control system, the extended disturbance-observer-based fixed-time sliding mode control (EDO-FTSMC) approach is investigated to obtain the fixed-time stability subject to the mismatched uncertainties. Finally, the performance of the proposed control method is illustrated to compare other control approaches with numerical simulation results and application examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-10T06:24:21Z
      DOI: 10.1177/0142331220952305
       
  • Self-organizing probability neural network-based intelligent non-intrusive
           load monitoring with applications to low-cost residential measuring
           devices
    • Authors: Zejian Zhou, Yingmeng Xiang, Hao Xu, Yishen Wang, Di Shi, Zhiwei Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Non-intrusive load monitoring (NILM) is a critical technique for advanced smart grid management due to the convenience of monitoring and analysing individual appliances’ power consumption in a non-intrusive fashion. Inspired by emerging machine learning technologies, many recent non-intrusive load monitoring studies have adopted artificial neural networks (ANN) to disaggregate appliances’ power from the non-intrusive sensors’ measurements. However, back-propagation ANNs have a very limit ability to disaggregate appliances caused by the great training time and uncertainty of convergence, which are critical flaws for low-cost devices. In this paper, a novel self-organizing probabilistic neural network (SPNN)-based non-intrusive load monitoring algorithm has been developed specifically for low-cost residential measuring devices. The proposed SPNN has been designed to estimate the probability density function classifying the different types of appliances. Compared to back-propagation ANNs, the SPNN requires less iterative synaptic weights update and provides guaranteed convergence. Meanwhile, the novel SPNN has less space complexity when compared with conventional PNNs by the self-organizing mechanism which automatically edits the neuron numbers. These advantages make the algorithm especially favourable to low-cost residential NILM devices. The effectiveness of the proposed algorithm is demonstrated through numerical simulation by using the public REDD dataset. Performance comparisons with well-known benchmark algorithms have also been provided in the experiment section.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-04T07:41:12Z
      DOI: 10.1177/0142331220950865
       
  • Synchronization of chaotic Lur’e systems with time-delays via quantized
           output feedback control
    • Authors: Yu Rao, Dongbing Tong, Qiaoyu Chen, Wuneng Zhou, Yuhua Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the asymptotic stability for chaotic Lur’e systems (CLSs) is studied. A new control method, which involves both state quantizer and control quantizer, is presented. In addition, dynamic parameters of quantizers and controller are designed synchronously to ensure the asymptotic synchronization of the master–slave systems. Moreover, by solving linear matrix inequalities, the corresponding dynamic parameters and control gain can be given. Finally, one numerical simulation and two practical simulations are raised to prove the effectiveness of the control strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-04T07:39:11Z
      DOI: 10.1177/0142331220950864
       
  • Adaptive quasi-Monte Carlo method for uncertainty evaluation in centroid
           measurement of planetary rovers
    • Authors: Qiang Na, Shurong Hu, Jianguo Tao, Yang Luo
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The measurement of the centroid is of great significance to improve the control performance and reduce the energy consumption of the planetary rover (PR). The uncertainty is an essential indicator of the reliability of centroid measurement results. The purpose of the current study is to evaluate the uncertainty of centroid measurement in the multi-configuration rover. For the measurement of the centroid, the model with 37 parameters of two measurements as the input and the centroid coordinates as the output is derived. Further, the mechanical and electrical integrated system is developed, which can measure the centroid of PRs in different configurations and sizes. Moreover, to overcome the shortcomings of the Monte Carlo method (MCM) in uncertainty evaluation, an adaptive algorithm that automatically determines the number of input sequences is proposed. On this basis, an adaptive quasi-Monte Carlo method (AQMCM) is presented in order to accelerate the uncertainty evaluation, which is characterized by the randomized Sobol sequence. Besides, experiments are performed to compare the uncertainty evaluation process and results of the AQMCM and the adaptive Monte Carlo method (AMCM) in multiple configurations. The result shows that the standard uncertainty of the AQMCM is almost the same as that of the AMCM, but the sequence size of AQMCM is evidently smaller than that of AMCM. Taken together, we identify that the AQMCM evaluates the uncertainty of CM for the multi-configuration rover in an efficient and fast way. Furthermore, the AQMCM provides a new method for uncertainty evaluation, particularly for nonlinear models in different states.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-03T05:22:38Z
      DOI: 10.1177/0142331220950038
       
  • Parametric control to permanent magnet synchronous motor via proportional
           plus integral feedback
    • Authors: Da-Ke Gu, Da-Wei Zhang, Quan-Zhi Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study investigates a parametric approach to design the proportional-integral (PI) controller for a permanent magnet synchronous motor (PMSM). Based on the solutions of the generalized Sylvester equation, the generally parametric expressions of PI controller and right eigenvector matrix are obtained. By using the parametric approach, the closed-loop system is converted into a linear time-invariant system with an expected eigenstructure. Further, a numerical example is put forward to illustrate the effectiveness and feasibility of the proposed parametric approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-02T12:36:00Z
      DOI: 10.1177/0142331220944898
       
  • Linear active disturbance rejection control for hysteresis compensation
           based on backpropagation neural networks adaptive control
    • Authors: Wentao Liu, Tong Zhao, Zhongwang Wu, Wei Huang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a compound control framework for non-affine nonlinear systems facing hysteresis disturbance. The controller consists of linear active disturbance rejection control (LADRC) and backpropagation (BP) neural networks adaptive control. BP neural networks are utilized to arbitrarily approximate the uncertainty nonlinear caused by the deviation of control parameter from its nominal value and LADRC is designed to real-time estimate and compensate the disturbance with vast matched and mismatched uncertainties including unknown internal system dynamic uncertainty and external hysteresis disturbance therein. Combining the adaptive neural networks design with LADRC design techniques, a new dual-channel composite controller scheme is developed herein whereby adaptive neural networks are used as feed-forward inverse control and LADRC as closed-loop feedback control. Furthermore, as compared with a traditional control algorithm, the proposed BP-LADRC dual-channel composite controller can guarantee that the desired signal can be tracked with a small domain of the origin and it is confirmed to be effective under Lyapunov stability theory and MATLAB simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-31T08:49:48Z
      DOI: 10.1177/0142331220934948
       
  • Model predictive control-based control strategy to reduce driving-mode
           switching times for parallel hybrid electric vehicle
    • Authors: Jiangtao Fu, Zhumu Fu, Shuzhong Song
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Multi-power sources are included in hybrid electrical vehicles, which leads to multi-driving modes co-existing when driving the vehicle. However, the frequent driving mode switching (DMS) will probably need the engine to be started frequently, which can result in extra fuel consumption. So, avoiding unnecessary DMS should be fully considered when designing the control strategy. For solving this problem, a model predictive control (MPC) strategy integrating Markov chain driving intention identification is put forward. First, the component models of the powertrain system are established. Second, according to the real driving cycle data, a driving intention model based on the Markov chain is designed according to the real driving cycle data. Then the MPC-based control strategy aiming at reducing DMS times is proposed by integrating the cost of DMS. Finally, the proposed control strategy is contrasted with three other control strategies to verify its validity in reducing the mode switching times and improving the fuel economy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-31T07:49:23Z
      DOI: 10.1177/0142331220949711
       
  • Fast moving and deformational target tracking approach based on
           heterogeneous features fusion
    • Authors: Bo Li, Qingyang Jing
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Aiming at the unstable performance on fast-moving and deformational target tracking in current kernel correlation filter (KCF), an innovative approach based on heterogeneous features fusion is proposed in this paper. Firstly, a histogram of oriented gradient is utilized to cater for motion state change in complex surveillance background. Combined with a colour-free template as a novel heterogeneous feature, the proposed approach improves the tracking performance on the fast-moving target in KCF. Subsequently, the optimized spatial regularization and quadruple block method are implemented in order to solve the difficulties of scale change and boundary effect in the cyclic matrix. The simulation results indicate that the proposed approach has better precision and success rate than other popular tracking algorithms when dealing with both fast motion and deformation on the platform of the object tracking benchmark and actual traffic datasets.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-27T09:03:26Z
      DOI: 10.1177/0142331220949303
       
  • Variable gain control-based acceleration slip regulation control algorithm
           for four-wheel independent drive electric vehicle
    • Authors: Luole Guo, Hongbing Xu, Jianxiao Zou, Hongyu Jie, Gang Zheng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to improve the dynamic performance and stability of general acceleration slip regulation (ASR) control technology for four-wheel independent drive electric vehicle (4WID EV), an ASR control strategy based on variable gain controller (VGC) is proposed in this paper. First of all, a road identification strategy is designed to identify the current road surface and calculate the optimal slip ratio of the road. Then, the optimal slip ratio is taken as the control target, and the ASR control strategy based on VGC is designed to keeps slip ratio around the optimum slip ratio through controlling the driving torque output, so wheels can make the best of road adhesion to prevent vehicle from slipping. Meanwhile, we analyze the control system state space, and build a scalar function of the system, and prove that the system satisfies Lyapunov large scale asymptotic stability theorem, so the parameters of the VGC does not affect the system stability. Then, in order to meet the requirement of quick dynamic response and no overshoot, parameters selection of VGC is deduced by mathematics. Finally, the co-simulation of Matlab/Simulink and Carsim results show that the proposed control strategy is with the better dynamics and stability, and can better prevent wheel slipping on various roads.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-26T07:16:28Z
      DOI: 10.1177/0142331220933423
       
  • Iterative method to the coupled operator matrix equations with sub-matrix
           constraint and its application in control
    • Authors: Caiqin Song
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A finite iterative algorithm is presented for solving the numerical solutions to the coupled operator matrix equations in Zhang (2017b). In this paper, a new finite iterative algorithm is presented for solving the constraint solutions to the coupled operator matrix equations [math], where the constraint solutions include symmetric solutions, bisymmetric solutions and reflexive solutions as special cases. If this system is consistent, for any initial constraint matrices, the exact constraint solutions can be obtained by the introduced algorithm within finite iterative steps in the absence of the roundoff errors. Also, if this system is not consistent, the least-norm constraint solutions can be obtained within the finite iteration steps in the absence of the roundoff errors. Furthermore, if a group of suitable matrices are given, the optimal approximation solutions can be derived. Finally, several numerical examples are given to show the effectiveness of the presented iterative algorithm.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-25T11:52:59Z
      DOI: 10.1177/0142331220947560
       
  • Finite-time dissipative control for networked control systems with
           hybrid-triggered scheme
    • Authors: Qian Zhang, Huaicheng Yan, Shiming Chen, Xisheng Zhan, Xiaowei Jiang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the problem of finite-time dissipative control for networked control systems by hybrid triggered scheme. In order to save network resources, a hybrid triggered scheme is proposed, which consists of time-triggered scheme and event-triggered scheme simultaneously. Firstly, sufficient conditions are derived to guarantee that the closed-loop system is finite-time bounded (FTBD) and [math] dissipative. Secondly, the corresponding controller design approach is presented based on the derived conditions. Finally, a numerical example is presented to show the effectiveness of the proposed approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-25T11:52:51Z
      DOI: 10.1177/0142331220946509
       
