Subjects -> INSTRUMENTS (Total: 63 journals)
Showing 1 - 16 of 16 Journals sorted alphabetically
Applied Mechanics Reviews     Full-text available via subscription   (Followers: 27)
Computational Visual Media     Open Access   (Followers: 5)
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: 18)
Experimental Astronomy     Hybrid Journal   (Followers: 39)
Flow Measurement and Instrumentation     Hybrid Journal   (Followers: 15)
Geoscientific Instrumentation, Methods and Data Systems     Open Access   (Followers: 2)
Geoscientific Instrumentation, Methods and Data Systems Discussions     Open Access   (Followers: 1)
IEEE Journal on Miniaturization for Air and Space Systems     Hybrid Journal   (Followers: 3)
IEEE Sensors Journal     Hybrid Journal   (Followers: 111)
IEEE Sensors Letters     Hybrid Journal   (Followers: 4)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Imaging & Microscopy     Hybrid Journal   (Followers: 7)
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: 8)
International Journal of Instrumentation Science     Open Access   (Followers: 41)
International Journal of Measurement Technologies and Instrumentation Engineering     Full-text available via subscription   (Followers: 1)
International Journal of Metrology and Quality Engineering     Full-text available via subscription   (Followers: 6)
International Journal of Remote Sensing     Hybrid Journal   (Followers: 151)
International Journal of Remote Sensing Applications     Open Access   (Followers: 49)
International Journal of Sensor Networks     Hybrid Journal   (Followers: 2)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Invention Disclosure     Open Access   (Followers: 1)
Journal of Astronomical Instrumentation     Open Access   (Followers: 4)
Journal of Instrumentation     Hybrid Journal   (Followers: 31)
Journal of Instrumentation Technology & Innovations     Full-text available via subscription   (Followers: 2)
Journal of Medical Devices     Full-text available via subscription   (Followers: 4)
Journal of Medical Signals and Sensors     Open Access   (Followers: 1)
Journal of Optical Technology     Full-text available via subscription   (Followers: 4)
Journal of Research of NIST     Open Access   (Followers: 1)
Journal of Sensors and Sensor Systems     Open Access   (Followers: 12)
Journal of Vacuum Science & Technology B     Hybrid Journal   (Followers: 1)
Jurnal Informatika Upgris     Open Access  
Measurement : Sensors     Open Access   (Followers: 5)
Measurement and Control     Open Access   (Followers: 36)
Measurement Instruments for the Social Sciences     Open Access  
Measurement Techniques     Hybrid Journal   (Followers: 3)
Medical Devices & Sensors     Hybrid Journal   (Followers: 1)
Metrology and Instruments / Метрологія та прилади     Open Access  
Metrology and Measurement Systems     Open Access   (Followers: 8)
Microscopy     Hybrid Journal   (Followers: 7)
Modern Instrumentation     Open Access   (Followers: 57)
Optoelectronics, Instrumentation and Data Processing     Hybrid Journal   (Followers: 5)
PFG : Journal of Photogrammetry, Remote Sensing and Geoinformation Science     Hybrid Journal   (Followers: 5)
Photogrammetric Engineering & Remote Sensing     Full-text available via subscription   (Followers: 33)
Remote Sensing     Open Access   (Followers: 57)
Remote Sensing Applications : Society and Environment     Full-text available via subscription   (Followers: 9)
Remote Sensing of Environment     Hybrid Journal   (Followers: 96)
Remote Sensing Science     Open Access   (Followers: 30)
Review of Scientific Instruments     Hybrid Journal   (Followers: 20)
Science of Remote Sensing     Open Access   (Followers: 7)
Sensors International     Open Access   (Followers: 3)
Solid State Nuclear Magnetic Resonance     Hybrid Journal   (Followers: 3)
Standards     Open Access  
Transactions of the Institute of Measurement and Control     Hybrid Journal   (Followers: 12)
Videoscopy     Full-text available via subscription   (Followers: 9)
Труды СПИИРАН     Open Access  
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Transactions of the Institute of Measurement and Control
Journal Prestige (SJR): 0.41
Citation Impact (citeScore): 1
Number of Followers: 12  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0142-3312 - ISSN (Online) 1477-0369
Published by Sage Publications Homepage  [1174 journals]
  • Feature extraction and fault detection scheme via improved locality
           preserving projection and SVDD

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      Authors: Muhammad Zohaib Hassan Shah, Zahoor Ahmed, Lisheng Hu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Manifold learning is widely adopted for the fault detection of industrial processes. However, the quality of low-dimensional embedding coordinates can be adversely affected by ill-constructed graph Laplacian. An improved locality preserving projection (ILPP) scheme is proposed. ILPP is built on a geometrically inspired Laplacian, and the Riemannian metric is used to find the suitable bandwidth parameter. The proposed approach combines the advantages of ILPP in preserving manifold data structures and those of support vector data description (SVDD) in handling complex process data distributions. Case studies on helix data, hot strip mill, and Pensim benchmark processes demonstrate the utility and feasibility of the proposed approach. The average fault detection rate for proposed ILPP is 99%, which is higher than locality preserving projection (LPP; 87.8%), local tangent space alignment (LTSA; 74.9%), and principal component analysis (PCA; 90.6%).
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-13T10:30:23Z
      DOI: 10.1177/01423312221099855
       
  • Finite-time sliding mode control of underwater vehicles in 3D space

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      Authors: Ali Keymasi Khalaji, Shahab Bahrami
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, trajectory tracking control of an underwater vehicle in three-dimensional (3D) space has been addressed. The assumed underwater vehicle has 6 degrees of freedom and the aim is to control all system rotations and displacements. In this paper, a finite-time sliding mode controller as a robust control method is proposed for an underwater vehicle with 6 degrees of freedom in 3D space using the method without simplifications or decouplings. Therefore, both system positions and orientations are controlled in the presence of disturbances and uncertainties. In previous research works, control of two-dimensional underwater vehicles is commonly studied. In this paper, a novel stable control algorithm is proposed for an underwater vehicle with 6 degrees of freedom. The stability of the closed-loop system is analyzed using the Lyapunov theory. The designed algorithm can cover 3D complicated tasks. Also, the designed algorithm as a robust control approach can attenuate external disturbances. The performance and stability of this approach are compared with the sliding mode controller. The numerical comparison results show that the proposed approach is effective and applicable in practice.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-13T10:25:42Z
      DOI: 10.1177/01423312221099354
       
  • Fixed-time leader-following synchronization in delayed network via
           non-chattering nonlinear control

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      Authors: Zongying Li, Xu Xu, Tingruo Yan, Eric Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The fixed-time leader-following synchronization in a non-identical delayed network via non-chattering nonlinear control is investigated. By introducing a function of control error, a continuous and differential controller is constructed without using the sign function and absolution of the error. The sufficient conditions are then established to guarantee that synchronization errors converge exactly to zero within a fixed time interval. The proposed approach provides a high convergence for the network accurately tracking the trajectory of the leader. More importantly, a tighter bound for the settling time is obtained and the chattering effects are eliminated. The numerical simulations are conducted to illustrate the effectiveness of theoretical analysis.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-10T12:21:58Z
      DOI: 10.1177/01423312221099357
       
  • Relaxed stability analysis and sampled-data controller design for
           networked control systems with network-induced delays

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      Authors: Mohamed Rouamel, Fayçal Bourahala, Kevin Guelton
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is devoted to the stability analysis and sampled-data controller design problem for networked control systems subject to network-induced delays. The objective is to provide relaxed conditions in terms of linear matrix inequalities. Indeed, reducing the conservatism of such conditions allows to maximize the admissible range of the network-induced delays. To do so, an augmented Lyapunov–Krasovskii functional is proposed, which involves a novel augmented state vector to include as much as possible the information from the time-varying network-induced delay into the stability conditions, together with the use of extended Wirtinger-based inequalities, an extended reciprocal convexity approach and the Finsler’s lemma. Then, declined from the proposed stability conditions, new relaxed delay-dependent conditions for the design of networked sampled-data controllers are proposed. These allow to obtain simultaneously the controller gains and the maximal allowable bound of the network-induced delays with regards to its lower bound. Three illustrative examples are provided to show the effectiveness of the proposed networked control systems stability and controller design conditions, as well as to highlight the so raised conservatism improvements regarding the previous relevant results from the literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-10T12:19:20Z
      DOI: 10.1177/01423312221097796
       
  • Fault-tolerant adaptive PID switched control of robot manipulator based on
           average dwell time

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      Authors: Juan Wang, Qiang Wei, Liangliang Sun, Zhigang Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The multi-mode tracking control of robot manipulators with unknown dynamics is investigated in this paper. In view of varying loads, robot manipulators are modeled as multi-mode switched systems. Adaptive PID (proportion–integration–differentiation)–like switched controllers are designed via the error transformation and multiple Lyapunov function method, which can make the error system practical stability within prescribed time under a class of switching signals satisfying average dwell time. Furthermore, two cases under the healthy actuator and faulty actuator are discussed. For the case of the partial failure of the actuator, the fault-tolerant adaptive PID-like controller is presented, which consists of two parts. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-08T11:02:05Z
      DOI: 10.1177/01423312221099714
       
  • L1 impedance control for bilateral teleoperation containing model
           uncertainty

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      Authors: Behnam Yazdankhoo, Mohammad Reza Ha’iri Yazdi, Farshid Najafi, Borhan Beigzadeh
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Restricting transient peaks of contact force in teleoperation systems is undeniably vital, specially in critical applications such as telesurgery. This issue, however, has still remained unsolved in the literature. In order to address this problem, we propose an impedance control scheme using optimal L1 theory for teleoperation systems encompassing asymmetric randomly time-varying delays and model uncertainties. To this end, an L1-based state-feedback compensator is designed employing linear matrix inequalities, aiming at minimizing the desired impedance error subjected to human force as exogenous disturbance. A simulation is ultimately conducted in comparison with the sliding-mode-based impedance controller. The results validate that the proposed controller is able to keep the integral of impedance error within the desired bound and, thus, improves the transient response. This is, however, at the expense of imposing a steady-state error for the integral of impedance error, which is normally made zero by the sliding-mode controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-08T10:57:24Z
      DOI: 10.1177/01423312221099382
       
  • Adaptive sliding mode-based active disturbance rejection control for a
           quadcopter

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      Authors: Suhail Ahmad Suhail, Mohammad Abid Bazaz, Shoeb Hussain
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an adaptive sliding mode-based active disturbance rejection control (ASM-ADRC) strategy for the altitude and attitude control of an unmanned quadcopter with disturbances. The quadcopter is an underactuated system subject to parametric perturbations, nonlinearity, unmodeled dynamics, strong coupling, and external disturbances. The proposed algorithm is based on the quadcopter’s dynamic model, where the effects of noise and wind are considered additive disturbances. The central concept is to combine the advantages of adaptive sliding mode control (SMC) to accurately track the reference trajectory with the ability of ADRC to reject the parameter uncertainties and external disturbances. The proposed control scheme is verified in simulation studies with sensor noise and external disturbances. The simulation results show that the proposed algorithm can significantly reduce the chattering phenomenon, owing to the estimation capability of the extended state observer (ESO). The proposed method also improves the robustness against modeling errors and disturbances and smoothly tracks the reference trajectory.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-08T10:54:17Z
      DOI: 10.1177/01423312221099366
       