  • Multi-objective integrated scheduling optimization of semi-combined marine
           crankshaft structure production workshop for green manufacturing
    • Authors: Haochen Li, Jianguo Duan, Qinglei Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to realize green manufacturing in the production process of semi-combined marine crankshaft structural parts, good job scheduling and reasonable workshop layout are the key. In traditional method, flexible job shop scheduling problem (FJSP) and the multi-row workshop layout problem (MRWLP) are regarded as separate tasks. However, the separate optimization method ignores the interaction between FJSP and MRWLP. Because the process sequencing of FJSP affects the layout results of processing machines, while the layout scheme of MRWLP affects the scheduling completion time through the transportation between processes. Therefore, it is very important to establish an integrated mathematical model for optimization of both layout and scheduling simultaneously to explore the common influence of the two resource constraints on scheduling results. At the same time, the transportation task is also a manufacturing process that cannot be ignored, which affects the completion time and energy consumption of the workshop, especially the heavy industrial manufacturing workshop with crane as transportation equipment. According to the established model, a five-segment coding including transportation information, layout information and processing information is designed, and two heuristic selection strategies are integrated into non-dominated sorting genetic algorithm II (NSGA-II) to optimize the iterative results twice. Finally, the effectiveness of the integrated mathematical model is verified by an example, which provides guidance for green manufacturing in the shipbuilding industry.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-19T05:27:03Z
      DOI: 10.1177/0142331220945917
       
  • The proportional-integral controller design based on a Smith-like
           predictor for a class of high order systems
    • Authors: Zhenlong Wu, Jie Yuan, Donghai Li, Yali Xue, YangQuan Chen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Heat transfer and fluid flow play important roles in industrial processes, especially in chemical and thermal processes. Their dynamics are often modelled as high order systems with the type of [math], which have slow responses to the set point and the input disturbance. To enhance the tracking and disturbance rejection performance of these systems, a control structure combining the proportional-integral (PI) controller and Smith-like predictor is proposed in this paper. The tracking and disturbance rejection performance of the proposed control structure with the order mismatch are analyzed. In addition, the precondition where the proposed control structure can obtain satisfactory disturbance rejection performance is deduced. By analyzing the influence of PI parameters on control performance, an empirical tuning rule, which can balance the control performance and robustness constraint well, is summarized and the corresponding tuning toolbox is developed. Finally, the superiority of the proposed control structure is verified by simulations and comparative experiments based on Peltier temperature control platform.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-10T08:54:46Z
      DOI: 10.1177/0142331220944627
       
  • An efficient grasshopper optimization with recurrent neural network
           controller-based induction motor to replace flywheel of the process
           machine
    • Authors: Vasant M Jape, Hiralal M Suryawanshi, Jayant P Modak
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a convenient power electronic circuitry with a control approach for the flywheel replacement of an induction motor. The proposed control approach is the joined execution of grasshopper optimization algorithm and recurrent neural network based on duty ratio controller and hence the proposed work is named grasshopper optimization with recurrent neural network. The main contribution of this work is, the power electronic circuitry gets the input voltage samples and limits the deviation to appraise the instantaneous torque demand. The required voltage for the instantaneous torque demand is produced by the proposed control technique. In the proposed grasshopper optimization with recurrent neural network technique, the grasshopper optimization algorithm is a meta-heuristic population-based algorithm, which works from the perspective of the swarming behavior of grasshoppers in nature. In the proposed system, the recurrent neural network learning procedure is improved by the grasshopper optimization algorithm in the perspective of the minimum error objective function. the proposed grasshopper optimization with recurrent neural network technique optimizes the inverter switching states by limiting the error between the setpoint torque and the demand torque regarding objective function. With this proposed technique, the unbalance between demand torque and generated torque is found with high precision and the quicker execution to pull back out the torsional pulsation insensitive load linked transmission systems. By utilizing the proposed methodology, the extreme fluctuation of load torque due to peaky loads in an induction motor will be detected accurately. Also, the proposed technique reduces the torsional vibrations, weakness in components and minimizes the outages of uninterrupted production leading to higher profits. The proposed strategy is actualized in the MATLAB/Simulink platform and evaluated their performance. The performances are appeared differently compared with the existing methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-10T08:37:58Z
      DOI: 10.1177/0142331220938205
       
  • Combination of predictive models with an optimal adaptive fuzzy controller
           for active suspension systems having control force constraints on front
           and rear tires
    • Authors: Mohammad Javad Mahmoodabadi, Mohammad Javanbakht
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents optimal adaptive fuzzy approaches combined by the predictive models for five degrees of freedom vehicle systems having a control force constraint of 1000 N on both front and rear suspensions in order to minimize the road disturbances. First, two separate adaptive fuzzy controllers are designed for the rear and front tires using the singleton fuzzifier, center average defuzzifier and product inference engine. The constructed fuzzy systems implement the adaptation laws based on the Lyapunov theory to guarantee the stability of the system. Afterward, a gravitational search optimization algorithm is applied to calculate the optimal values of the controller’s gains. The weighted summation of four objectives, as the relative displacement between the sprung mass and the front tire, the relative displacement between the sprung mass and the rear tire, the acceleration of the body and the acceleration of the seats, are regarded in the optimization process. Two different predictive models are employed to find the optimal design variables for the circumstances where the stability of the system is under variation. The first model is a fuzzy predictive system while the second one is based on the moving least squares interpolation. Eventually, the resultant online models are compared with the offline systems when the vehicle mass varies. These simulations obviously illustrate the efficiency and ability of the suggested strategy to remove the effect of the road disturbances on the ride comfort.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-07T09:31:51Z
      DOI: 10.1177/0142331220944360
       
  • Functional interval observer design for singular fractional-order systems
           with disturbances
    • Authors: Dinh Cong Huong, Dao Thi Hai Yen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, we consider the problem of designing functional interval observers for a class of singular fractional-order systems. The goal of this work is to design not a full state interval observer for singular fractional-order systems, but to design an observer for state functions of this kind of systems. Conditions for the existence of such functional interval observers are given and an effective algorithm for computing unknown observer matrices is provided in this study. Two numerical examples and simulation results are provided to illustrate the effectiveness of the proposed design method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-06T09:28:21Z
      DOI: 10.1177/0142331220944897
       
  • Higher-order cluster consensus of a multi-agent network with
           continuous-time dynamics
    • Authors: Ümit Develer, Mehmet Akar
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the higher-order cluster agreement problem for continuous-time networks evolving over any given directed graph. Necessary and sufficient conditions are derived to reach clusters that are not pre-determined as opposed to existing literature. The analysis shows that appropriate stabilizing choices of coupling strengths do not affect the number of clusters and the final values of the clusters. The results are verified by numerical examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-04T04:11:27Z
      DOI: 10.1177/0142331220940229
       
  • Fixed-order data-driven [math] controller synthesis for flexible
           mechanical systems: Two-stage approach
    • Authors: Ayhan Arda Araz, S. Çağlar Başlamışlı, Uğur Mertcan Özmarangoz
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a two-stage method is introduced to design fixed-order data-driven [math] controller for flexible mechanical systems. In the first stage of the proposed method, unknown parameters of anti-resonance filter that is added to the forward path of the control loop of the system to minimize resonant peaks, are calculated using frequency domain data obtained from open-loop system identification tests. In the second stage, a fixed-order data-driven [math] controller is calculated by solving an optimization problem under convex [math] constraints obtained based on the Nyquist diagram. With the proposed method, lower order controllers that meets the performance constraints of classical model-based [math] problems can be synthesized without need of a parametric plant model. The method developed in this study is tested experimentally on a military stabilized platform and its performance is compared with a model-based [math] controller design method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-04T04:10:57Z
      DOI: 10.1177/0142331220940934
       
  • Iterative learning control for nonlinear heterogeneous multi-agent systems
           with multiple leaders
    • Authors: Qin Fu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article investigates the iterative learning control problem for a class of nonlinear heterogeneous multi-agent systems. The main contribution of this article is to apply iterative learning control algorithm to the multi-agent systems with multiple leaders, and solve the containment control problem of multi-agent systems in the sense of iterative learning control stability. Based on the framework of communication topologies, distributed iterative learning controllers are designed. And when the iterative learning control laws are applied to the systems, the containment errors between the followers’ states and the convex hull spanned by the leaders’ states over a finite-time interval are bounded, and furthermore, the containment errors can converge to zero as the iteration index approaches to infinity in the absence of initial errors. A simulation example is finally constructed to verify the effectiveness of the theoretical method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-30T11:20:03Z
      DOI: 10.1177/0142331220941636
       
  • Finite-time integrated guidance and control system for hypersonic vehicles
    • Authors: Chong Zhenyu, Guo Jianguo, Zhao Bin, Guo Zongyi, Lu Xiaodong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A finite-time integrated guidance and control (IGC) method is proposed in this study for hypersonic vehicles. The IGC dynamic model is initially built by combining the 3D relative kinematics and dynamics equations. Then, by introducing the adaptive control technology and the backstepping approach, an IGC scheme with adaptive parameters is presented to guarantee the finite-time stability of a closed-loop control system on the basis of Lyapunov stability theory. Nonlinear simulation results demonstrate the effectiveness and robustness of the proposed IGC method for hypersonic vehicles compared with other robust IGC methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-27T11:54:05Z
      DOI: 10.1177/0142331220941934
       
  • A sensorless angular displacement measurement method for rotational
           oscillation generation in biomedical applications with Ros-Drill©
    • Authors: Handan Nak, Ali Fuat Ergenc
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a novel measurement method for angular displacement of an oscillation-assisted micro drill device, Ros-Drill©. The device is driven with a brushless dc motor (BLDC) which is desired to track a sinusoidal position reference. The measurement method is based on the principle of monitoring the back-emf voltage that is induced on the non-fed winding of the brushless motor. It offers sensorless analog measurement of the angular displacement of the oscillatory motion which is not possible with optical encoders. The measurement methodology and control algorithms are implemented utilizing a digital signal processor. Experiments reveal that the method is feasible for measuring angular displacements of rotational oscillations during cellular piercing operations. Furthermore, it presents fair performance for frequencies up to 1000 Hz and provides early diagnosis for a potential malfunction of the micro drill.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-27T10:53:40Z
      DOI: 10.1177/0142331220940226
       
  • Towards collaborative drilling with a cobot using admittance controller
    • Authors: Yusuf Aydin, Doganay Sirintuna, Cagatay Basdogan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In the near future, collaborative robots (cobots) are expected to play a vital role in the manufacturing and automation sectors. It is predicted that workers will work side by side in collaboration with cobots to surpass fully automated factories. In this regard, physical human-robot interaction (pHRI) aims to develop natural communication between the partners to bring speed, flexibility, and ergonomics to the execution of complex manufacturing tasks. One challenge in pHRI is to design an optimal interaction controller to balance the limitations introduced by the contradicting nature of transparency and stability requirements. In this paper, a general methodology to design an admittance controller for a pHRI system is developed by considering the stability and transparency objectives. In our approach, collaborative robot constrains the movement of human operator to help with a pHRI task while an augmented reality (AR) interface informs the operator about its phases. To this end, dynamical characterization of the collaborative robot (LBR IIWA 7 R800, KUKA Inc.) is presented first. Then, the stability and transparency analyses for our pHRI task involving collaborative drilling with this robot are reported. A range of allowable parameters for the admittance controller is determined by superimposing the stability and transparency graphs. Finally, three different sets of parameters are selected from the allowable range and the effect of admittance controllers utilizing these parameter sets on the task performance is investigated.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-27T05:14:27Z
      DOI: 10.1177/0142331220934643
       
  • Controller design for systems subject to multi-layer nested saturation via
           event-triggered scheme
    • Authors: Yuan Zhou, Hongchao Li, Jiao Liu, Dedong Yang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The design of an event-triggered controller to stabilize the continuous-time systems subject to multi-layer nested saturation is presented in this paper. As a complex nonlinearity, the nested saturation exists in a large number of systems, which may degrade the performance of the system. The sufficient condition for stabilization of the multi-layer saturated system is given by employing event-triggered control, which could reduce communication load of the system. The lower bound of the inter-event time interval is calculated to avoid the Zeno behavior. The domain of attraction for the system is estimated, which is determined by solving an optimization problem. The main advantage of the proposed approach lies in the extensive applicability for different layers of the nested saturation. In the final section, simulation and pratical examples are given to demonstrated the effectiveness of the proposed results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-21T11:58:25Z
      DOI: 10.1177/0142331220940484
       
  • Asymmetric indirect-driven self-sensing actuation and its application to
           piezoelectric systems
    • Authors: Bin Hu, Chee Khiang Pang, Jie Wan, Shuyu Cao, Jern Khang Tan, Hui Li, Jianyi Wang, Guoxiao Guo
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Self-sensing actuators use a single piezoelectric element as actuators and sensors simultaneously. This paper proposes the asymmetric indirect-driven self-sensing actuation (AIDSSA) circuit to realize the concept of self-sensing in piezoelectric-actuated systems. Unlike traditional circuits relying on differential amplifiers, the AIDSSA circuit is constructed with only op-amps and uses negative feedback to reject the common-mode interferences from the control command. The new circuit requires simpler conditions of component matching and is able to sense the mechanical responses with a uniform gain and without a phase lag. The actuator is able to achieve full-stroke actuation while sensing is performed, because AIDSSA introduces no undesirable dynamics into the control loop. For the first time, the sensing and actuation transfer functions in self-sensing actuators have become fully decoupled at all frequencies. The investigation takes the form of an industrial application of hard disk drives, and demonstrates the usefulness the circuit in complex positioning systems. Experimental results show that the position error variance, a measure of disturbance rejection capability, has been improved by about 15% in the track-following mode relative to the same servo before modifications.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-21T07:07:48Z
      DOI: 10.1177/0142331220938208
       
  • Nonlinear Granger causality graph method for data-driven target attack in
           power cyber-physical systems
    • Authors: Qinxue Li, Bugong Xu, Shanbin Li, Yonggui Liu, Xuhuan Xie
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Owing to the deep integration of the information and communication technologies, power cyber-physical systems (CPSs) have become smart but are vulnerable to cyber attacks. To correctly assess the vulnerability of power CPSs and further study feasible countermeasures, we verify that a data-driven target attack on a nonlinear Granger causality graph (NGCG) can be constructed successfully, even if adversaries cannot acquire the configuration information of the systems. A NGCG is a unified framework for the processing and analysis of nonlinear measurement data or datasets and can be used to evaluate the significance of power nodes or lines. In addition, an algorithm including data-driven parameter estimation, noise removal and data reconstruction based on symplectic geometry is introduced to make the NGCG a parameter-free and noise-tolerant method. In particular, three new indexes on the weight analysis of the NGCG are defined to quantitatively evaluate the significance of power nodes or lines. Finally, several case studies of a nonlinear simulation model and power systems in detail verify the effectiveness and superiority of the proposed data-driven target attack. The results show the proposed target attack can select the key attack targets more accurately and lead to physical system collapse with the least number of attack steps.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-21T07:03:23Z
      DOI: 10.1177/0142331220938200
       
  • Explicit nonlinear predictive control algorithms for Laguerre filter and
           sparse least square support vector machine-based Wiener model
    • Authors: Divyesh Raninga, Radhakrishnan TK, Kirubakaran Velswamy
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, three computationally proficient model predictive control (MPC) algorithms for least square support vector machine (LSSVM)-based Wiener model are described. A Wiener model with Laguerre filter as dynamic linear part and LSSVM approximator as nonlinear static part is considered. Even though having excellent approximation abilities, LSSVM suffers from lack of sparseness. A pruning algorithm for LSSVM model is proposed and its comparison is made with classical pruning algorithm. The proposed pruning algorithm is able to remove 99% of support vectors with no remarkable drop in modelling accuracy. Using pruned Wiener model, three computationally efficient MPC algorithms are described. In the first algorithm, linearization of Wiener model is performed at every sampling interval and therefore control vector is determined by carrying out a quadratic optimization task. In the second algorithm, control signal is determined by an explicit control law and parameters of this control law are computed by performing lower-upper (LU) factorization of a matrix and solving linear equations without any online optimization. In the third algorithm, the parameters of explicit control law are calculated directly by another LSSVM approximator, which is trained offline. The advantages and effectiveness of proposed methods are demonstrated on the benchmark pH neutralization reactor. The control performance and computational efficiency of proposed algorithms are compared with computationally complex nonlinear MPC, which repeats a nonlinear optimization task at every sampling interval. The impact of pruning on model accuracy, computational efficiency and control accuracy is also discussed.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-21T04:28:18Z
      DOI: 10.1177/0142331220938532
       
  • Combined effect of autocorrelation and measurement errors on the adaptive
           [math] monitoring schemes
    • Authors: Sandile Charles Shongwe, Jean-Claude Malela-Majika
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      For independent and identically distributed observations, and those with measurement errors only, the adaptive designs (i.e. variable sampling sizes (VSS), variable sampling intervals (VSI) and the latter two combined to form VSSI) have been thoroughly discussed. However, no research exists for processes under the combined effect of autocorrelation and measurement errors; thus, such adaptive Shewhart [math] schemes are proposed. The Markov chain approach for adaptive designs are used to evaluate the run-length distribution properties with two special sampling strategies (i.e. s-skip and multiple measurements) incorporated to reduce the combined negative effect of autocorrelation and measurement inaccuracy. Using numerous run-length metrics, it is shown that the combination of the two sampling strategies with the VSSI design reduces this negative effect considerably and improves the detection ability of the [math] scheme by a significant margin as compared with using the fixed sample size and sampling interval (FSSI), VSS and VSI designs. Autocorrelation level has a higher negative effect as compared with the measurement inaccuracy level. For high levels of autocorrelation ([math]0.8), the s-skip strategy has little influence in reducing the negative effect; but the VSSI design maintains better performance than the other designs. Finally, a real-life example is used to illustrate its implementation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-20T07:25:21Z
      DOI: 10.1177/0142331220935293
       
  • Harmonics mitigation in hybrid shunt active power filter connected
           renewable energy source using an intelligent controller
    • Authors: Ganesan Arunsankar, Subbaraman Srinath
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes an intelligent technique-based optimal controller for harmonics mitigation to maintain the power quality in renewable energy source (RES)-based distribution systems. The proposed intelligent technique is the joint execution of both the fractional-order proportional integral controller and moth-flame optimization with random decision forest. In the proposed approach, moth-flame optimization optimizes the dataset of fundamental and harmonic loop parameters such as terminal voltage and direct current voltage present in the hybrid shunt active power filter.The dataset is generated based on the linear and nonlinear load variation and parameter variation of the renewable energy sources, subject to the minimum error objective function. Based on the accomplished dataset, random decision forest accurately predicts the parameters and produces optimized control signals. The proposed technique guarantees the system with less complexity for the harmonics mitigation of the power quality event and hence the accuracy of the system is raised. Then, the proposed model is executed in the Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. The simulation analysis of the proposed approach is tested using the six test cases with various combinations of nonlinear loads. In all the test cases, the performance of various system parameters, such as source current with and without filter, source voltage, hybrid shunt active power filter current, load current and voltage, is analysed. Furthermore, the total harmonic distortion at different load ratings is also examined.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-14T10:58:06Z
      DOI: 10.1177/0142331220932642
       
  • Extended conjugate gradient squared and conjugate residual squared methods
           for solving the generalized coupled Sylvester tensor equations
    • Authors: Eisa Khosravi Dehdezi, Saeed Karimi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, two attractive iterative methods – conjugate gradient squared (CGS) and conjugate residual squared (CRS) – are extended to solve the generalized coupled Sylvester tensor equations [math]. The proposed methods use tensor computations with no maricizations involved. Also, some properties of the new methods are presented. Finally, several numerical examples are given to compare the efficiency and performance of the proposed methods with some existing algorithms.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-14T09:31:25Z
      DOI: 10.1177/0142331220932385
       
  • Measurement of roughness on hardened D-3 steel and wear of coated tool
           inserts
    • Authors: A Bovas Herbert Bejaxhin, G Paulraj, G Jayaprakash, V Vijayan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This research investigation has been carried out in Computer Numerical Control (CNC) turning of 40–50 Hardness Rockwell C (HRC) hardened high chromium high carbon steel (HCHCR-D3) specimen for the findings of surface roughness (Ra) and the tool wear. The HCHCR-D3 steel, which has excellent abrasion and wear resistance, is machined with the physical vapor deposition (PVD) coated carbide (CNMG) turning insert nomenclature based on shape, clearance angle, tolerance and type of tool inserts. The coatings preferred are Titanium Nitrate (TiN), Aluminium Chromium Nitrate (AlCrN) and Latuma for the coating thickness of 3–4μm. The varying input parameters of speed and depth of cut under constant feed rate are used as machining parameters for this CNC turning operation. The machined surface characterization and tool wear have been investigated analytically in this manuscript along with the predicted results of effective stresses and temperatures under dynamic cutting conditions in Deform 3D can be related. The outcomes indicate that the depth of cut and the hardening effect (HRC) are the major influencing parameter on surface roughness. Less tool wear and machining time are obtained by the usage of coated CNMG tool insert for high-speed cutting conditions which results in minimization of wear interruption and growth in surface improvements.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-14T09:25:44Z
      DOI: 10.1177/0142331220938554
       