  • Design of Begian–Melek–Mendel structure-based interval type-2 fuzzy
           logic systems optimized with backpropagation algorithms

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      Authors: Yang Chen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      As an emerging technology, the efficient and energy conserving process of permanent magnetic drive (PMD) presents high uncertainties. This paper designs a type of Begian–Melek–Mendel (BMM) structure interval type-2 fuzzy logic systems (IT2 FLSs) for PMD process uncertain parameters forecasting. The antecedent, consequent, and input measurements of systems are all selected as the Gaussian type-2 primary membership functions with uncertain standard deviations. Then the backpropagation algorithms are used to tune the parameters of IT2 FLSs. According to the Monte Carlo simulation studies and convergence analysis, the proposed IT2 FLSs are proved to be superior to two corresponding T1 FLSs in generalization ability.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-08T06:36:40Z
      DOI: 10.1177/01423312221099700
       
  • Federated strong tracking filtering for nonlinear systems with multiple
           sensors

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      Authors: Shiyang Liu, Ming Gao, Wuxiang Huai, Li Sheng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the filtering problem is investigated for nonlinear systems with multiple sensors. A federated strong tracking filter is designed to track state mutations by making full use of limited sensor information. Several subsystems are composed of different sensor combinations, and their states are independently estimated by using local filters in parallel. The strong tracking filter, as local filters, adaptively adjusts gain matrices of filters by introducing fading factors to track state mutations timely. Based on the theory of boundedness and inequality technique, the fusion estimation error is proved to be exponentially bounded in mean square. Finally, the feasibility and effectiveness of the proposed method is demonstrated by an experiment concerning the rotary steering drilling tool system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-06T08:10:32Z
      DOI: 10.1177/01423312221099706
       
  • Bipartite containment control of multi-agent systems with multiple leader
           groups

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      Authors: Yanhua Yang, Wenfeng Hu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article mainly considers the bipartite containment control problem of multi-agent systems with first- and second-order dynamics, where the antagonistic networks and multiple leader groups are considered. Specially, under the antagonistic networks, the multiple leader groups constitute two opposite convex hulls. One is a real convex hull composed of the real leader groups and the other is a virtual convex hull composed of opposite virtual leaders. For the first-order multi-agent systems with multiple leader groups, the followers move into the stationary real or virtual convex hull. While for the second-order multi-agent systems, the followers finally move into the dynamic real or virtual convex hull. In both cases, we obtain the sufficient conditions on achieving bipartite containment control. In the end, the effectiveness is verified by some simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-04T08:19:02Z
      DOI: 10.1177/01423312221099708
       
  • Simultaneous tuning of cascade controllers based on nonlinear optimization

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      Authors: Diego S Torga, Moisés T da Silva, Lucas A Reis, Thiago AM Euzébio
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Cascade control is widely used in the process industry, especially to reject disturbances. Typically, the controller parameters in the inner and outer loops of the cascade controller structure are defined in a strict sequence. In this paper, simultaneous tuning of cascade controllers is proposed to improve the performance of the system under load disturbance. For this purpose, the cost function of a nonlinear optimization problem is formulated to minimize the effect of disturbances on the system output. In addition, robustness constraints are defined for the maximum sensitivity function to independently guarantee a robust system for inner and outer loops. In this sense, the designer can explicitly and independently address the trade-off between performance and robustness for both loops. Simulation studies illustrate the performance and effectiveness of the proposed controller design method compared to well-known methods in the literature. These results indicate that the proposed method reduces the integrated absolute error (IAE) under load disturbance by up to [math]. In addition, experimental results from a tank-level control application in the mineral process industry illustrate the practical applicability of the proposed method. In this case, the proposed method reduces the IAE under load disturbance by [math].
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-04T08:14:47Z
      DOI: 10.1177/01423312221099376
       
  • Neural network–based adaptive fractional-order terminal sliding mode
           control

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      Authors: Shixi Hou, Cheng Wang, Yundi Chu, Juntao Fei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes an adaptive fractional-order (FO) terminal sliding mode control (TSMC) scheme to the robust current control of active power filter (APF) using a recurrent meta-cognitive fuzzy neural network (RMCFNN). An FO TSMC is developed by considering that the parametric perturbations and the external disturbances of APF are bounded. Compared with conventional TSMC approach, the proposed scheme, with an FO sliding surface, can obtain enhanced finite-time high-precision tracking performance due to another degree of freedom. Then, a novel observer-based FO TSMC is derived to achieve an absorbing model-free feature arising from RMCFNN. To improve the capabilities in managing the uncertainties, the specific online updating schemes for the structure and parameters of RMCFNN are designed. Meanwhile, closed-loop stability and finite-time convergence characteristic can be achieved using Lyapunov theory. Finally, simulation and experimental results indicate that the proposed observer-based FO TSMC can be easily implemented by microcontroller and has superior control performance compared with other existing schemes.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-04T08:11:01Z
      DOI: 10.1177/01423312221098486
       
  • A novel robust output-based control approach via adaptive event-triggered
           scheme

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      Authors: Atefeh Behnia, Mohammad Hossein Shafiei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a new robust output-feedback adaptive event-triggered control (AETC) method for linear systems with parametric uncertainties. The proposed event-triggered mechanism (ETM) is obtained based on the [math] stability condition. In this paper, two design approaches are presented, the emulation approach (pre-designed control gain) and the co-design approach. In the latter, the event-triggering law and the output-feedback controller are designed simultaneously to have a more efficient control system. The proposed adaptive event-triggered mechanism (AETM) in both approaches leads to an increase in the average of inter-event times based on linear matrix inequalities (LMIs). Consequently, in the proposed methods, the stability of the event-based system is ensured, the Zeno phenomenon is avoided, the feasibility margin and the quality of the response are well maintained, and the number of samplings is reduced, considerably. Finally, to indicate the capability of the proposed methods, two numerical simulations are presented.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-02T10:57:57Z
      DOI: 10.1177/01423312221098736
       
  • Integration sliding mode control for vehicle yaw and rollover stability
           based on nonlinear observation

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      Authors: Chuanbin Sun, Zhangbao Xu, Shuchao Deng, Baohong Tong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An active rear steering and direct yaw moment (ARS-DYC) coordination control is conducted on the basis of nonlinear fuzzy observation to improve yaw and roll stability control of vehicles under extreme conditions. First, a Takagi–Sugeno (T-S) model of yaw and roll motion is established, and tire nonlinearity at emergency steering is approximated with sector domain. A nonlinear fuzzy observation model is established on the basis of the extended Kalman filter (EKF) to observe the sideslip angle, yaw rate, and roll state accurately under extreme conditions in real time. Second, an improved ideal yaw reference model under the T-S framework is constructed in accordance with the effect of yaw rate on roll stability, and the feedforward control of roll stability is achieved through yaw motion tracking. A fuzzy sliding mode controller is designed on the basis of nonlinear fuzzy observation considering tire sideslip stiffness and actuator constraints, and the coordinated control strategy of layered sliding mode surface for yaw and roll is constructed. Finally, the parameters of sub-sliding mode surface are adjusted with the 4-wire phase plane stability domain, the main sliding mode surface parameters are adjusted following the roll stability index, and the stability of the fuzzy sliding mode controller is proven in the Lyapunov framework. A hardware-in-loop simulation test is established with Carsim-Labview software, and results show that the proposed controller significantly enhances the yaw and roll stability of vehicles under the extreme steering process, due to the accuracy of nonlinear dynamic observation and the flexibility of layered sliding surface coordinated control.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-02T07:25:57Z
      DOI: 10.1177/01423312221099414
       
  • Improved model-free fractional-order intelligent proportional–integral
           fractional-order sliding mode control with anti-windup compensator

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      Authors: Aghiles Ardjal, Maamar Bettayeb, Rachid Mansouri
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In addition to the difficulty of system modeling, every physical system faces actuator saturation, making the real control different from the controller output (desired control input). When this occurs, the controller output does not regulate the system properly and errors occur as a result of incorrect updating. This is known as the windup phenomenon. In the event that the controller is configured to override actuator saturation, it can lead to a failure in the controller’s performance, such as large overshoots, high response time, and even system instability in the worst case. Therefore, in this paper, a new robust model-free controller method is proposed. It is a combination of four nonlinear control techniques, namely model-free controller, fractional-order sliding mode controller, fractional integral–proportional (PI) controller, and anti-windup compensator, which gives rise to the new model-free controller algorithm called hybrid fractional-order intelligent PI fractional sliding mode controller with an anti-windup compensator termed (MF-FOiPI-FOSMC-AW). However, to illustrate the effectiveness of the new proposed MF-FOiPI-FOSMC-AW method, simulation and experimental results compared to classical PI and iPI controllers (with and without an anti-windup compensator) on a hydraulic system are presented in the presence or absence of external disturbances for different types of references. Finally, simulation is conducted through an experimental comparison of the proposed approach with other strategies such as the classical anti-windup PI controller and the anti-windup intelligent PI controller, which is carried out for this purpose.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-02T07:24:09Z
      DOI: 10.1177/01423312221099302
       
  • Iterative learning control of fractional-order linear systems with
           nonuniform pass lengths

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      Authors: Yang Zhao, Yan Li, Fangfang Zhang, Haiying Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Most previous studies about fractional-order iterative learning control (FOILC) assume fixed pass lengths in iteration domain and identical initial condition. These fundamental preconditions may be violated in practical applications. This paper introduces a novel FOILC strategy for tracking control of fractional-order linear systems. To relax the fixed pass lengths assumption, redefined tracking error is applied to formulate control input. Meanwhile, an initial state learning algorithm is introduced to relax the identical initial condition assumption. Strict convergence analysis of the tracking error in iteration domain is given. Finally, two illustrative simulation examples are applied to verify the efficiency and applicability of the proposed algorithm.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-02T07:21:41Z
      DOI: 10.1177/01423312221097736
       
  • Data-driven adaptive tuning of iterative learning control

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      Authors: Yingzhen Yu, Na Lin, Ronghu Chi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, we propose two data-driven adaptive tuning (DDAT) approaches of iterative learning control (ILC) for nonlinear non-affine systems. First, a compact-form iterative dynamic linearization (CFIDL) method is introduced to transfer the original nonlinear system into a linear data model. Then, we design an objective function for the tuning of the learning gains of a PD-type ILC law. By optimizing the designed cost function subjected to the linear data model, a CFIDL-based DDAT method is proposed, where only the real I/O data are used without requiring any mechanistic model information. Furthermore, the results are extended by introducing a partial-form iterative dynamic linearization (PFIDL) method for the purpose of utilizing more additional control information. Following the similar steps, a PFIDL-based DDAT method is developed for learning gain tuning of the PD-type ILC scheme. Both the proposed DDAT methods can help the PD-type ILC have a better robustness against to the uncertainties since they can use the real I/O data to iteratively tune the learning gains. The convergence of the DDAT-based PD-type ILC methods has been proved rigorously. The effectiveness of the two proposed DDAT-based ILC methods are further verified through simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-01T09:11:42Z
      DOI: 10.1177/01423312221099381
       