  • On wavelet-based statistical process monitoring
    • Authors: Achraf Cohen, Mohamed Amine Atoui
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an overview of wavelet-based techniques for statistical process monitoring. The use of wavelet has already had an effective contribution to many applications. The increase of data availability has led to the use of wavelet analysis as a tool to reduce, denoise, and process the data before using statistical models for monitoring. The most recent review paper on wavelet-based methods for process monitoring had the goal to review the findings up to 2004. In this paper, we provide a recent reference for researchers and engineers with a different focus. We focus on: (i) wavelet statistical properties, (ii) control charts based on wavelet coefficients, and (iii) wavelet-based process monitoring methods within a machine learning framework. It is clear from the literature that wavelets are widely used with multivariate methods compared to univariate methods. We also found some potential research areas regarding the use of wavelet in image process monitoring and designing control charts based on wavelet statistics, and listed them in the paper.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-14T05:54:21Z
      DOI: 10.1177/0142331220935708
       
  • Integration of affine ICP into the precise localization problem of
           smart-AGVs: Procedures, enhancements and challenges
    • Authors: Abdurrahman Yilmaz, Hakan Temeltas
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The localization problem in robotics has been widely studied both for indoor and outdoor applications, but is still open for improvements. In indoor environments, GPS-based methods are not preferred due to reflections, and the pose of the robot is determined according to the measurements taken around with its sensors. One of them is iterative closest point (ICP)-based localization method. ICP is a point set registration method, the essence of which is to iteratively compute the transformation between two point sets. However, it is also utilized to solve the localization problem thanks to its high precision in registration. Precise localization is important for applications that require highly accurate pose estimation, such as for smart-AGVs to be used in smart factories to reach a station at industrial standards. Traditional ICP finds transformation in terms of a rotation and translation, and thus can be directly applied to the localization problem. On the other hand, the affine variant of ICP is not adapted to solve the localization problem. In this study, the necessary arrangements to make affine ICP suitable for precise localization are given as a procedure such that the transformation between point sets is found by affine ICP, the resulting transformation is projected to rotation plane by polar decomposition and then the pose is estimated. The enhancements achieved with the usage of affine ICP in precise localization problems are demonstrated in simulation by comparing localization performance of affine ICP with that of traditional ICP. For this purpose, in a factory environment, a scenario where a smart-AGV approaching the target autonomously to carry out an operation has been prepared. The performances of the algorithms have been evaluated for five different docking stations with 30 separate experiments. Moreover, the challenges related to the affine ICP-based fine localization, in particular about finding projection of affine transformation to rotation plane, are highlighted in this study.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-13T09:08:22Z
      DOI: 10.1177/0142331220933430
       
  • Operation characteristics and methods of the hydraulic power take-off
           system
    • Authors: Qijuan Chen, Donglin Yan, Yang Zheng, Xuhui Yue, Dazhou Geng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The power take-off system plays a vital role in the wave energy generating unit. Here, for studying the operation characteristics and methods of the hydraulic power take-off system, its basic model is built relying on the operating principles of every component. Meanwhile, a proportional–integral–derivative (PID) controller is also designed to regulate the rotational speed of the motor. Then, a test platform for the hydraulic power take-off system is constructed to verify the correctness of the model. Fortunately, based on model analyses, some useful results are found. Firstly, the PID controller has a visible effect on stabilizing the rotational speed. In addition, a group of optimal control parameters are obtained. Secondly, the influences of the displaced volume on the operation characteristics of the hydraulic power take-off system are found. Meanwhile, the optimal displaced volume is also presented by weighing the efficiency and stability. Finally, the operation modes and regions of the hydraulic power take-off system are obtained, and its rationality is also proved by a simulated running of the system. More importantly, these results can provide a reference to the design and operation of the hydraulic power take-off system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-10T10:43:16Z
      DOI: 10.1177/0142331220934352
       
  • An incentive mechanism-based negotiation model for green supply chain
           networks
    • Authors: Fang Yu, Chun Zhang, Yongsheng Yang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This research aims to prompt agents to improve their strategies initiatively in order to decrease carbon dioxide emissions and enhance green factors during production and consumption processes. An incentive negotiation mechanism is proposed for agents in supply chains to improve their strategies. Multiple items, multiple attributes, and multiple echelons are involved in the proposed model. In addition, this research takes both the commerce and the environmental attributes into account. The environmental attributes were transformed into rewards or penalty by setting reward factors or penalty factors, and were taken into account during the calculation of the profits. The simulation results show that the proposed model was feasible to solve the complex negotiation problems, and had a good performance. The green factors of agents in the green supply chain network are increased when the agents have low initial green factors. Moreover, the proposed model can effectively reduce the carbon dioxide emissions as well. The proposed model can be seen as a “win–win” solution from the perspective of both business and environmental protection. The total profit of the green supply chain network is improved, and the harm to the environment is decreased as well.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-10T10:42:16Z
      DOI: 10.1177/0142331220929814
       
  • Maximum likelihood-based robust state estimation over a horizon length
           during measurement outliers
    • Authors: Khurram Ali, Muhammad Tahir
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel approach towards horizon-based maximum likelihood (ML) state estimator is proposed that makes the state estimation process more robust against unmodeled and unstructured noise and disturbances in the state-space models. State space models provide a powerful way to perform state and parameter estimation for dynamical systems. However, if the measurements are contaminated by outliers and disturbances with no known models, the estimation process is highly biased. A ML-based approach is used to find a batch solution for the filtering problem. Based on ML solution, a robust algorithm is proposed that seamlessly estimates dynamic state in the presence of zero or non-zero mean measurement outliers. The proposed algorithm that dictates this switching uses an explicit outlier detection mechanism that enables its seamless working. Simulations have been carried out for a moving target tracking application as an example to demonstrate the resilience of the proposed method against zero-mean and non-zero mean measurement outliers in comparison to state-of-the-art methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-10T10:38:36Z
      DOI: 10.1177/0142331220928896
       
  • Finite-time H∞ dynamic quantization inputs control for uncertain
           switched systems
    • Authors: Liangda Zhang, Baowei Wu, Lili Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the problem of finite-time stability and finite-time [math] stabilization for switched systems with parametric uncertainties and nonlinear disturbances satisfying Lipschitz condition. The dynamic quantization inputs feedback control technology is proposed to utilize quantized input measurements which can significantly reduce the communication burden. Sufficient conditions in terms of linear matrix inequality (LMIs) are presented through applying Lyapunov function method and average dwell approach to ensure the finite-time stability of the switched system. By analysing the feasibility of LMIs’ solution, the feedback gain matrix and the dynamic quantization parameter are obtained. In addition, more constraints are proposed to ensure the finite-time stabilization with a prescribed [math] performance index with respect to nonlinear disturbances, and the Lipschitz constant matrix of Lipschitz condition is not required to be known in advance. Finally, with the application to the proposed control of a numerical example and a two-stage chemical reactor system, the validity of the conclusion is verified.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-06T09:49:42Z
      DOI: 10.1177/0142331220933424
       
  • A hybrid fuzzy with feedback integral phase locked loop-based control
           strategy for unified power quality conditioner
    • Authors: Rajesh Kumar Patjoshi, Rakhee Panigrahi, Shasanka Sekhar Rout
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a hybrid fuzzy control strategy comprising both Takagi-Sugeno fuzzy and Mamdani fuzzy along with novel feedback integral phase-locked loop based modified synchronous reference frame for unified power quality conditioner for power quality enhancement in power distribution network. The hybrid fuzzy controller can vary the gain nonlinearly for controlling dc-bus capacitor voltage of unified power quality conditioner, which limits the dc-bus voltage deviations during the load and supply voltage turbulences. Moreover, the proposed novel feedback integral phase-locked loop system is employed to improve the grid synchronization performance of unified power quality conditioner by considering the feedback integral loop and nonlinear adaptive-filter type phase detector approach. As a consequence, the proposed feedback integral phase-locked loop system can extract the positive sequence signal perfectly during power system disturbances. Additionally, the novelty of modified synchronous reference frame control technique relies upon nonintervention with low pass filter as well as high pass filter. Hence, the proposed control technique quickly and accurately extracts the reference signal from the distorted power system. The efficacy of the proposed control technique is justified through a real-time Opal-RT Hardware underneath different states of power system and compared with both conventional modified phase locked loop system and Takagi-Sugeno fuzzy with synchronous reference frame-based control system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-06T07:48:17Z
      DOI: 10.1177/0142331220933760
       
  • Transfer function identification of a liquid flow-line pressure control
           system from simple relay auto-tuning
    • Authors: Prasenjit Ghorai, Somanath Majhi, Venkata Ramana Kasi, Saurabh Pandey
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Accurate modeling of liquid flow systems is necessary for the effective operation of the plant under different conditions. The plant dynamics may change with time, and due to this, the operation may not be satisfactory. In this article, relay autotuning of a liquid flow-line is proposed. Well-known describing function approximation is utilized for the estimation of gain of relay used in a feedback loop to excite the plant to be identified. The expressions are derived for the identification of a class of overdamped second-order plus dead-time and first-order plus dead-time plant dynamics. The identification method tested on different standard systems shows that the proposed method has good identification accuracy. Therefore, the proposed identification method is applied to a liquid flow line pressure control system. The experimental results show that an accurate dynamic model is extracted using the proposed method with a minimal set of data from an obtained limit cycle oscillation. The measured quantities of the limit cycle are utilized in the derived explicit expressions for the identification of unknown variables of the dynamic plant model. A distributed process control system is utilized here as a standard industrial platform to design virtual relay and conduct the proposed autotuning. The efficiency of the modeling method is demonstrated through the comparison of Nyquist and relay response plots with the transfer functions obtained from the MATLAB system identification toolbox.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-06T07:15:33Z
      DOI: 10.1177/0142331220934949
       
  • Event-triggered finite-time consensus for stochastic multi-agent systems
    • Authors: Zichao Yang, Shiqi Zheng, Bingyun Liang, Yuanlong Xie
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies a consensus problem for a kind of stochastic multi-agent systems (SMAS). First, a reduced-order observer is designed to estimate unknown states in SMASs. Second, an event-triggered adaptive output feedback control method is presented. It can reduce the controller updates and communication burden. Moreover, the radial basis function neural networks are applied to approximate the unknown functions in systems. Finally, it is demonstrated that the proposed control scheme can achieve finite-time practical consensus for SMASs. Simulation results are provided to illustrate the effectiveness of the theoretical analysis.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-06T07:11:14Z
      DOI: 10.1177/0142331220933441
       
  • Reduced-order observer-based consensus control of linear multi-agent
           systems over directed networks with nonuniform communication delays
    • Authors: Qiuzhen Wang, Jiangping Hu, Yiyi Zhao, Bijoy Kumar Ghosh
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper considers a consensus control of a general linear multi-agent system with time-varying communication delays. Since each agent can only use the relative output information from its neighbors, a reduced-order observer-based control protocol is proposed to guarantee consensus on the directed communication network. The stability of the closed-loop system is analyzed for the cases with uniform delays and nonuniform time-varying delays, respectively. Moreover, the upper bounds of the communication delays are obtained respectively for the two cases. Finally, two numerical examples are provided to illustrate the proposed theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-03T06:13:07Z
      DOI: 10.1177/0142331220934306
       
  • Multi-model estimation using neural network and fault detection in unknown
           time continuous fractional order nonlinear systems
    • Authors: Gholamreza Nassajian, Saeed Balochian
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, multi-model estimation and fault detection using neural network is proposed for an unknown time continuous fractional order nonlinear system. Fractional differentiation is considered based on Caputo concept and the fractional order is considered to be between 0 and 1. In order to estimate a time continuous fractional order nonlinear system with unknown term in its dynamic, single-layer and double-layer RBF neural network is used. First, a parallel-series neural network observer is designed for state estimation. Weights of the neural network are updated adaptively and updating laws are presented in fractional order form. Using Lyapunov method, it is proved that state estimation error and weight estimation error of the neural network are bounded. Parameters of the neural estimator converge to ideal parameters which satisfy excitation condition stability. Then, multi-model estimation structure of fractional order nonlinear systems is presented and its application in fault detection is investigated. Finally, simulation results are presented to show efficiency of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-29T10:42:45Z
      DOI: 10.1177/0142331220932376
       
  • A fast alignment of marine strapdown inertial navigation system based on
           adaptive unscented Kalman Filter
    • Authors: Hossein Rahimi, Amir Ali Nikkhah, Kaveh Hooshmandi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study has presented an efficient adaptive unscented Kalman filter (AUKF) with the new measurement model for the strapdown inertial navigation system (SINS) to improve the initial alignment under the marine mooring conditions. Conventional methods of the accurate alignment in the ship’s SINS usually fail to succeed within an acceptable period of time due to the components of external perturbations caused by the movement of sea waves and wind waves. To speed up convergence, AUKF takes into account the impact of the dynamic acceleration on the filter and its gain adaptively tuned by considering the dynamic scale sensed by accelerometers. This approach considerably improved the corrections of the current residual error on the SINS and decreased the influence due to the external perturbations caused by the ship’s movement. Initial alignment algorithm based on AUKF is designed for large misalignment angles and verified by experimental data. The experimental test results show that the proposed algorithm enhanced the convergence speed of SINS initial alignment compared with some state-of-the-art existing approaches.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-29T10:41:23Z
      DOI: 10.1177/0142331220934293
       
  • Dual-loop generalized predictive control method for two-phase three-wire
           railway active power quality controller
    • Authors: Hamed Jafari Kaleybar, Morris Brenna, Federica Foiadelli
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      One of the most challenging topics in electric railway networks (ERNs) is power quality (PQ) problems caused by single-phase feeding of time-varying and high-power locomotives. During previous years, many techniques and compensators have been offered to alleviate these problems. Railway active power quality controller (RAPQC) is considered as one of the most efficient approaches. Due to the time-variant, uncertainty and distorted features of ERNs, the controlling of RAPQCs has always been a substantial concern to experts. This paper presents, a new robust control system for two-phase three-wire RAPQC (ThRAPQC) based on generalized model predictive control integrated with modified instantaneous reactive power theory (GMPC-MIRP). A dual-loop balancing system has been adopted in the proposed control system to equalize the active powers of traction power substation (TPSS) adjacent feeders, compensate reactive powers and suppress harmonic simultaneously. The performance of the proposed method in comparison with the conventional Fryze-Buchholz-Depenbrock (FBD)-based current strategy together with hysteresis current controller (FBD-HCC) has been evaluated through the detailed simulations and Opal-RT 5600-based laboratory setup results. The fast response, high precision, lower fluctuation in reference current tracking and high capability of working in distorted conditions are the outstanding privileges of the proposed method that are confirmed by the output results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-26T08:37:07Z
      DOI: 10.1177/0142331220932470
       
  • LSTM-based soft sensor design for oxygen content of flue gas in coal-fired
           power plant
    • Authors: Hongguang Pan, Tao Su, Xiangdong Huang, Zheng Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      To address problems of high cost, complicated process and low accuracy of oxygen content measurement in flue gas of coal-fired power plant, a method based on long short-term memory (LSTM) network is proposed in this paper to replace oxygen sensor to estimate oxygen content in flue gas of boilers. Specifically, first, the LSTM model was built with the Keras deep learning framework, and the accuracy of the model was further improved by selecting appropriate super-parameters through experiments. Secondly, the flue gas oxygen content, as the leading variable, was combined with the mechanism and boiler process primary auxiliary variables. Based on the actual production data collected from a coal-fired power plant in Yulin, China, the data sets were preprocessed. Moreover, a selection model of auxiliary variables based on grey relational analysis is proposed to construct a new data set and divide the training set and testing set. Finally, this model is compared with the traditional soft-sensing modelling methods (i.e. the methods based on support vector machine and BP neural network). The RMSE of LSTM model is 4.51% lower than that of GA-SVM model and 3.55% lower than that of PSO-BP model. The conclusion shows that the oxygen content model based on LSTM has better generalization and has certain industrial value.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-26T08:35:27Z
      DOI: 10.1177/0142331220932390
       
  • Performance evaluation of constant current and constant voltage charge
           control modes of an inductive power transfer circuit with double-sided
           inductor-capacitor-capacitor and inductor-capacitor/series compensations
           for electrical vehicle battery charge applications
    • Authors: Sevilay Cetin, Veli Yenil
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      For electric vehicle (EV) battery chargers, inductive power transfer (IPT) has become popular day by day due to its features such as being safe, comfortable and weather proof. The constant current (CC) and the constant voltage (CV) charge control modes are important for high-efficiency charging and long-life use of Lithium-ion (Li-ion) batteries commonly used in EVs. However, IPT method requires a wide range of operating frequency in order to provide CC/CV charge control modes. In IPT applications, CC and CV charge control modes are mainly achieved with dc-dc circuits using compensation networks at the transmitter and receiver sides. In this study, performances of inductor-capacitor/series compensation and double-sided inductor-capacitor-capacitor compensation topologies are evaluated based on CC/CV charge control modes. The analytical evaluation is presented in terms of voltage and current regulations during the entire charge control period. Finally, presented analytical evaluation is confirmed with ANSYS software providing field-electric common simulation to predict real response of compensation topologies. In the simulation work, both compensation topologies are operated for the maximum 2.5 kW output power and at the 250 V-450 V output voltage range.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-22T10:55:59Z
      DOI: 10.1177/0142331220932438
       
  • Suboptimal obstacles avoidance control of spacecraft rendezvous
    • Authors: Lu Cao, Bing Xiao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Spacecraft on-orbital services and docking require their autonomous rendezvous control system to have obstacle avoidance capability. Motivated by this, a suboptimal velocity artificial potential function-based control scheme is presented. An ellipsoid model is applied to describe the outer envelopes of the service spacecraft and the obstacles via an eigenvalue algorithm. This has better description precision than the traditional methods. The potential sigmoid function is used to generate repulsive force to avoid obstacles collision. A velocity artificial potential function-based controller is finally developed to ensure that the relative speed of the service spacecraft is reduced to zero before reaching the outer envelops of obstacles. The shaping parameters of the attractive potential function are adaptively optimized. Numerical simulations are performed to demonstrate that the approach can achieve a safe and autonomous rendezvous with fuel cost saved.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-22T10:50:38Z
      DOI: 10.1177/0142331220928886
       
  • Suboptimal midcourse guidance design using generalized model predictive
           spread control
    • Authors: Amin Ebrahimi, Ali Mohammadi, Abdorreza Kashaninia
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A new generalized model predictive spread control technique is presented for the midcourse guidance of interceptors that are designed to intercept high-speed ballistic missile targets. Because of using the basis functions, this new technique is further computationally efficient over the model predictive static programming technique. Also, the smoothness of the control variable is guaranteed for the smooth basis functions. For demonstrating the performance of the proposed technique, an interceptor midcourse guidance problem with an angle constraint is formulated and solved to intercept an incoming ballistic missile target successfully. Additionally, the results are compared with those of the midcourse guidance design using the model predictive static programming technique. A comparative study of the new technique has also been conducted with the quasi-spectral model predictive static programming technique proposed earlier in the literature. It has been observed that the orthogonality of the basis functions is a necessary assumption and without that, the quasi-spectral model predictive static programming technique is not a near-optimal technique. By using the new technique based on Legendre basis functions, the solution converges to the model predictive static programming method solution by increasing the number of basis functions with less computational load.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-22T10:48:19Z
      DOI: 10.1177/0142331220928888
       
  • Prescribed performance trajectory tracking control of dynamic positioning
           ship under input saturation
    • Authors: Yuanhui Wang, Haibin Wang, Mingyu Fu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates concentrates on the trajectory tracking control problem of dynamic positioning (DP) ship, in the presence of the time-varying disturbance and input saturation. Firstly, a simplified mathematical model of three degrees of freedom is established. According to the characteristics of the DP ship, an adaptive backstepping controller which combine the prescribed performance function with disturbance observer is proposed. The control scheme can guarantee the transient and steady state performance of the trajectory tracking and meet the prescribed performance criteria. In addition, an auxiliary dynamic system is introduced into the controller to deal with the input saturation problem of the actuator, so that the DP ship can accomplish the task of trajectory tracking under the condition of actuator constraint. Subsequently, in combination of barrier Lyapunov function (BLF), it is proved that the DP system can stabilize and converge rapidly to the small neighborhood of the equilibrium point, which can achieve the prescribed performance. Finally, the effectiveness of the DP control law is demonstrated by a series of simulation experiments.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-19T10:37:41Z
      DOI: 10.1177/0142331220928887
       
  • Optimal IMC-PID controller design for large-scale power systems via EDE
           algorithm-based model approximation method
    • Authors: Vasu G, Sivakumar M, Ramalingaraju M
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the authors propose an optimal IMC-PID controller design for the Load Frequency Control (LFC) of large-scale power system via model approximation method. The model approximation method uses the Enhanced Differential Evolution (EDE) algorithm to determine an optimal Reduced Order Model (ROM) for the considered large-scale power system by minimizing the performance measure called Integral Square Error (ISE) between their step responses. Later, the LFC design is carried out using an optimal ROM instead of processing with the large-scale power system model. Thus, this simplifies the design, reduces the computational efforts and also helps in determining the lower order controller. An optimal IMC design methodology is proposed by minimizing ISE between the actual output and the reference input responses of the large-scale power system using EDE algorithm. Further, PID controller gains are acquired by least square model matching with the optimal IMC transfer function. The proposed IMC-PID controller design allows a satisfied reference input tracking performance, robustness in disturbance rejection and improves the dynamic stability of the power system. The proposed method is validated by applying it to a single area power system of third-order SISO model and also extended to a centralized two-area thermal–thermal non-reheated power system of a seventh-order MIMO model. The simulation results and the comparison of error performance indices show the efficacy of the proposed method over the significant methods available in the literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-15T09:44:27Z
      DOI: 10.1177/0142331220921578
       