  • Dynamic sliding mode control of pitch blade wind turbine using sliding
           mode observer

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      Authors: Ali Karami-Mollaee, Ali Asghar Shojaei, Oscar Barambones, Mohd Fauzi Othman
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In a wind turbine (WT), the maximum power can be achieved using a suitable and smooth signal, which should be applied to the pitch angle of the blades (PABLE). On the contrary, the uncertainties of the WT models cause the fatigue due to the mechanical stresses. To overcome these two problems, dynamic sliding mode control (D-SMC) is used because it is robust against uncertainties and can suppress the chattering by providing smooth signals. In D-SMC, an integrator is located before the actuator, as a low-pass filter, to suppress the high-frequency chattering. Then, the states number of the overall augmented system is one more than the states number of the actual system. To control such an augmented system, the added state variable needs to be estimated and hence, a novel sliding mode observer (SMO) is proposed. A trusty comparison is also presented using the conventional sliding mode control (C-SMC) with the proposed SMO. To implement D-SMC and C-SMC, a new state feedback is applied to the turbine at first. Therefore, a linear model with uncertainty is obtained, where its input is the PABLE. Lyapunov theory is used to proof the stability of the proposed SMO, D-SMC, and also the C-SMC. The presented comparison demonstrates the advantages of the D-SMC with respect to the C-SMC in removing the chattering and simplicity in concept and in implementation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-01T09:07:59Z
      DOI: 10.1177/01423312221099304
       
  • Delay-dependent H∞ dynamic observers for non-linear systems with
           multiple time-varying delays

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      Authors: Ghali Naami, Mohamed Ouahi, Belamfedel Alaoui Sadek, Fernando Tadeo, Abdelhamid Rabhi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The design of dynamic [math] observers (DO) for non-linear Lipschitz systems with multiple time-varying delays and disturbances is studied. Sufficient conditions for the existence of these observers are presented in the form of rank equality. Compared to previously published work, the system under consideration includes non-linearity, non-commensurable delay, and external disturbance. Through the use of the Wirtinger inequality and the extended reciprocally convex matrix inequality, new and less conservative delay-dependent conditions in terms of linear matrix inequalities (LMIs) are derived based on the Lyapunov–Krasovskii functional method. Solving these LMIs makes it possible to obtain DO that satisfies an [math] performance index. Through two numerical examples in which the comparison with the proportional observer (PO) and the proportional–integral observer (PIO) shows the efficiency of the proposed DO synthesis condition. Furthermore, the results indicate that the DO developed in this paper is more resilient to parameter perturbations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-27T10:05:56Z
      DOI: 10.1177/01423312221093169
       
  • Pth moment input-to-state stability of impulsive stochastic functional
           differential systems with Markovian switching

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      Authors: Fang Huang, Jianli Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The paper introduces a unified criterion for pth moment input-to-state stability (p-ISS), pth moment integral input-to-state stability (p-iISS), and eσt-weighted pth moment integral input-to-state stability (eσt-p-ISS) of impulsive stochastic function differential system with Markovian switching under the perturbation of the stabilizing impulse and destabilizing impulse. The Lyapunov function approach, comparison principle, and impulsive average dwell-time method are applied in this paper. The linear coefficients of the upper bound of Lyapunov functional differential operators are time-varying functions, including the case of constants, which advances and improves the existing results. In addition, the same results were obtained by applying impulse differential inequality. At the end of this paper, we use a numerical example to verify the validity of the results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-25T12:27:33Z
      DOI: 10.1177/01423312221095736
       
  • Friction-free approach for a servo system: Design of a robust sliding-mode
           control based on a recurrent fuzzy neural network

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      Authors: Ha Quang Thinh Ngo, Hung Nguyen, Thanh Phuong Nguyen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Uncertainties such as disturbance and nonlinear friction always exist in physical motion control systems and degrade the precision of their tracking performance. In this research, a practical control strategy is integrated with a continuously differentiable friction model for a high-performance AC servo motor that performs with a continuous control input and is, hence, more properly suited for industrial applications. To further lessen the external disturbance and improve the tracking accuracy, a recurrent fuzzy neural network scheme was developed to approximate the system uncertainties, and its stability was guaranteed by the design of robust laws. The proposed controller was implemented on a high-performance digital signal processor (TMS320C6727). The results of the tracking simulations and experiments show that the proposed control scheme has a feasible and effective design for engineering servo system. In comparison with other algorithms, our approach has smaller values for both the peak and the root mean square of the tracking error while maintaining friction compensation, and it can potentially have a software implementation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-25T05:41:52Z
      DOI: 10.1177/01423312221097738
       
  • Consensus error analysis for linear continuous-time multi-agent systems
           with additive noises

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      Authors: Huifang Sun, Xiaowen Wang, Shuai Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the distributed consensus problem for linear continuous-time multi-agent systems subject to additive process noises. Due to the existence of noises, the asymptotic consensus cannot be achieved. Hence, a distributed consensus protocol is proposed such that all the agents can achieve consensus to some degree. Furthermore, based on Lyapunov theory, we characterize the consensus error under undirected and directed topologies. Numerical examples are presented to verify the effectiveness of two results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-21T10:15:23Z
      DOI: 10.1177/01423312221096919
       
  • Adaptive control for full-states constrained nonlinear systems with
           unknown control direction using Barrier Lyapunov Functionals

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      Authors: Dao-gen Jiang, Wei Jiang, Xiao-dong Zhu, Xiang-yuan Yin
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a new adaptive back-stepping (BS) control technique based on barrier Lyapunov functions (BLFs) is proposed to manage a class of full-state constrained nonlinear systems subject to totally unknown directions and uncertain time-varying parameters. BLFs guarantee that all the system states are constrained in a predefined compact set and the tracking error can converge to a small zero neighborhood. Nussbaum’s gain technique is utilized to tackle the unknown control direction issue. Besides, a sufficiently smooth projection algorithm is adopted to estimate the unknown time-varying parameters, so as to ensure that the adaption laws are differentiable and bounded. The developed controller not only makes all the system states restrained in the compact set but also assures the smoothness and boundedness of all the signals of the closed-loop system. In addition, the sufficiently smooth projection algorithm and Nussbaum gain technique are combined with the BLF-BS control method for the nonlinear systems. Finally, the simulation example results verify the effectiveness and feasibility of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-21T10:13:02Z
      DOI: 10.1177/01423312221093826
       
  • Consensus based on output for nonlinear multi-agent systems with switching
           topologies

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      Authors: Haixiang Zhang, Chong Chen, Jun Huang, Yueyuan Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article addresses the consensus problem based on static output feedback for a kind of leader-following multi-agent systems. Traditional nonlinear constraints, such as Lipschitz and one-sided Lipschitz, cannot describe most nonlinear functions. The incremental quadratic constraints and switching topologies are considered to extend the application range and practical significance of the existing consensus control protocol. By investigating the topology having a directed spanning tree and constructing a proper Lyapunov function, this article gives sufficient conditions for the consensus problem, including the dwell time by a threshold value. Then, a design method for the static output feedback gain matrix is deduced and an algorithm for achieving consensus is presented. Finally, two simulation examples are used to verify the validity as well as the superiority of the designed protocol. It is the first piece of work to study the consensus problem of multi-agent with incremental quadratic constraints under switching topologies.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-12T10:57:27Z
      DOI: 10.1177/01423312221096683
       
  • Soft sensor of iron tailings grade based on froth image features for
           reverse flotation

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      Authors: Dingsen Zhang, Xianwen Gao, Wenhai Qi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In the iron reverse flotation production process, the amount of flotation agent and the quality of flotation products are usually judged according to the grade of tailings, so it is essential to measure the grade of tailings froth. This research applies computer vision and image feature extraction technology to the soft sensor of tailings froth grade. An adaptive selection method for the image target region is proposed. The relationship between RGB (Red, Green, Blue), HSI (Hue, Saturation, Intensity), and Lab color space and tailings grade of reverse flotation in iron mine has been analyzed. A new image feature is proposed to characterize the degree of froth mineralization. The RGB and HSI dual color space feature values and froth mineralization degree values are determined as input, and the tailing grade soft sensor model is established by the multilayer feedforward perceptrons and VGG-19 neural network. A tailings grade soft sensor system has been developed and applied in a flotation workshop. The results of industrial tests show that this method is efficient and reliable.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-12T10:54:42Z
      DOI: 10.1177/01423312221096450
       
  • Proportional–integral–derivative stabilization of complex
           conjugate-order systems

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      Authors: Gulten Cetintas, Serdar Ethem Hamamci
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Proportional–integral–derivative (PID) stabilization is an important control design strategy that provides the designer with all PID controller set which results control system stability absolutely. In this way, the designer has a wide range of freedom to obtain the controller that meets the desired criteria. This process is particularly advantageous in situations where it is difficult to clearly define the design criteria at the beginning of the design or to make a balanced decision among the design criteria. The main objective of this paper is to present for the first time a PID stabilization method for complex conjugate-order systems, which is a new type of system for the control community and has been little studied on. The method is based on obtaining of stability/instability regions using the D-decomposition method in the controller parameter space graphically. These regions are formed by stability boundaries that are defined as real root, infinite root and complex root boundaries. The stability of the regions is determined using generalized modified Mikhailov stability criterion that is a powerful stability tool of the system theory. The simulation results indicate that the presented stabilization method is effective and practically useful in the analysis and control of the complex conjugate-order systems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-12T10:51:32Z
      DOI: 10.1177/01423312221095840
       
  • Research on belt foreign body detection method based on deep learning

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      Authors: Dong Xiao, Zhuang Kang, Hang Yu, Lushan Wan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Recently, accelerating the improvement in the level of iron ore mining has become extremely important for the sustainable development of the steel industry. Various foreign objects such as steel bars, wood, and plastic pipes easily appear on iron ore belt conveyors, which cause damage to equipment and harm the personal safety of mining workers. Accordingly, a lightweight detection model based on you only look once (YOLO)v3 is proposed in this study. This study first uses the median filter method to preprocess the belt foreign body image to remove the influence of dust and improve the clarity of ore edges. Second, we train the YOLOv3 belt foreign matter detection algorithm based on the selected data set to detect belt foreign matter and evaluate the model based on mean average precision (mAP) and other indicators. Finally, after implementing the sparse training based on the batch normalization (BN) layers, the channel-pruning and layer-pruning strategies are implemented to simplify the YOLOv3 model, followed by parameter fine-tuning. When the accuracy of the model is not affected, our model realizes smaller calculations, faster processing, and a smaller size compared to the original YOLOv3 model. Hence, the model effectively achieves real-time recognition of foreign matter on the ore conveyor belt.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-10T06:16:23Z
      DOI: 10.1177/01423312221094393
       
  • Constructing the real-world driving cycle for electric vehicle
           applications: A comparative study