  • H∞ fuzzy proportional integral state feedback controller of photovoltaic
           systems under asymmetric actuator constraints
    • Authors: K Houda, D Saifia, M Chadli, S Labiod
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a new strategy for a robust maximum power point (MPP) tracking fuzzy controller for photovoltaic (PV) systems subject to actuator asymmetric saturation. A DC-DC boost converter is used to connect a PV panel with an output load. The output voltage of the DC-DC boost converter can be adjusted by duty ratio that is limited between 0 and 1. The aim of our control design is to track the MPP under atmospheric condition changes and the presence of the asymmetric saturation of the duty ratio. To minimize tracking error and disturbance effect, the dynamic behaviour of a PV system and its reference model are described by using Takagi–Sugeno fuzzy models. Then, a constrained control based on a fuzzy PI state feedback controller is proposed. The H∞ control approach is used in control design and stability conditions of the closed-loop system are formulated and solved in terms of linear matrix inequalities. Finally, simulation results are given to show the tracking performance of the control design.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-08T07:15:37Z
      DOI: 10.1177/0142331220921579
       
  • A novel load prediction method for hybrid electric ship based on working
           condition classification
    • Authors: Diju Gao, Yao Jiang, Nan Zhao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to effectively optimize the load distribution between power sources during the navigation of hybrid ships, a method for predicting ship load demand based on real-time classification according to different working conditions is proposed. The k-means clustering algorithm is used to quantify the voyage history data to classify the ship’s navigation conditions into fast-changing conditions and slow-changing conditions. Some characteristic parameters related to working conditions are selected as input. Then, input and the category of working conditions are put into least squares support vector machine to learn and train to get an online working condition classifier. The genetic algorithm is used to optimize the radial-based neural network to predict the load demand under fast-changing conditions, use the Markov chain model to predict the load demand under slow-changing conditions, so as to obtain the most accurate future load demand of the ship. The simulation results show that the proposed prediction models under different conditions have higher precision, which is an effective means of predicting the load demand for hybrid power ships.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-08T04:20:49Z
      DOI: 10.1177/0142331220923767
       
  • An improved DC-DC converter with high voltage gain based on fully tapped
           quadratic boost converter for grid connected solar PV micro-inverter
    • Authors: Lakhdar Bentouati, Ali Cheknane, Boumediène Benyoucef, Oscar Barambones
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The need to increase the voltage level produced by PV systems becomes an urgent task to be compatible with the requirements of the AC load, but we meet problems in the operation of the step-up converter at a high duty cycle which is not preferred due to the reduction in voltage gain, and also a higher number of turns ratio in the windings inductance coupled adds to the overall losses of the converter. This article proposes an improved DC-DC converter with a lower duty cycle by integrating three tapped-inductors in new topology, which combined quadratic boost converter and tapped-inductor boost converter. The proposed converter achieves a high voltage gain with a lower duty ratio (Gmax = 14.32) and a maximum efficiency of 98.68% is improved compared to the voltage gain and efficiency results of these converters in several recently published references. The analyses are done theoretically and supported with simulation results. A prototype of the proposed converter has been built to experimentally validate the obtained results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-08T04:12:28Z
      DOI: 10.1177/0142331220921988
       
  • Moving sliding mode controller for overhead cranes suffering from matched
           and unmatched disturbances
    • Authors: Xiutao Gu, Weimin Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel time-varying gain extended state observer (ESO)-based moving sliding mode control method is proposed for anti-sway and positioning control of two-dimensional underactuated overhead cranes. The designed moving sliding mode surface can adjust its slope in real time according to the state variable errors; in addition, a dynamic exponential term is added into the moving sliding mode surface so as to drive any initial state variable errors into the sliding surface rapidly, and thereby the robustness of crane systems is improved. Then, a chattering-free reaching law is designed to realize fast convergence of the system state errors, and the input is modelled as a saturated one due to the fact the motor torque is bounded and the control law and adaptive updating law of switching gain are derived in the sense of Lyapunov function, so the stability can be guaranteed even under the input saturation. Moreover, to suppress the matched and unmatched disturbance occurring in crane dynamic systems, a time-varying gain ESO is constructed to estimate the lumped disturbance, then the estimated value is used for feedforward compensation to establish the controller. Finally, the simulation results confirm the effectiveness of the proposed controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-04T09:22:19Z
      DOI: 10.1177/0142331220922109
       
  • An improved method for swing measurement based on monocular vision to the
           payload of overhead crane
    • Authors: Jinling Huang, Weimin Xu, Weiwei Zhao, Hesong Yuan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to solve the problem that the blurred image of a moving object decreases accuracy in the process of detecting the payload swing angle of an overhead crane based on vision, and the tracking failure caused by the drastic change of grey targets, a robust real-time detection method of the load swing angle of a bridge crane is proposed. This method uses a spherical marker attached to the load, which is insensitive to rotation and tilt when it is detected. First, it uses the mean shift algorithm combined with Kalman filter to track the moving objects in the image plane continuously, and then integrates the method of minimum area circle to detect the spherical marker image in the region of interest accurately and quickly. Finally, combined with the geometric method, the real-time swing angle is calculated. In addition, the angle diagram method is used to increase the speed of calculating the swing angle. The experimental results show that the method is effective for detecting the load target swing angle of different trolley motion speed.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-04T08:44:10Z
      DOI: 10.1177/0142331220921318
       
  • Sub-fixed-time control for a class of second order system
    • Authors: Boyan Jiang, Hua Chen, Bo Li, Xuewu Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a new concept “sub-fixed-time stability” (SFTS) is proposed and studied, which means the states can converge to a region of equilibrium points in a fixed time for any initial states’ values. Then, a sufficient condition for it is given and proven. Though SFTS is similar to “practical fixed-time stability” (PFTS), they are not the same, and the sufficient condition for SFTS is much clearer and simpler than PFTS. Next, a sub-fixed-time controller is proposed for a class of second order system. The stability analyses are given in the case without disturbance and with disturbance, respectively. Finally, to illustrate the robustness of the proposed sub-fixed-time controller to different initial conditions, 100 numerical simulations are conducted for 100 initial states’ values.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-01T09:46:01Z
      DOI: 10.1177/0142331220921008
       
  • Optimum utilization of grid connected hybrid renewable energy sources
           using hybrid algorithm
    • Authors: M. Suresh, R. Meenakumari
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An optimal utilization of smart grid connected hybrid renewable energy sources is proposed in this paper. The hybrid technique is the combination of recurrent neural network and adaptive whale optimization algorithm plus tabu search, called AWOTS. The main objective is the RES optimum operation for decreasing the electricity production cost by hourly day-ahead and real time scheduling. Here, the load demands are predicted using AWOTS to develop the correct control signals based on power difference between source and load side. Adaptive whale optimization algorithm searching behaviour is adjusted by tabu search. The proposed technique is executed in the MATLAB/Simulink working platform. To test the performance of the proposed method, the load demand for the 24-hour time period is demonstrated. By then the power generated in the sources, such as photovoltaic, wind turbine, micro turbine and battery by the proposed technique, is analyzed and compared with existing techniques, such as genetic algorithm, particle swarm optimization and whale optimization algorithm. Furthermore, the state of charge of the battery for the 24-hour period is compared with existing techniques. Likewise, the cost of the system is compared and error in the sources also compared. The comparison results affirm that the proposed technique has less computational time (35.001703) than the existing techniques. Moreover, the proposed method is cost-effective power production of smart grid and effective utilization of renewable energy sources without wasting the available energy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-01T09:43:21Z
      DOI: 10.1177/0142331220913740
       
  • Real time assessment of power quality issues in 11 kV/440 V distribution
           feeder using distribution static synchronous compensator
    • Authors: Suresh Srinivasan, Murugaperumal Krishnamoorthy, RK Pongiannan, S Jeyasudha
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The effects of power quality (PQ) issues in a distribution feeder occur due to abnormal load condition. In this paper, first, the real time PQ issues in an 11 kV/440 V distribution feeder are measured and analyzed by PQ analyzers. The sudden load fluctuations in the distribution system result in different PQ issues such as voltage sag/swell, transient, flicker and harmonics. Then, an improved interactive distribution static synchronous compensator (D-STATCOM) is installed in distribution feeder to mitigate the PQ issues. A novel control algorithm will operate the interactive D-STATCOM in voltage control mode (VCM) or current control mode (CCM). At normal operating conditions, the D-STATCOM operates in CCM, during abnormal condition the D-STATCOM will operates in VCM to mitigates the PQ issues. The D-STATCOM is modeled and simulated in MATLAB-SIMULINK environment. The field programmable gate array (FPGA)-based laboratory prototype D-STATCOM has been developed to validate the function of the controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-05-04T11:27:10Z
      DOI: 10.1177/0142331220913009
       
  • Robust model reference control for uncertain second-order system subject
           to parameter uncertainties
    • Authors: Guang-Tai Tian, Guang-Ren Duan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is devoted to designing a robust model reference controller for uncertain second-order systems subject to parameter uncertainties. The system matrix of the first-order reference model is more general and the parameter uncertainties are assumed to be norm-bounded. The design of robust controller can be devided into two separate problems: problem robust stabilization and problem robust compensation. Based on the solution of generalized Sylvester matrix equations, we obtain some sufficient conditions to guarantee the complete parameterization of the controller. Then, the problem robust compensation of the closed-loop system is estimated by solving a convex optimisation problem with a set of linear matrix equations constraints. Two simulation examples are provided to illustrate the effectiveness of the proposed technique.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-02-27T06:48:11Z
      DOI: 10.1177/0142331220904544
       
  • An adaptive control approach for semi-active suspension systems under
           unknown road disturbance input using hardware-in-the-loop simulation
    • Authors: Gokhan Kararsiz, Mahmut Paksoy, Muzaffer Metin, Halil Ibrahim Basturk
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article presents an application of the adaptive control method to semi-active suspension systems in the presence of unknown disturbance and parametric uncertainty. Due to the technical difficulties such as time delay and sensor noise, the road disturbance is assumed to be unmeasured. To overcome this problem, an observer is designed to estimate the disturbance. It is considered that the road profile consists of a finite number of the sum of sinusoidal signals with unknown amplitudes, phases and frequencies. After the parametrization of the observer, the adaptive control approach is employed to attenuate the effect of the road-induced vibrations using a magnetorheological damper. It is proved that the closed-loop system is stable, despite the adverse road conditions. Finally, the performance of the controller is illustrated with a hardware-in-the-loop simulation in which the system is subjected to sinusoidal and random profile road excitations. To demonstrate the benefits of the adaptive controller, the results are presented in comparison with a conventional proportional integral derivative (PID) controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-01-30T08:38:09Z
      DOI: 10.1177/0142331219895935
       