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      Authors: Zeyu Chen, Zhiyuan Fang, Qing Zhang, Nan Zhou, Quanqing Yu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Construction of real-world driving cycle is of great significance for designing and assessing the energy management strategy of electric vehicles. In this study, five methods of driving cycle construction are investigated, namely, the random selection method, principal component analysis-based method, clustering analysis method, Markov chain-based method, and the optimization-based method. Urban driving conditions in Shenyang, China, are used as a case study to construct the driving cycles using the five methods, respectively. Based on the above efforts, an evaluation method of driving cycle effectiveness is proposed from the three perspectives, namely, accuracy, operability, and reproducibility. Characteristic parameters, speed–acceleration probability distribution, impact on energy control effect, dependence on data volume, and result repeatability are considered specifically. The assessing results of the common methods are proposed by making systematic comparisons. The results disclose the advantages and disadvantages of each method and obtain the ranking of five methods in three performance indexes. The presented results are expected to provide a theoretical basis and useful guidance for establishing real-world driving cycles in practical engineering applications.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-10T06:14:42Z
      DOI: 10.1177/01423312221094384
       
  • Survey on deep learning-based 3D object detection in autonomous driving

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      Authors: Zhenming Liang, Yingping Huang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Autonomous driving technology has entered into the fast lane of development in recent years. An essential component of autonomous driving technology is scene perception, especially 3D object detection. This work gives a comprehensive survey on the up-to-date deep learning-based approaches for 3D object detection in autonomous driving, and categorizes the existing detection models into three classes in terms of their input data format, including LiDAR point cloud-based, Camera RGB image-based, and LiDAR point cloud-camera image fusion-based 3D object detection methods. This work also discusses and analyzes these models according to their characteristics, basic frameworks, advantages and disadvantages, and exhibits the benchmark datasets which are commonly used in the research community. At last, this work summarizes the review work and provides a discussion on the practical challenges and future trend of the research domain.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-10T06:12:02Z
      DOI: 10.1177/01423312221093147
       
  • A robust intelligent controller-based motion control of a wheeled mobile
           robot

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      Authors: Reza Rouhi Ardeshiri, Meysam Gheisarnejad, Mohammad Reza Tavan, Navid Vafamand, Mohammad-Hassan Khooban
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an adaptive intelligent controller is developed for the velocity-tracking problem of a nonholonomic wheeled mobile robot (WMR) in the presence of external disturbances and measurement noises. The whole control system is consisting of two subsystems, where each subsystem has its own control responsibility. In this way, first, a kinematic controller is implemented according to the kinematic model of the robot, and then a dynamic controller is designed based on the characteristic of the robot dynamics. Our focus is designing and developing an adaptive fractional-order fuzzy logic proportional–integral–derivative (FOFPID) controller for the trajectory-tracking task in a two-WMR. Unlike the prevalent works which only designed the scaling factors of FOFPID, a simultaneous optimization of fuzzy membership functions and controller coefficients are realized to improve the efficiency of the WMR dynamic controller. Accordingly, the controller parameters are optimally adjusted by employing a combination of the sin cos algorithm and harmony search, called SCA-HS. To validate the applicability of the suggested framework, experimental studies are also conducted on a real-time platform using a two-WMR prototype. The experimental results confirm the effectiveness of the proposed controller for the exact trajectory-tracking problem in the presence of disturbances and noises.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-10T06:09:58Z
      DOI: 10.1177/01423312221088389
       
  • Robust feedback feed-forward PD-type iterative learning control for
           uncertain discrete systems over finite frequency ranges

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      Authors: Wei Zou, Yanxia Shen, Wojciech Paszke, Hongfeng Tao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a robust feedback feed-forward proportional-derivative type (PD-type) iterative learning control (ILC) scheme for a class of linear discrete systems with polytopic uncertainty over finite frequency ranges. First, the ILC process is transformed into an equivalent discrete linear repetitive process. Then, with the help of the generalized Kalman–Yakubovich–Popov lemma, the issue of a robust control law design algorithm in the process model is converted into the problem of solutions to the corresponding linear matrix inequality conditions. This procedure not only meets the robust performance specifications along the trial, but also guarantees the monotonic converge of the trial-to-trial error dynamics over finite frequency ranges. Finally, the simulations for a direct current servo motor system are adopted to show the effectiveness and superiority of the proposed method. Compared with previously established works, the new algorithm is more effective in delivering higher performance and achieving better tracking effect.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-10T06:07:24Z
      DOI: 10.1177/01423312221086363
       
  • Adaptive command-filtered finite-time control of non-strict feedback
           stochastic non-linear systems

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      Authors: Parisa Seifi, Seyed Kamal Hosseini Sani
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an adaptive neural network (NN) finite-time command filter controller for a class of non-strict feedback stochastic non-linear systems has been investigated. Using error compensation signals and NNs, a command filter controller is presented which guarantees that all the signals of the closed-loop system are practical finite-time stable and the output signal tracks the given reference signal under the bounded error. In the design procedure, NNs are employed to approximate unknown non-linear functions, which contain all the state variables of the whole system, in order to avoid excessive and burdensome computations and ensure that the backstepping method works normally for non-strict feedback systems. Meanwhile, the “explosion of complexity” problem caused by the backstepping method is avoided using the command filter approach. The control scheme not only resolves the “explosion of complexity” problem but also eliminates the filtering error in finite-time. Finally, the simulation results are given to prove the effectiveness of the proposed control method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-08T02:35:13Z
      DOI: 10.1177/01423312221093825
       
  • A soft-sensing method for product quality monitoring based on particle
           swarm optimization deep belief networks

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      Authors: Qi Li, Menghan Yang, Zhengyin Lu, Yu Zhang, Wei Ba
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A novel soft-sensing method for quality parameters of aviation kerosene in atmospheric distillation column based on least absolute shrinkage and selection operator and particle swarm optimization deep belief network (LASSO-PSO-DBN) is proposed. First, to reduce the dimension of the input variables, the least absolute shrinkage and selection operator (LASSO) algorithm is used to select the input variables that are irrelevant to the soft sensor of aviation kerosene quality parameters. Then, to improve the generalization of soft sensor model, a deep learning algorithm, deep belief network (DBN), is proposed for soft sensing of aviation kerosene quality parameters. Considering that the structure characteristics and parameters of DBN algorithm have a great impact on the learning and prediction results, the parameters of DBN are optimized based on particle swarm optimization (PSO) algorithm. The benchmark data sets and the industrial atmospheric distillation column data are used for simulation analysis and evaluation of the soft-sensing performance. The simulation results show that the novel proposed algorithm can effectively reduce the dimension of the input variables and simplify the structure of the soft sensor model. It also has good generalization ability and the predicted value is in good agreement with the actual measured value.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-08T02:32:50Z
      DOI: 10.1177/01423312221093166
       
  • Nonsingular fast terminal sliding mode control based on neural network
           with adaptive robust term for robotic manipulators with actuators

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      Authors: Ningyu Lu, Li Ma, Xiaoqing Hua
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      For accurate trajectory tracking of robotic manipulators with actuators, a novel nonsingular fast terminal sliding mode control (NFTSMC) strategy based on radial basis function neural network (RBFNN) is put forward and investigated in this paper. Because of the existence of nonsingular fast terminal sliding mode (NFTSM) manifold, the controller possesses high precision and fast convergence. Considering that it is difficult to obtain accurate model parameters owing to modeling errors or external disturbances, RBFNN is used to approximate the nonlinear uncertainties due to its simple structure and great generalization ability. A new adaptive law is designed to adjust RBFNN. In order to compensate the estimation errors and suppress other unstable factors, a robust term is introduced. A new adaptive law is developed to flexibly adjust the robust term. Then, Lyapunov theory is applied to prove the system stability and finite-time convergence. Finally, a small-sized industrial robotic manipulator Epson LS3-401S with its first two joints is taken as the simulation plant, and several simulations between the proposed controller and the other two controllers are performed. External disturbances and other two conditions are considered to simulate the real environment, and the corresponding results verify the effectiveness and superiority of the proposed controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-08T02:30:54Z
      DOI: 10.1177/01423312221093152
       
  • Nonlinear controller design for a fractional extended model of COVID-19
           outbreak using feedback linearization method

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      Authors: A Khoshdel, SJ Sadati Rostami, H Abbasi Nozari
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a novel fractional-order epidemic model for the COVID-19 outbreak using the Caputo derivative that incorporates various intervention policies to manage the spread of the disease. A total of eight state variables were considered in this nonlinear model, namely, susceptible, exposed, infected, quarantined, hospitalized, recovered, deceased, and insusceptible. Two possible outbreak scenarios were considered to control the disease before and after vaccine discovery. The proposed system was designed using the feedback linearization method, allowing to develop a suitable controller for reducing susceptible, exposed, and infected populations. A comparative study with previous work was conducted based on Canada’s reported cases to demonstrate the advantages and disadvantages of the proposed COVID-19 outbreak control strategy using this model. The simulation results confirmed that the proposed fractional controller could effectively track the desired goals, including an exponential decrease in infected, exposed, and susceptible populations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-05T11:24:26Z
      DOI: 10.1177/01423312221092523
       
  • Dynamic event-triggered tracking control for a class of p-normal switched
           stochastic nonlinear systems

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      Authors: Manman Yuan, Junyong Zhai, Hui Ye
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the event-triggered tracking issue for p-normal switched stochastic nonlinear systems. Unlike the existing event-triggered schemes, an event-triggering mechanism is proposed with a dynamic gain. Then, a new adaptive event-triggered controller (ETC) is designed via output feedback. The presented control scheme can render that all signals of the closed-loop system are bounded almost surely. Moreover, the Zeno phenomenon is excluded. Three examples are provided to verify the efficiency of the presented strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-05T11:18:00Z
      DOI: 10.1177/01423312221090734
       
  • Leakage detection method of natural gas pipeline combining improved
           variational mode decomposition and Lempel–Ziv complexity analysis

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      Authors: Lijuan Zhu, Dongmei Wang, Jikang Yue, Jingyi Lu, Gongfa Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      With the continuous development of pipeline transportation industry, pipeline leakage often occurs, posing a great threat to people’s lives and property safety. In order to improve the detection accuracy of natural gas pipeline leakage, a pipeline leakage detection method based on improved variational mode decomposition algorithm and Lempel–Ziv complexity analysis is proposed. In this work, the normalized mutual information is used to determine the decomposition level K of variational mode decomposition, and the Lempel–Ziv complexity analysis algorithm is used to extract pipeline signal feature. The results show that the proposed leakage detection method has higher classification accuracy than other methods, which verifies the effectiveness of this method in the process of pipeline leakage detection.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-02T08:06:43Z
      DOI: 10.1177/01423312221088080
       
  • Control and synchronization of chaotic spur gear system using adaptive
           non-singular fast terminal sliding mode controller

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      Authors: Mohammad Ali Labbaf Khaniki, Mohammad Salehi Kho, Mahdi Aliyari Shoorehdeli
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study reports a novel adaptive non-singular fast terminal sliding mode controller for the tracking control and synchronization of a chaotic spur gear system. The proposed novel control law attenuates the chattering phenomena of the conventional sliding mode controller. In addition, a non-singular fast terminal sliding mode surface is employed to remove the singularity problem, increase the convergence rate, and guarantee finite-time convergence. An extreme learning machine (ELM) neural network is utilized to estimate the unknown dynamics of the spur gear system and the reaching law coefficients; hence, this control scheme is a combination of the direct and indirect adaptive control. The adaptation rules of the ELM are derived based on the Lyapunov stability theorem to ensure closed-looped stability. Finally, some different numerical simulations are considered to check the validity and efficiency of the proposed control strategy compared with other control methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-02T08:03:21Z
      DOI: 10.1177/01423312221087578
       
  • Speed control of PMSM based on neural network model predictive control

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      Authors: Hubo Mao, Xiaoming Tang, Hao Tang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to optimize the control performance of permanent magnet synchronous motor (PMSM) servo system, an improved model predictive control (MPC) scheme based on neural network is investigated in this paper. First, the dynamic characteristics of the PMSM are approximated by echo state network (ESN) to predict the future speed. Particle swarm optimization (PSO) is used to train ESN output weights to solve the problem that instability of output weights caused by pseudo-inverse matrix in ESN weight solving algorithm, called PSO-ESN, which enhances the stability and the accuracy of ESN speed prediction. That provides future plant output for control optimization of the predictive control. Furthermore, in order to reduce the computational cost and improve the response performance of the controller, a fast gradient method (GM) is applied to minimize the quadratic performance index and solve the optimal control input sequences. The simulation results under three different working conditions show that the PSO-ESNMPC controller designed in this paper reduces the overshoot by 5.87% and the rise time by 0.036 s compared with the reference controllers and has better robustness under parameter changes and load disturbances.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-02T08:01:03Z
      DOI: 10.1177/01423312221086267
       
  • Input-observer event-based consensus in linear multi-agent systems

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      Authors: Mohammad Eslami, Hajar Atrianfar, Mohammad Bagher Menhaj
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper provides an input-observer event-based controller to solve consensus problems in multi-agent systems with general linear dynamics over fixed directed and undirected network topologies. A Lyapunov-based event condition is proposed to achieve consensus using neighbors’ output information. The proposed method is distributed in the sense that the event detectors only use neighbors’ information, and the controller updates its value by using intermittent communication. Finally, an example is provided to illustrate the effectiveness of theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-02T07:58:23Z
      DOI: 10.1177/01423312221083783
       
  • Distributed event-triggered for adaptive neural network containment
           control of uncertain Euler–Lagrange systems with external disturbances

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      Authors: Qiangde Wang, Yang Zhang, Chunling Wei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the containment control problem for multiple Euler–Lagrange systems with unknown time-varying disturbances over directed graphs, in which the dynamics of leaders and followers are heterogeneous. First of all, the expected output signals of leaders can only be acquired by some subsystems owing to the limited communication conditions, and the output adjustment errors are obtained indirectly by other subsystems through the network connection. In consequence, a compensator based on relative output information is designed to estimate a trajectory inside the convex hull spanned by states of the leaders. Second, a fully distributed event-triggered adaptive control scheme is proposed, and a disturbance estimator is designed to achieve interference suppression. In addition, the design of the overall control protocol does not use the relative speed of the followers. Finally, a dual-axis manipulator is taken as an example to validate the effectiveness of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-01T01:31:23Z
      DOI: 10.1177/01423312221088656
       
  • Detection of operating mode changes, without a priori model and in
           uncertain environments

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      Authors: José Ragot
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Starting from the general observation that a measurement delivered by a sensor is subject to an uncertainty, its use in a decision chain must take into account this imprecise character. It is thus advisable to propagate this imprecision in all the chain of treatment and use of the measurement in question. In what follows, this principle is applied to the diagnostic function, one of the components of system monitoring. More precisely, we propose to analyze the temporal data collected on a system in order to detect and locate possible changes in the behavior of this system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-27T11:55:15Z
      DOI: 10.1177/01423312221092527
       
  • A method for robust quadratic pole assignment

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      Authors: Manhong Lu, Huiqing Xie
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A new method is proposed for robust quadratic pole assignment problem. We first give the results on the solution of quadratic pole assignment problem. Then the Schur form corresponding to closed-loop system is established and normality departure is used to measure the robustness of closed-loop system. On these grounds, a method for robust quadratic pole assignment problem is proposed by minimizing the normality departure of closed-loop system. The proposed method avoids to transform the second-order control system to the first-order control system. Moreover, it is implemented in real operations. Numerical experiments show that our method has good performance on the robustness of closed-loop system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-19T05:36:52Z
      DOI: 10.1177/01423312221088651
       
  • Discrete-time integral sliding mode position control of H-type platform
           direct-drive servo system based on smooth saturation function

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      Authors: Xin Fang, Limei Wang, Kang Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The direct-drive servo system of H-type platform is easily affected by load disturbance and mechanical coupling. In this paper, a discrete-time integral sliding mode position control method based on smooth saturation function is proposed. First, the discrete-time mathematical model of direct-drive servo system with mechanical coupling characteristics is established with the position and speed of mover as state variables. Then, a discrete-time integral sliding mode position controller is designed to reduce the influence of external disturbance, and improve the tracking accuracy of the system. At the same time, in order to weaken the chattering caused by the sign function in the control law, a smooth saturation function is designed to replace the original sign function, and the advantages of the smooth saturation function are analyzed and proved. Finally, the simulation and experimental results show that the proposed method not only improves the position tracking accuracy of the system, weakens the chattering, but also enhances the robustness of the system to load disturbance.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-19T05:32:39Z
      DOI: 10.1177/01423312221088641
       
  • Robust and compliance control for robotic knee prosthesis using admittance
           model and sliding-mode controller

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      Authors: Yongshan Huang, Hongxu Ma, Quan He, Lin Lang, Honglei An
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Achieving compliance and flexibility under the premise of ensuring trajectory tracking performance and also reflecting the wearer’s movement intention, has not yet been well solved in the field of prosthesis. The aim of this paper is to provide a compliant, robust, and continuous control scheme for robotic knee prosthesis to solve the contradictory problems of trajectory tracking performance and compliance. The proposed scheme are based on the admittance model and radial basis function (RBF) neural network–enhanced nonsingular fast terminal sliding-mode controller (NFTSMC). The desired trajectory of the prosthetic knee joint is driven by humans and reshaped to reference trajectory by an admittance model, so that the prosthetic leg can reflect the human’s movement intention and being compliant. RBF neural network is introduced to achieve adaptive approximation of unknown models and ensure that the controller does not depend on the mathematical model of the “human-in-the-loop” prosthesis system. A novel NFTSMC was proposed to deal with the influence of ground reaction forces (GRFs) and fitting errors of the RBF neural network, which make the tracking error converge to zero in a finite time. The adaptive law of the RBF neural network is obtained by the Lyapunov method, and the stability and finite-time convergence of the closed-loop system are rigorously proved and analyzed mathematically. The simulation results prove the feasibility and effectiveness of the propose control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-19T05:32:33Z
      DOI: 10.1177/01423312221088848
       
  • Reference governed ADRC approach to manage the handling-comfort
           contradiction in a full-vehicle suspension

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      Authors: Alhelou Muhammed, Dayoub Yazan, Alexander Gavrilov
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper aims to add to the discourse surrounding the development of a new approach to managing the trade-off between the ride-comfort and road-handling experiences induced by car suspension systems. Indeed, at present, management of the handling-comfort contradictions in such a large system using traditional algorithms requires precise modeling and large calculations, for example, model predictive control (MPC) or different models of road disturbances and a genetic representation of the solution domain, such as genetic algorithms. The proposed algorithm takes advantage of the adaptive properties of the active disturbance rejection control (ADRC) to construct a reference governor for the full-car suspension system. Resultant from the proposed algorithm, the required calculations are significantly reduced when compared to the MPC and the performance of the system is constantly monitored. The ADRC focuses on maintaining ride-comfort while the reference governor adjusts the reference signal to maintain the road-handling ability. The results demonstrate how the reference governor optimizes the input reference signals to prevent the suspension deflection from exceeding its imposed limits in instances when required to maintain the greatest degree of road-handling, while simultaneously acting neutrally when the suspension travel is far from the strokes.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-15T07:14:25Z
      DOI: 10.1177/01423312221089715
       
  • An anomaly detection algorithm of rolling bearing combining random matrix
           eigenvalues and principal eigenvectors

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      Authors: Heng Wang, Wenchang Zhu, Wenyuan Zhang, Guangxian Ni, Yupeng Cao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An anomaly detection algorithm combining eigenvalues and eigenvectors in random matrix is proposed, which can solve the problem that present algorithms based on random matrix theory overly rely on eigenvalues and ignore useful information contained in eigenvectors. Firtsly, the time window method is used to select the original data of rolling bearing, and the sampling feature matrix is constructed by extracting bearing feature. Secondly, the eigenvalues and principal eigenvector of sampling feature matrix are investigated and combined to construct comprehensive feature index and its corresponding threshold. Finally, an anomaly detection based on comprehensive feature index is proposed to detect the early anomaly of rolling bearing. The application research is carried out by using bearing datasets of intelligent maintenance center and Xi’an Jiaotong University; the result shows that compared with the single eigenvalue index and kurtosis index, the algorithm based on the comprehensive feature index can detect the abnormal condition of bearing earlier. And the accuracy and effectiveness of the anomaly detection algorithm are proved through spectrum analysis, which provides guidance and basis for fault warning and equipment maintenance.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-15T07:08:42Z
      DOI: 10.1177/01423312221088390
       
  • Trajectory-tracking control of an underactuated unmanned surface vehicle
           based on quasi-infinite horizon model predictive control algorithm

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      Authors: Hao Wang, Zaopeng Dong, Shijie Qi, Zhengqi Zhang, Haisheng Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The method of a designed trajectory tracking for an underactuated unmanned surface vehicle (USV) in the presence of ocean disturbances is addressed in this paper; the differential flatness theory is applied to get the reference inputs and speed states at the reference position trajectory. Second, a transition process is arranged for the reference trajectory to reduce the overshoot of the actuator, which caused by the large deviation in the initial tracking. Third, the nonlinear disturbance observer is designed to obtain the estimated values of unknown disturbances in the ocean. Then, a controller-based model predictive control (MPC) and terminal cost function is designed for the nominal system. The inherent robustness of the controller and estimates of the observer are used to resist and compensate disturbances. Finally, the simulation experiments of linear trajectory and sinusoidal trajectories are carried out to prove the effectiveness and reliability of the control algorithm designed.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-15T07:06:02Z
      DOI: 10.1177/01423312221088378
       
  • Sampled-data-based dynamic event-triggered formation control for nonlinear
           multi-agent systems