  • Bilateral teleoperation with continuously variable scaling and PD force
           control
    • Authors: Burak Oztoprak, Eray A. Baran, Asif Sabanovic
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the bilateral teleoperation with the possibility of continuously variable scaling during real-time operation. The algorithm proposed for this purpose provides the operator with the ability to change the scaling gains of force and velocity loops during operation. The controllers are derived to enforce exponentially decaying error dynamics on systems which have inner loop disturbance compensation. The proposed architecture assumes the scale factors as continuous functions of time which have continuous derivatives that are also included in the mathematical derivation. Unlike the existing studies, the presented framework allows real-time adaptation of scaling gains, which provides the user with the ability to conduct coarse and fine motion in the same operation. The Lyapunov stability proof of the proposed method is made and the margins of the controller gains are identified for practical operation. Furthermore, the operational accuracy is enhanced by the application of a PD force control loop which is also new for scaled bilateral teleoperation. The realization of PD loop is made using an [math]-[math]-[math] filter to differentiate the force signal. The algorithm is validated on a setup consisted of two single DOF motion control systems. In order to provide a complete analysis, a wide range of experiments are made, velocity and force scales having sinusoidal patterns with different amplitudes and frequencies. Moreover, comparison with a classical bilateral control architecture is made to highlight the flexibility of the proposed control method. The efficacy of the proposed approach is solidified by the successful tracking responses obtained from these experiments.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-01-27T11:53:01Z
      DOI: 10.1177/0142331219895922
       
  • Priority-based speed control strategy for automated guided vehicle path
           planning in automated container terminals
    • Authors: Meisu Zhong, Yongsheng Yang, Shu Sun, Yamin Zhou, Octavian Postolache, Ying-En Ge
      First page: 3079
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      With the continuous increase in labour costs and the demands of the supply chain, improving the efficiency of automated container terminals has been a key factor in the development of ports. Automated guided vehicles (AGVs) are the main means of horizontal transport in such terminals, and problems in relation to their use such as vehicle conflict, congestion and waiting times have become very serious, greatly reducing the operating efficiency of the terminals. In this article, we model the minimum driving distance of AGVs that transport containers between quay cranes (QCs) and yard cranes (YCs). AGVs are able to choose the optimal path from pre-planned paths by testing the overlap rate and the conflict time. To achieve conflict-free AGV path planning, a priority-based speed control strategy is used in conjunction with the Dijkstra depth-first search algorithm to solve the model. The simulation experiments show that this model can effectively reduce the probability of AGVs coming into conflict, reduce the time QCs and YCs have to wait for their next task and improve the operational efficiency of AGV horizontal transportation in automated container terminals.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-28T01:19:43Z
      DOI: 10.1177/0142331220940110
       
  • Speed-adaptive dynamic surface attitude control for a satellite with
           moving masses under input constraints
    • Authors: Yuandong Hu, Zhengliang Lu, Wenhe Liao
      First page: 3091
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates an attitude control technique for a low Earth orbit nanosatellite with moving masses based on the active use of aerodynamic forces. A speed-adaptive dynamic surface control scheme is designed to comprehensively solve the practical problems of aerodynamic model error, the dynamic effect of movement, stroke limitation, and slow convergence. Multiple constraints are imposed on the inputs to reduce the fast-varying dynamic effect of the masses to be negligible. Other slow-varying disturbances are precisely estimated by a nonlinear observer. In particular, to resolve the contradiction between the overshoot and the attitude convergence speed, a novel adaptive law is designed based on the smooth hyperbolic tangent function to adjust the convergence parameter within the given boundary. Moreover, considering the actual physical limitation, hard constraints are imposed on two actuators. Finally, by using the Lyapunov approach, it is proven that, despite uncertain dynamics, unknown disturbances and input constraints, the attitude error can be adjusted to be arbitrarily small by choosing the proper parameters. A semi-physical simulation platform is built to verify the feasibility of the moving mass actuator and the effectiveness and robustness of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-28T02:21:22Z
      DOI: 10.1177/0142331220940427
       
  • Rotor-current-based fault detection for doubly-fed induction generator
           using new sliding mode observer
    • Authors: Wenxin Yu, Dan Jiang, Junnian Wang, Ruiqi Li, Lu Yang
      First page: 3110
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      To detect the fault of the doubly-fed induction generator (DFIG), in this paper, a fault detection method of novel sliding mode observer is proposed, without a velocity sensor. In addition to better elimination of chattering for the new sliding mode observer, at the same time, it has better stability and faster convergence speed than the traditional sliding mode observer. Firstly, the sliding mode observer is built according to the mathematical model of the DFIG. Then, the rotor current and the rotational speed are estimated. After comparing the actual rotor current value with the observed value, the self-detection of the fault for the DFIG is realized. Secondly, three faults of grid voltage sags failure, DFIG inter-turn stator fault and rotor current sensor fault are given respectively. After that the Simulink simulation model is built under different fault conditions. It is proved by simulation that this sliding mode observer can well detect faults occurring at different positions. Additionally, it can also be proved that the sliding mode observer has the characteristics of fast response and good stability.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-28T07:30:15Z
      DOI: 10.1177/0142331220941009
       
  • Integral-Proportional Derivative tuning for optimal closed loop responses
           to control integrating processes with inverse response
    • Authors: Ibrahim Kaya
      First page: 3123
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper provides optimum analytical tuning rules to determine tuning parameters of Integral-Proportional Derivative (I-PD) controllers for controlling integrating processes with inverse response and time delay. Integral performance criteria, such as ISTE (integral of squared time error), IST2E (integral of squared time2 error) and IST3E (integral of squared time3 error), are used to derive mentioned optimum tuning rules. The effectiveness of the proposed I-PD controller design method are shown by simulation examples. Comparisons with design methods existing in the literature, in terms of set point tracking and disturbance rejection capability, are performed to see the use of the proposed I-PD controller. Some performance measures are also given to evaluate the closed loop performances. It has been observed that the proposed I-PD controller has some important advantages over design methods used for comparison.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-04T11:41:11Z
      DOI: 10.1177/0142331220941657
       
  • Observer-based robust control for flexible-joint robot manipulators: A
           state-dependent Riccati equation-based approach
    • Authors: Neda Nasiri, Ahmad Fakharian, Mohammad Bagher Menhaj
      First page: 3135
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the robust control problem is tackled by employing the state-dependent Riccati equation (SDRE) for uncertain systems with unmeasurable states subject to mismatched time-varying disturbances. The proposed observer-based robust (OBR) controller is applied to two highly nonlinear, coupled and large robotic systems: namely a manipulator presenting joint flexibility due to deformation of the power transmission elements between the actuator and the robot known as flexible-joint robot (FJR) and also an FJR incorporating geared permanent magnet DC motor dynamics in its dynamic model called electrical flexible-joint robot (EFJR). A novel state-dependent coefficient (SDC) form is introduced for uncertain EFJRs. Rather than coping with the OBR control problem for such complex uncertain robotic systems, the main idea is to solve an equivalent nonlinear optimal control problem where the uncertainty and disturbance bounds are incorporated in the performance index. The stability proof is presented. Solving the complicated robust control problem for FJRs and EFJRs subject to uncertainty and disturbances via a simple and flexible nonlinear optimal approach and no need of state measurement are the main advantages of the proposed control method. Finally, simulation results are included to verify the efficiency and superiority of the control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-06T09:28:19Z
      DOI: 10.1177/0142331220941653
       
  • Leader-following consensus of second-order multi-agent systems with
           time-varying delays and arbitrary weights
    • Authors: Lin Shi, Dongmei Xie
      First page: 3156
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Using Lyapunov first method instead of traditional Lyapunov second method, this paper focuses on studying the consensus tracking control problem of multi-agent systems (MASs) with time-varying delays and arbitrary adjacent weights under fixed topology and switching topology, respectively. We first give four equivalent criteria for MASs with fixed communication topology, where the positive stability of matrix [math] (L is the Laplacian matrix of [math], B is the leader’s adjacency matrix) not only plays a key role as usual but also becomes an urgent and more complicated problem due to the introduction of negative weights in MASs. Second, for MASs with switching communication topology if the average dwell time of switching topology, the total activation time of stable subsystems and the upper bound of time delay satisfy some conditions, then MASs with all stable subsystems (partially stable subsystems) can achieve consensus tracking. Finally, simulations are given to demonstrate the effectiveness of our theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-04T11:41:23Z
      DOI: 10.1177/0142331220942715
       
  • Static output feedback stabilization of discrete time linear time
           invariant systems based on approximate dynamic programming
    • Authors: Okan Demir, Hitay Özbay
      First page: 3168
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study proposes a method for the static output feedback (SOF) stabilization of discrete time linear time invariant (LTI) systems by using a low number of sensors. The problem is investigated in two parts. First, the optimal sensor placement is formulated as a quadratic mixed integer problem that minimizes the required input energy to steer the output to a desired value. Then, the SOF stabilization, which is one of the most fundamental problems in the control research, is investigated. The SOF gain is calculated as a projected solution of the Hamilton-Jacobi-Bellman (HJB) equation for discrete time LTI system. The proposed method is compared with several examples from the literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-04T11:41:40Z
      DOI: 10.1177/0142331220943071
       
  • Predictive current control of a bearingless induction motor model based on
           fuzzy dynamic objective function
    • Authors: Zebin Yang, Jiajie Wu, Chengling Lu, Ding Wang
      First page: 3183
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A control strategy for a bearingless induction motor (BL-IM) based on the fuzzy dynamic objective function is proposed in this paper. Firstly, based on the discrete mathematical model of the BL-IM, the stator current and flux linkage are predicted according to the given stator current and flux linkage, the objective function of model predictive current control (MPCC) is designed. Secondly, the fuzzy control algorithm is introduced in the objective function of the MPCC to dynamically assign the weighting factors before the current component on the d-q axis and the influence of the objective function on the performance of the BL-IM is analyzed under different weighting factors. By discretizing the rotational speed deviation Δω and rotational speed deviation rate, fuzzy reasoning is performed to obtain the optimal fuzzy dynamic function. Finally, the optimal fuzzy dynamic function is selected as the objective function of the MPCC to perform the simulations and experiments. The results show that the performance of the BL-IM under the MPCC strategy based on the fuzzy dynamic objective function is improved compared with the traditional MPCC and the vector control based on the fuzzy PID, due to its better dynamic and suspension performance. Meanwhile, the stability of rotor current component is enhanced.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-13T11:03:38Z
      DOI: 10.1177/0142331220944076
       