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      Authors: Xiaofeng Chai, Qing Wang, Qi Diao, Yao Yu, Changyin Sun
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the distributed formation control of multi-agent systems with nonlinear dynamics. In view of practical digital microprocessor and limited network resources, the sampled-data-based dynamic event-triggered control strategy is developed. First, each agent synchronously samples its states and monitors the event-triggered function periodically. Each agent broadcasts its states to neighbors only when the function is triggered which can greatly reduce communication times. Meanwhile, the Zeno behavior is excluded due to periodic sampling. Moreover, the dynamic parameter in event-triggered function updates in accordance with a dynamic rule which helps achieve a trade-off between communication frequency and formation performance. The formation problem is transformed into the stability analysis of a time-delay system. Finally, numerical simulations are shown to illustrate the effectiveness of the proposed strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-15T07:04:31Z
      DOI: 10.1177/01423312221088087
       
  • Event-triggered adaptive backstepping admittance control for cooperative
           manipulation

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      Authors: Mohamed Abbas, Santosha K Dwivedy
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes an adaptive control strategy for multiple uncertain manipulators handling an object cooperatively in the presence of environmental forces and limited communication. To address the same, external and internal admittance models are imposed between the object/environment and manipulators/object to limit the excess interaction and internal forces. Thereafter, an adaptive backstepping approach is dedicated to follow the admittance-generated trajectory and deal with the dynamic uncertainties of the manipulators. Based on the Lyapunov analysis, an event-triggered (ET) mechanism is further designed to alleviate the controller-to-robot communication burden and preserve the system stability in the cooperative task. The performance of the proposed controller is compared with two admittance-based control strategies while manipulating the object through circular and lemniscate trajectories. The well-known triggering conditions, fixed and relative thresholds, are utilized further to investigate the effectiveness of the designed triggering condition. The obtained results prove the superiority of the proposed controller over the different time-triggered and even-triggered control strategies.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T10:02:53Z
      DOI: 10.1177/01423312221088648
       
  • Multi-objective parametric design of PI/PID controllers via multi-level
           game-theoretic optimization for systems with time delay

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      Authors: SH Ashraf Talesh, N Nariman-zadeh, A Jamali
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this research study, a new methodology of multi-objective optimal design is presented for control systems with time delay. Stackelberg method as an approach of game theory is implemented to develop the multi-objective optimization of proportional–integral (PI) and proportional–integral–derivative (PID) controllers. The surface area of control effort and tracking error are put in order of precedence together as the more important conflicting objective functions of the players in Stackelberg game design. Besides, the desirability of other effective criteria including frequency and time domains are measured as constraints in the procedure of the game-theoretic design. The main purpose of the proposed method is to optimally set and formulate controller parameters in the Stackelberg game-control system (SG-CS) design. Mapping the leader’s variables into the optimized values of the follower’s variables obtained via differential evolution (DE), the effectiveness of the proposed method is demonstrated in constructing a simple and explicit approximate model for rational reaction sets (RRSs). These obtained optimal models for the RRS allow the user to access the set of optimal controller parameters in the entire accessible strategic space of design variables in a formulated form. Utilizing the optimal synthesis for two case studies is validated the superiority of SG-CS design in establishing the explicit relationship between the controller’s parameters.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T09:57:14Z
      DOI: 10.1177/01423312221086812
       
  • Feedback error learning neural network for stable control of nonlinear
           nonaffine systems

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      Authors: Masoud Asgari, Mersad Asgari
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study presents a stable feedback error learning (FEL) scheme for nonlinear nonaffine systems in the presence of uncertainty and disturbances. The distinguishing feature of the FEL method, which can have a significant effect on both transient and steady-state performance, has led us to adopt this approach. The nonlinear system studied here is nonaffine. In other words, the function that describes the dynamic equations of the system is an implicit function of the control input rather than a particular class of systems. We aim to develop a stable FEL control system with three components: a neural network (NN), a linear controller, and a robustifying control term. To this end, all the adaptation laws for the NN weights are derived from a Lyapunov function, ensuring that the closed-loop system is uniformly asymptotically stable (UAS). Thus, an NN learning control approach that effectively improves the transient performance, as well as the steady-state performance, is proposed, and its remarkable effectiveness is illustrated in comparison with the existing methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T09:53:43Z
      DOI: 10.1177/01423312221086076
       
  • Full adaptive Kalman filters for nonlinear fractional-order systems
           containing unknown parameters and fractional-orders

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      Authors: Xiaomin Huang, Zhe Gao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, full adaptive Kalman filters are designed for continuous-time nonlinear fractional-order systems (FOSs) containing unknown parameters and fractional-orders. First, the estimated FOS is discretized using the Grünwald–Letnikov difference method to transform the fractional-order differential equation into a difference equation. Then, in terms of the nonlinear function contained in the investigated system, the Taylor expansion formula is adopted to linearize the discretized equation. Based on the method of augmented vector, an augmented state equation is established by state equations, unknown parameter equations, and fractional-order equation to achieve the state estimation. Besides, the sigmoid function is brought to ensure that the estimation of the fractional-order is performed in a suitable range. Because the covariance matrices of noises are difficult to be measured in physical systems, we also concern the problems on the state estimation, parameter estimation, and fractional-order estimation under the cases that the covariance matrix of process noise is unknown or the covariance matrix of measurement noise is unknown. Considering that the initial value can produce an error of state estimation and parameter identification for the FOS defined under the Caputo sense, the augmented vector method is used to achieve the initial value compensation. Finally, the effectiveness of the proposed algorithms is validated by four examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T09:47:40Z
      DOI: 10.1177/01423312221086070
       
  • Consensus of piecewise time-varying multi-agent systems with switching
           topologies

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      Authors: Jian Sun, Chen Guo, Lei Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a consensus problem is first investigated for piecewise time-varying multi-agent systems with switching topologies. Due to the piecewise time-varying characteristics of system matrix, it is challenging to design an appropriate controller to stabilize the error state within each piecewise time period. To overcome this difficulty, a piecewise time-varying Lyapunov function (PTVLF) approach is proposed to analyze the piecewise time-varying systems. Then, a useful lemma guaranteeing the negative definiteness of matrix polynomials is first derived, which is utilized to prove the negative definiteness of the derivative for the PTVLF. Based on this, a novel controller with time-varying gain is presented to stabilize the error state within each piecewise time period. Then, by selecting the dwell time of each topology larger than a positive threshold, the overall consensus of such systems is guaranteed. Finally, a numerical simulation is shown to illustrate the theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-08T12:23:55Z
      DOI: 10.1177/01423312221085786
       
  • Finite-time bounded control for quadrotors with extended dissipative
           performance using a switched system approach

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      Authors: Liang Nie, Bo Cai, Yunpeng Li, Hui Wang, Lixian Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to deal with the problem of attitude tracking control for quadrotors subject to time-varying inertia and external disturbances, a finite-time bounded switched linear parameter-varying (LPV) control method is presented. The attitude dynamics is described by two subsystems, where the inner angular-velocity system is used to track the desired angular velocities that are generated by the outer attitude-angle system. The angular-velocity system of quadrotors is modeled as a switched LPV model, where a family of linear models is developed to approximate the original nonlinear system and the LPV method is applied to model the time-varying inertia. Specially, a mode-dependent persistent dwell-time (MPDT) switching logic, which is more general than the typically used dwell-time (DT) or average dwell-time (ADT) switching logic, is adopted to govern the switching behaviors among these linear models. A state-feedback controller for the switched LPV error-tracking system is designed, which ensures both finite-time boundedness and extended dissipative performance. Finally, the developed theoretical results are verified by numerical simulation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-07T11:17:47Z
      DOI: 10.1177/01423312221085140
       
  • Dynamic surface control for formation control of quadrotors with input
           constraints and disturbances

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      Authors: Ao Dun, Rui Wang, Fei Lei, Yuning Yang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel formation control scheme is presented by integrating the dynamic surface control for multi-quadrotor subject with model uncertainties and external disturbances. First, according to requirements of formation control, the target trajectories of followers are obtained by the designed virtual quadrotors. Then, the formation control problem is transformed into the trajectory tracking control problem. Second, the saturation function and the auxiliary system are developed to make up for nonlinear terms arising from input saturation. A nonlinear extended state observer (ESO) is proposed to estimate and compensate for model uncertainties and external disturbances, and a dynamic surface controller based on the nonlinear ESO is constructed for the desired formation performance. In addition, the amount of communications between the quadrotors is decreased by the constructed distributed speed estimator. And the uniformly ultimately bounded is proved by using the Lyapunov method. Finally, the numerical example is used to demonstrate that the designed controller is effective.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-07T05:10:55Z
      DOI: 10.1177/01423312221085391
       
  • The feedback stabilization of finite-state fuzzy cognitive maps

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      Authors: Wang Xiaojie, Luo Chao, Lv Chen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Fuzzy cognitive maps (FCMs) are a kind of cognitive model for knowledge representation and causal inference. Meanwhile, as fuzzy dynamical systems, FCMs have also been widely applied in the control-related fields, such as mobile robots, unmanned aerial vehicles (UAVs), and industrial controls. However, the existing works mainly focused on the practical applications but lacked the necessary theoretical discussions related to the FCM-based control mechanism. As is known, stabilization is one of the fundamental issues in the control fields. Till date, rigorous research on the stabilization of FCMs is still an issue to be studied. In this article, using state feedback control method, the global stabilizations of finite-state FCMs are investigated. First, utilizing the semi-tensor product (STP) of matrices, the algebraic expression of FCM can be derived. Some theorems ensure the sufficient condition for the existence of the state feedback controller of the global stabilization. Second, the constructive design processes of state feedback controllers are discussed in detail. Third, the global stabilization is further extended into partial stabilization, where only specific concepts of FCMs can be stabilized. The corresponding theoretical analysis is implemented. Finally, the effectiveness of the proposed methods is verified by several examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-05T11:39:09Z
      DOI: 10.1177/01423312221085785
       
  • Stabilization of a class of switched systems with state constraints via
           time-varying Lyapunov functions

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      Authors: Ruicheng Ma, Lin Huang, Xiaoyi Tian
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the stabilization problem of a class of continuous-time switched linear systems with state constraints under pre-specified dwell-time switchings. Such systems are defined on a closed hypercube as all state variables are constrained to the unit hypercube. The dwell time in this paper is an arbitrarily pre-specified rather than a calculated constant, which is independent of any parameters. First, a class of multiple time-varying Lyapunov functions is introduced to study the stability analysis, and sufficient conditions on stability of the studied switched systems without control input are derived in the framework of pre-specified dwell-time switchings. The distinguishing feature of the proposed Lyapunov functions is that this type of delicately constructed Lyapunov functions can efficiently eliminate the “jump” phenomena of adjacent Lyapunov functions at switching times. Second in the same framework of the dwell time, sufficient conditions for stabilization are proposed for that of the switched systems with state constraints by further designing state feedback controllers. Finally, two examples are provided to demonstrate the effectiveness of the proposed results. The results of this paper do not require to calculate the total time of each subsystem during which the state is saturated or non-saturated separately, which makes the pre-specified dwell-time switchings easy to apply.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-04T11:03:01Z
      DOI: 10.1177/01423312221086075
       
  • Fixed-time consensus disturbance rejection for high-order nonlinear
           multi-agent systems with input saturation

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      Authors: Xiaolin Ai
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study is devoted to investigating the fixed-time consensus disturbance rejection problem for a class of high-order nonlinear multi-agent systems (MASs) with input saturation. A distributed fixed-time state observer (FTSO) is first proposed to reconstruct the leader’s states for each follower. Based on the estimated values, a fixed-time consensus protocol is designed via backstepping, where a fixed-time disturbance observer (FTDO) is used to provide the robustness against the external disturbances. The violation of the input saturation is prevented by introducing an auxiliary variable and the problem of “explosion of terms” suffered by the conventional backstepping design is also successfully avoided by a fixed-time differentiator. Detailed convergence results are presented by leveraging Lyapunov stability theory. Finally, the effectiveness of the proposed approach is numerically validated through simulation results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-04T10:59:21Z
      DOI: 10.1177/01423312221086063
       
  • An Unscented Kalman Filter–based iterative learning controller for
           multibody rotating scan optical spacecraft

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      Authors: Xian Zhao, Yunhai Geng, Chao Yuan, Baolin Wu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, to address the periodic control problem facing high-precision observation for multibody rotating scan optical spacecraft connected with active magnetic bearing (AMB), the Unscented Kalman Filter (UKF)–based iterative learning controller (UILC) is proposed. In the UILC, an adaptive backstepping controller (ABC) is deployed in the main loop to make the system state converge, and an UKF module is substituted for the memory module to use feedback information in real time and eliminate error propagation between adjacent periods. In the paper, the 9 degrees of freedom (DOF) error discrete dynamics are first derived to facilitate the convergence proved in the discrete domain. Then, the convergence analysis of the closed-loop system is investigated, and the state error supremum of closed-loop system in the mean square is indicated. Finally, for a comparison with the classical iterative learning controller (ILC), a series of numerical simulations are performed. As indicated by the simulation results, the UILC is capable of eliminating periodic deviation and error propagation during the adjacent periods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-04T10:56:23Z
      DOI: 10.1177/01423312221085268
       
  • Stabilisation of network-controlled aircraft pitch control system with
           time delay

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      Authors: Manikandan Subramanian, Priyanka Kokil
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper describes the stability assurance of network-controlled aircraft pitch control system with time delays. A frequency-domain method is used to determine the upper bound of time delay for aircraft pitch control system with gain and phase margin constraint. The effectiveness of proportional-integral (PI) and fractional-order PI controller on aircraft pitch control system stability and performance is investigated in presence of time delay. The parametric space of the PI and fractional-order PI controller are plotted in two-dimensional space to determine the stability region and controller is designed with concern to the time delay. The relation between controller parameters and time delay is estimated and these findings contribute significantly for the design of the controller for aircraft pitch control system. The accuracy of the proposed results is validated using simulation benchmark.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-04T10:52:28Z
      DOI: 10.1177/01423312221083756
       
  • [math] smooth switching distributed consensus controller for uncertain
           time-delay switched LPV multi-agent systems

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      Authors: MA Moradi, B Safarinejadian, MH Shafiei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an approach to design [math] smooth switching distributed linear parameter-varying (LPV) controller for consensus of LPV multi-agent systems (MASs) with a large range of parameter variations, uncertainty, input disturbance, and time-varying delay. By dividing the region of variable parameters into subregions with overlaps, a [math] smooth switching distributed sliding mode LPV controller with a switched dynamic sliding surface is designed for each subregion and the controller in overlapping subregions is interpolated from two adjacent subregions. This control problem is formulated into parametric linear matrix inequality (LMI), which is solved by convex optimization algorithms. To illustrate the efficacy of the result, it is applied to consensus of practical vertical take-off and landing (VTOL) helicopter MAS.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-03T09:48:32Z
      DOI: 10.1177/01423312221085145
       
  • Analysis of fractional-order dynamics of dengue infection with non-linear
           incidence functions

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      Authors: Rashid Jan, Salah Boulaaras
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The infection of dengue is a devastating mosquito-borne infection around the globe that affects human health, social and economic sectors in low-income areas. Therefore, policymakers and health experts are trying to point out better policies to reduce these losses and provide better information for the development of vaccination and medication. Here, we formulated a compartmental model for the transmission phenomena of dengue fever with nonlinear forces of infection through fractional derivative. We established several results related to the solution of our dengue model by using the basic properties of fractional calculus. We determined the basic reproduction number of our fractional-order system, symbolized by [math]. We established the local asymptotic stability of the infection-free equilibrium of our dengue system for [math], and proved that the infection-free equilibrium is globally asymptotically stable without vaccination. The threshold dynamics [math] is tested through partial rank correlation coefficient method to notice the importance of parameters in the transmission of dengue infection. In addition, we have shown the impact of memory on the basic reproduction number numerically with the variation of different parameters. We conclude that the biting rate, recruitment rate of mosquitoes and index of memory are the most sensitive factors, which can effectively lower the level of dengue fever. The dynamical behavior of the proposed fractional system is presented through a numerical scheme to explore the overall transmission process. We predict that the fractional-order model can explore more accurately and preciously the intricate dengue disease transmission model rather than the integer-order derivative.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-03T09:44:26Z
      DOI: 10.1177/01423312221085049
       
  • Finite-frequency self-triggered model predictive control for Markov jump
           systems subject to actuator saturation

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      Authors: Yuling Liu, Jiwei Wen, Xiaoli Luan, Fei Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a self-triggered saturated model predictive control (SMPC) for Markov jump system (MJS) is studied in finite-frequency domain. First, the MJS with multi-modes is transformed into a single mode system with embedded transition probability to prepare for the use of generalized Kalman–Yakubovich–Popov (GKYP) lemma. Second, a dynamic self-triggered mechanism with time-varying threshold is developed to predict the next triggering time according to the current time, states, and jumping mode. Third, for disturbances that only possess finite-frequency band, a co-design of triggering condition and SMPC is realized by properly employing GKYP lemma. Compared with existing works, the main motivation of this paper is to improve the anti-interference ability within a specified frequency range. Moreover, we also aim to shorten the gap between the finite band control theory and its applications to practical engineering problems. Finally, the effectiveness of the proposed approach is demonstrated by both the numerical and practical simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-03T09:40:27Z
      DOI: 10.1177/01423312221085045
       
  • Preview control for discrete-time periodic systems with state delay

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      Authors: Li Li, Yaofeng Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      State feedback and output feedback control strategies are developed for discrete-time periodic systems with state delay via periodic preview control (PPC) technique in this article. To utilize future reference information for the controller design, a periodic augmented error system (PAES) with delay is constructed using the state augmentation technique and difference operator approach. Then, the PPC problem is converted into a stabilization problem. Furthermore, the state feedback and static output preview controllers are designed and sufficient conditions that guarantee the closed-loop stability of PAES are derived via the linear matrix inequality (LMI) approach. Finally, two examples are presented to illustrate the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-03T08:49:43Z
      DOI: 10.1177/01423312221085707
       
  • Consensus of multi-agent systems via prescribed-time sliding mode control
           method

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      Authors: Yingjiang Zhou, Jingyu Liu, Guo-Ping Jiang, Cheng Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The consensus of multi-agent systems (MASs) by way of prescribed-time sliding mode control (PTSMC) is investigated in this paper. For the nonlinear system, a continuous and monotone controller is devised to attain the prescribed-time stable (PTS). A prescribed-time sliding mode surface (PTSMS) is selected for the second-order system, and a prescribed-time controller is designed to ensure that all states arrive at the PTSMS within the prescribed time. Then, the PTSMC method is applied to the distributed consensus of the second-order MASs. The efficiency of the presented methods is validated by the simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-29T12:40:03Z
      DOI: 10.1177/01423312221085410
       
  • A Friend-or-Foe framework for multi-agent reinforcement learning policy
           generation in mixing cooperative–competitive scenarios

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      Authors: Yu Sun, Jun Lai, Lei Cao, Xiliang Chen, Zhixiong Xu, Zhen Lian, Huijin Fan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Although multi-agent deep deterministic policy gradient is a classic deep reinforcement learning algorithm in multi-agent systems. It also has critical problems such as poor training stability and low policy robustness, which significantly limit the capability and application of the algorithm. So this article proposes an improved algorithm called friend-or-foe multi-agent deep deterministic policy gradient for solving the above problems. The main innovations are as follows: (1) inspired by the concept of friend-or-foe game theory, we modified the framework of the original multi-agent deep deterministic policy gradient by using two identical training networks with agents’ optimal and worst actions input, which improves the robustness of training policies, and (2) we propose an action perturbation technique based on gradient-descent to expand the selection range of actions, thereby improving training stability of our proposing algorithm. Finally, we conducted multiple sets of comparative experiments between our friend-or-foe multi-agent deep deterministic policy gradient and original one in four authoritative mixed cooperative–competitive scenarios. The results show that our improving algorithm can simultaneously improve the training stability and the robustness of agents’ generating policies in different complicated environments.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-29T12:38:28Z
      DOI: 10.1177/01423312221077755
       
  • Solving two-dimensional bioheat optimal control problem in solid and
           vessel domain by pseudospectral discretization

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      Authors: Mohammad Ebrahim Dastyar, Alaeddin Malek, Sohrabali Yousefi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an optimal control problem subject to an energy transfer equation in thermally significant blood vessel coupled with the Pennes governing equation is solved. The proposed dynamical system is modeled by a system of conduction-reaction and convection-conduction equations. Chebyshev–Gauss–Lobatto (CGL) and Legendre–Gauss–Lobatto (LGL) points are applied to discretize optimal control problem. Then, the problem transferred into a quadratic programming problem using domain decomposition and matching the solution and its first derivative across the related interfaces. The Tikhonov regularization method is used to compute the optimal regularization parameter for the objective function. Some theories have been discussed to prove that the discrete problem has a solution and it is also consistent with the continuous problem. Numerical results are compared and numerical convergent is shown. Optimal and non-optimal external heat source is compared and it is shown that the mathematical modeling is effective in saving the external heat energy. Numerical results show that by this process of heating at the final time, the temperature is very close to the desired temperature without damaging the vessel domain. Numerical results and corresponding graphs are depicted.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-25T06:58:25Z
      DOI: 10.1177/01423312221083770
       
  • Design of the MVT RBF neural network robotic manipulator control system
           based on model block approximation

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      Authors: Yuan Xiaoliang, Liu Jun, Xie Shouyong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Due to the uncertain dynamic characteristics, the requirements for robotic manipulator control are increasingly complex. The traditional radial basis function (RBF) neural network has a good generalization ability, but its redundant and tedious training process cannot meet the “Intelligent” control requirement of robotic manipulator. This study designs a new valve-regulated memristive RBF neural network, which adopts the model block approximation control strategy to estimate the three coefficient matrices of the robotic manipulator and uses the memristor with voltage threshold (MVT) as an electronic synapse to provide connections between neurons for the neural network and store information. This study adopts the design idea of software hardening and replaces the updated neural network weight with the change of the memristance value in the MVT network (crossed array), which can effectively improve the control performance of the traditional RBF neural network and can also provide analytical data for the fault detection of the subsequent control system. A simulation analysis is conducted with a single-joint robotic manipulator as the control object, and the results verify the rationality and feasibility of the proposed control algorithm.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-19T10:44:50Z
      DOI: 10.1177/01423312221083782
       