  • The design of a fractional-order sliding mode controller with a
           time-varying sliding surface
    • Authors: Osman Eray, Sezai Tokat
      First page: 3196
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The novelty of this paper is the usage of a time-varying sliding surface with a fractional-order sliding mode controller. The objective of the controller is to allow the system states to move to the sliding surface and remain on it so as to ensure the asymptotic stability of the closed-loop system. The Lyapunov stability method is adopted to verify the stability of the controller. Firstly, by using the geometric coordinate transformation that is formerly defined for conventional sliding mode controller, a novel fractional-order sliding surface is defined. The time-varying fractional-order sliding surface is then rotated in the region in which the system state trajectories are stable. The adjustment of the sliding surface slope on the new coordinate axes is achieved by tuning a parameter defined as a sigmoid function. Then, a new control rule is derived. Numerical simulations are performed on the nonlinear mass-spring-damper and 2-DOF robot manipulator system models with parameter uncertainties and bounded external disturbances. The proposed controller is compared with the conventional sliding mode controller with a constant sliding surface and the fractional-order sliding mode controller with a constant sliding surface. Simulation results have shown improved performance of the proposed controller in terms of a decrease in the reaching and settling time, and robustness to disturbances as compared with the related controllers. Moreover, it is seen that the designed controller provides an improvement in the error state trajectories.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-06T09:28:21Z
      DOI: 10.1177/0142331220944626
       
  • Anti-windup reconfigurable control for dynamic positioning vessel with
           thruster faults
    • Authors: Mingyang Li, Wenbo Xie, Jian Zhang
      First page: 3216
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, an anti-windup reconfigurable control method is developed for dynamic positioning vessel in the presence of thruster faults and input saturation. The designed reconfiguration block acting as a virtual thruster aims at hiding the faults from the nominal controller. Also, it is added into the closed-loop system between the nominal controller and the dynamic positioning system. A thruster saturation-failure fault matrix technique is proposed to regard the thruster saturation as thruster fault, meanwhile an auxiliary system is constructed to achieve extra compensation for the adverse effects induced by input saturation. Furthermore, an integral sliding mode control method is presented to accommodate the nonlinear items in the reconfiguration block. An adaptive technique is also employed to preserve robustness against the unknown uncertainties. Finally, a vessel dynamic positioning control process is adopted to evaluate the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-06T09:30:02Z
      DOI: 10.1177/0142331220944909
       
  • Robust output tracking of nonlinear systems with transient improvement via
           funnel-based sliding mode control
    • Authors: Mehdi Zahedi, Tahereh Binazadeh
      First page: 3225
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies a new procedure for robust tracking of nonlinear systems. This procedure is based on the combination of the sliding mode control and the funnel control, which in addition to the robust performance of the closed-loop system in the face of model uncertainties and/or external disturbances also leads to improvement of the characteristics of the transient responses. Using funnel control and the appropriate choice of the funnel can affect the convergence rate and overshoot. In this regard, a theorem has been presented and the effective performances of the suggested controller have been guaranteed in various respects based on exact mathematical analysis. Simulations have also been carried out to illustrate the efficiency of the proposed approach and to verify the theoretical achievements of the paper despite model uncertainties and external disturbances.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-21T10:53:38Z
      DOI: 10.1177/0142331220947556
       
  • Constrained stochastic control of positive Takagi-Sugeno fuzzy systems
           with Markov jumps and its application to a DC-DC boost converter
    • Authors: Mohamed Aatabe, Fatima El Guezar, Hassane Bouzahir, Alessandro N Vargas
      First page: 3234
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a stabilization control for positive, Takagi-Sugeno fuzzy systems subject to Markov jump parameters. In the continuous-time formulation, the approach guarantees mean-square stability with constraints on the control—the main condition hinges upon linear matrix inequalities. The proposed method’s usefulness is illustrated by a practical-oriented example, which was designed to control the output voltage of a DC-DC boost converter subject to both voltage and load variations driven by a Markov chain.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-21T09:49:23Z
      DOI: 10.1177/0142331220947553
       
  • Part-based multi-task deep network for autonomous indoor drone navigation
    • Authors: Xiangzhu Zhang, Lijia Zhang, Hailong Pei, Frank L. Lewis
      First page: 3243
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Two common methods exist for solving indoor autonomous navigation and obstacle-avoidance problems using monocular vision: the traditional simultaneous localization and mapping (SLAM) method, which requires complex hardware, heavy calculations, and is prone to errors in low texture or dynamic environments; and deep-learning algorithms, which use the fully connected layer for classification or regression, resulting in more model parameters and easy over-fitting. Among the latter ones, the most advanced indoor navigation algorithm divides a single image frame into multiple parts for prediction, resulting in doubled reasoning time. To solve these problems, we propose a multi-task deep network based on feature map region division for monocular indoor autonomous navigation. We divide the feature map instead of the original image to avoid repeated information processing. To reduce model parameters, we use convolution instead of the fully connected layer to predict the navigable probability of the left, middle, and right parts. We propose that the linear velocity is determined by combining three prediction probabilities to reduce collision risk. Experimental evaluation shows that the proposed method is nine times smaller than the previous state-of-the-art methods; further, its processing speed and navigation capability increase more than five and 1.6 times, respectively.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-28T12:01:46Z
      DOI: 10.1177/0142331220947507
       
  • Finite/fixed-time consensus of nonlinear multi-agent systems against
           actuator faults and disturbances
    • Authors: Yanhui Yin, Fuyong Wang, Zhongxin Liu, Zengqiang Chen
      First page: 3254
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the consensus tracking problem in nonlinear multi-agent systems against external disturbances and multiple actuator faults. The nonlinear dynamics are unknown and the leader’s input is unavailable to any follower. By using finite-time Lyapunov stability theory, a distributed discontinuous protocol is developed. On this basis, a fixed-time control protocol is further designed to obtain a settling time regardless of initial conditions. In addition, the practical finite-time consensus and practical fixed-time consensus are investigated by the adaptive technique, under which the bounds of the faults can be estimated online adaptively. The innovation of this work lies in the fact that the finite/fixed-time consensus problem is solved when multiple faults and mismatched nonlinearity are simultaneously considered. The relationship between the settling time and design parameters is well established. Finally, some numerical simulations are given to verify the effectiveness of the theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-27T09:05:06Z
      DOI: 10.1177/0142331220949354
       
  • Integrated nonlinear robust adaptive control for active front steering and
           direct yaw moment control systems with uncertainty observer
    • Authors: Jiaxu Zhang, Shiying Zhou, Fengjun Li, Jian Zhao
      First page: 3267
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an integrated nonlinear robust adaptive controller with uncertainty observer for active front wheel steering system and direct yaw moment control system. First, an integrated vehicle chassis control model is established as the nominal model with the additive and multiplicative uncertainties of the system. Secondly, an integrated nonlinear robust adaptive control law with the additive uncertainty observer is designed via Lyapunov stability theory to calculate the corrective yaw moment, and an adaptive law is designed based on projection correction method to online estimate and compensate the multiplicative uncertainty of the system. Then, the constrained optimal allocation problem of the corrective yaw moment is transformed into the nonlinear optimization problem, and the sequential quadratic programming method is used to solve the nonlinear optimization problem to coordinate active front wheel steering system and direct yaw moment control system. Finally, the performance of the proposed integrated nonlinear robust adaptive controller is verified via vehicle dynamics simulation software.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-08-31T07:52:10Z
      DOI: 10.1177/0142331220949718
       
  • Model order reduction based on discrete-time Laguerre functions for
           discrete linear periodic time-varying systems
    • Authors: Li-Li Sun, Kang-Li Xu, Yao-Lin Jiang
      First page: 3281
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Many engineering problems can be modelled as linear periodic time-varying (LPTV) systems, which naturally leads to the need for model order reduction of LPTV systems. This paper investigates a new model order reduction method for discrete LPTV systems. First, the state-space realization in the Fourier-lifted form of discrete LPTV system is constructed by representing periodic matrices in exponentially modulated periodic (EMP) Fourier series. By using Laguerre functions to expand the transfer function of the resulting Fourier-lifted system, the corresponding model order reduction algorithm is developed. Furthermore, the proposed algorithm is used to reduce the discrete LPTV system in the standard-lifted form. Theoretical analysis indicates that the transfer functions of both reduced order systems can match a certain number of moments. Finally, two numerical examples are given to verify the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-04T07:31:31Z
      DOI: 10.1177/0142331220949733
       
  • Stabilization method for the Saint-Venant equations by boundary control
    • Authors: Hassen Arfaoui
      First page: 3290
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, we are interested in the stabilization of the flow modeled by the Saint-Venant equations. We have solved two problems in this study. The first, we have proved that the operator associated to the Saint-Venant system has a finite number of unstable eigenvalues. Consequently, the system is not exponentially stable on the space [math], but is exponentially stable on a subspace of the space [math], ([math] is a given domain). The second problem, if the advection is dominant, the natural stabilization is very slow. To solve these problems, we have used an extension method due to Russel (1974) and Fursikov (2002). Thanks to this method, we have determined a boundary Dirichlet control able to accelerate the stabilization of the flow. Also, the boundary Dirichlet control is able to kill all the unstable eigenvalues to get an exponentially stable solution on the space [math]. Then, we extend this method to the finite difference equations analog of the continuous Saint-Venant equations. Also, in this case, we obtained similar results of stabilization. A finite difference scheme is used to compute the control and several numerical experiments are performed to illustrate the efficiency of the control.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-04T07:33:11Z
      DOI: 10.1177/0142331220950033
       
  • Predictor-based fractional disturbance rejection control for LTI
           fractional-order systems with input delay
    • Authors: Sajad Pourali, Hamed Mojallali
      First page: 3303
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a predictor-based fractional disturbance rejection control (PFDRC) scheme is proposed for processes subject to input delay. The proposed scheme can be generally applied to open-loop stable, integrative, and unstable integer-order processes, but it can be particularly utilized for open-loop stable fractional-order systems. A closed-loop reference model is formulated based on Bode’s ideal transfer function. The primary control design objective is to enable the output of input-delay process to follow the closed-loop reference model. Towards this end, the closed-loop transfer function of the PFDRC must take the same structure as that of the reference model. Meanwhile, the adverse effects of the input delay must be mitigated. To meet the latter, a filtered Smith predictor (FSP) is employed to provide a prediction of delay-less output response. To address the former, process dynamics are treated as a common disturbance; then, a fractional-order extended state observer (FESO) is introduced to estimate the delay-less output response and also the total disturbance (i.e. external disturbance and system uncertainties). The PFDRC feedback controller is easily derived by the gain crossover frequency of Bode’s ideal transfer function which facilitates the tuning process. The convergence analysis of the FESO is carried out in terms of BIBO stability. The effectiveness of the proposed control scheme is verified through three illustrative examples from the literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-09-02T12:38:00Z
      DOI: 10.1177/0142331220951407
       
 
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