  • Distributed fixed-time average-tracking for multi-agent systems with
           mismatched and matched disturbances

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      Authors: Yu-Ling Li, Cheng-Lin Liu, Ya Zhang, Yang-Yang Chen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, distributed fixed-time average-tracking problem is discussed for second-order multi-agent systems (MASs) with mismatched and matched disturbances. To address this issue, we first propose a novel distributed fixed-time average estimator for each agent to estimate the average value of multiple time-varying reference signals (TVRSs). Then, to tackle with the case in the presence of external mismatched and matched disturbances, a disturbance observer is constructed to estimate them in a fixed time. Finally, based on the disturbance observer, a fixed-time average-tracking protocol is designed to drive each agent to track the average value of multiple TVRSs within a fixed time. Simulation experiments are conducted to verify the effectiveness of the proposed fixed-time anti-disturbance average-tracking algorithm.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-19T04:43:18Z
      DOI: 10.1177/01423312221083785
       
  • A compensation sliding mode control for machining robotic manipulators
           based on nonlinear disturbance observer

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      Authors: Fangchen Yin, Congwei Wen, Qinzhi Ji, Hongyuan Zhang, Hui Shao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The machining robotic manipulators (MRMs) find a broad range of applications due to their high efficiency, wide range of processing, and strong flexibility. High tracking accuracy and strong anti-interference ability are required to trajectory tracking control of machining robot during processing. In view of the above characteristics, this paper proposes a compensation sliding mode control (CSMC) based on nonlinear disturbance observer (NBO-CSMC) for MRM. First, we deduced the dynamic model of MRM considering the uncertainties and disturbances. Then, for improving the trajectory tracking accuracy, a compensation sliding mode controller is designed based on the traditional sliding mode control (TSMC) strategy. Finally, in order to reduce the chattering in sliding mode control, the NBO-CSMC is designed for MRM, NBO is used to estimate the external composite uncertain interference existing in the system, and compensate the system control input in real time. The Lyapunov’s theory proved the stability of the proposed algorithm, and simulation experiments verified the effectiveness of the proposed control strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-19T04:41:00Z
      DOI: 10.1177/01423312221083771
       
  • Computation of parametric uncertainty margin using stability boundary
           locus: An application to load frequency control

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      Authors: Jitendra Sharma, Yogesh V Hote, Rajendra Prasad
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, computation of parametric uncertainty margin (PUM) of a system is explored. In the presence of parametric uncertainty, maintaining the stability of the system is a daunting task. In view of this, in this paper, a new methodology is proposed to determine the maximum parametric uncertainty or PUM that can be tolerated in an interval type proportional–integral (PI) controlled system so that the whole system remains robustly stable. In order to show the validity of the proposed approach, an example of interval type load frequency control (LFC) system is considered to determine the PUM numerically. The proposed approach utilizes the concept of Kharitonov’s theorem for the modeling of interval type systems and stability boundary locus (SBL) technique for the designing of PI controller. The PUM obtained using the proposed approach is compared by that achieved by Kharitonov’s rectangles and zero exclusion principle.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-17T07:17:15Z
      DOI: 10.1177/01423312221083762
       
  • Design of optimized interval type-2 fuzzy logic controller based on the
           continuity, monotonicity, and smoothness properties for a cart-pole
           inverted pendulum system

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      Authors: Ethem Kelekci, Tugce Yaren, Selcuk Kizir
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, an interval type-2 fuzzy logic controller design method is proposed and validated on the real-time under-actuated nonlinear inverted pendulum system for swing-up and stabilization control problems. The swing-up algorithm is designed to give a faster response and the stabilization controller is designed based on continuity, monotonicity, and smoothness theorems for worst and best cases using the Mamdani fuzzy inference system in order to show the effectiveness of the proposed method. Outstanding type reduction methods are analyzed for the stabilization controller based on the design approach to determine the best type reduction algorithm for the effective and robust control performance. Real-time experiments are conducted to investigate the capability of the proposed controller in terms of adaptation performance and robustness ability. The controller also is able to handle structured and unstructured uncertainties such as measurement noise, external payload, undesirable internal/external disturbances, and parameter uncertainties. The results show that the proposed method clearly improves the control performance of the system in six experimental tasks conducted.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-11T12:25:29Z
      DOI: 10.1177/01423312221081309
       
  • Multi-objective risk-based optimal power system operation with renewable
           energy resources and battery energy storage system: A novel Hybrid
           Modified Grey Wolf Optimization–Sine Cosine Algorithm approach

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      Authors: Kaushik Paul
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This research work proposes a Hybrid Modified Grey Wolf Optimization–Sine Cosine Algorithm for the multi-objective optimal scheduling of hybrid power system taking into consideration the risk factor arising due to the intermittent/uncertain nature of the renewable power generation sources. The hybrid power system is modelled considering the thermal generation units, wind energy system, solar photo voltaic system, electric vehicle and battery energy storage system. The multi-objective optimization problem is proposed based on the simultaneous minimization of the total operating cost and system risk. The conditional value at risk is introduced as the risk index to analyse the system risk due to uncertainties in power deliveries by the renewable energy resources, electric vehicle and battery energy storage system during the scheduling process. The integral contribution of this research work focuses on the establishment an optimal generation schedule based on the combined optimization of the total operating cost and system risk. The simultaneous minimization of the operating cost and the risk index is performed with the multi-objective Hybrid Modified Grey Wolf Optimization–Sine Cosine Algorithm and has been used to develop a Pareto-optimal front. The implementation of the fuzzy min–max technique is opted to fetch the best compromised solution. The standard test systems of IEEE-30 bus and Indian-75 bus system are used to validate the potency of the proposed approach. Comparative analysis has been established to highlight the results obtained with the proposed approach is appreciable than other optimization techniques.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-25T01:27:08Z
      DOI: 10.1177/01423312221079962
       
  • Robust gain-scheduled output feedback [math] controller synthesis with
           reduced conservativeness: An application to EMS system

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      Authors: Reza Yavari, Arash Sadeghzadeh, Saeed Shamaghdari
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article investigates the design problem of gain-scheduled output feedback (GSOF) [math] controller exploiting uncertain scheduling parameters for continuous-time linear parameter-varying (LPV) systems. The problem of coexistence of absolute and proportional uncertainties on the scheduling parameters is considered to address more practical situations. This challenging issue has been tackled by introducing a novel admissible region for the actual and measured scheduling parameters. Furthermore, all the system matrices of the LPV system are assumed to be polynomially dependent on the scheduling parameters with arbitrary degrees. Both Lyapunov and auxiliary matrices are considered to be parameter-dependent. The merit of the proposed method lies in its less conservativeness in comparison with the available approaches. The design method is presented in terms of solutions to a set of parameter-dependent linear matrix inequalities (LMIs) including parameter searches for two scalar values. The application of the provided method on an electromagnetic suspension (EMS) system is considered to demonstrate the applicability and benefits of the proposed approach for practical systems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-23T12:37:27Z
      DOI: 10.1177/01423312221078427
       
  • Self-referenced nanometric displacement sensing assisted by optical
           anapole mode

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      Authors: Jingzhi Wu, Hengze Yang, Yanhong Wang, Mengwei Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Long range optical rulers measuring distance greater than 10 nm have important applications in monitoring biological processes, nanolithography, and nanometrology. In this work, we show that lateral displacement over 120 nm can be determined by measuring two reflection peaks of the proposed nanostructure. The optical anapole in the nanostructure is excited, resulting from interactions of plasmonic resonance modes of nanoholes perforated in metal films and an array of nanoblocks. Results show that a 120 nm relative displacement between the nanoblocks and nanoholes induces a negative correlated 90% variation of reflection spectrum which can be used for self-referenced measurement. The proposed design could find applications in nanometrology, biosensing, and nanofabrication.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-01-22T06:44:45Z
      DOI: 10.1177/01423312211069742
       
  • On real-time creep damage prediction for steam turbine

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      Authors: Yongjian Sun, Bo Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, in order to solve the calculation problem of creep damage of steam turbine rotor, a real-time calculation method based on finite element model is proposed. The temperature field and stress field of the turbine rotor are calculated using finite element analysis software. The temperature data and stress data of the crucial positions are extracted. The data of temperature, pressure, rotational speed, and stress relating to creep damage calculation are normalized. A real-time creep stress calculation model is established by multiple regression method. After that, the relation between stress and damage function is analyzed and fitted, and creep damage is calculated in real-time. A creep damage real-time calculation system is constructed for practical turbine engineering. Finally, a numerical simulation experiment is designed and carried out to verify the effectiveness of this novel approach. Contributions of present work are that a practical solution for real-time creep damage prediction of steam turbine is supplied. It relates the real-time creep damage prediction to process parameters of steam turbine, and it bridges the gap between the theoretical research works and practical engineering.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-01-17T06:24:25Z
      DOI: 10.1177/01423312211068949
       
  • Research on cyber-physical system control strategy under false data
           injection attack perception

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      Authors: Zhiwen Wang, Bin Zhang, Xiangnan Xu, Usman, Long Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the security control problem of the cyber-physical system under false data injection attacks. A model predictive switching control strategy based on attack perception is proposed to compensate for the untrusted sequence of data caused by false data injection attacks. First, the binary attack detector is applied whether the system has suffered the attack. If the attack occurs, multistep correction is carried out for the future data according to the previous time data, and the waiting period [math] is set. The input and output sequence of the controller is reconstructed, and the system is modeled as a constant time-delay switched system. Subsequently, the Lyapunov methods and average-dwell time are combined to provide sufficient conditions for the asymptotical stability of closed-loop switched system. Finally, the simulation of the networked first-order inverted pendulum model reveals that the control technique can efficiently suppress the influence of the attacks.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-01-13T05:22:04Z
      DOI: 10.1177/01423312211069371
       
  • A framework for battery internal temperature and state-of-charge
           estimation based on fractional-order thermoelectric model

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      Authors: Yujie Wang, Caijie Zhou, Guanghui Zhao, Zonghai Chen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In recent years, the rapid development of electric vehicles has raised a wave of innovation in lithium-ion batteries. The safety operation of lithium-ion batteries is one of the major bottlenecks restraining the development of the energy storage market. The temperature especially the internal temperature can significantly affect the performance and safety of the battery; therefore, this paper presented a novel framework for joint estimation of the internal temperature and state-of-charge of the battery based on a fractional-order thermoelectric model. Due to the nonlinearity, coupling, and time-varying parameters of lithium-ion batteries, a fractional-order thermoelectric model which is suitable for a wide temperature range is first established to simulate the battery’s thermodynamic and electrical properties. The parameters of the model are identified by the electrochemical impedance spectroscopy experiments and particle swarm optimization method at six different temperatures, and then the relationship between parameters and temperature is obtained. Finally, the framework for joint estimation of both the cell internal temperature and the state-of-charge is presented based on the model-based state observer. The experimental results under different operation conditions indicated that, compared with the traditional off-line prediction method, the model-based online estimation method not only shows stronger robustness under different initial conditions but also has better accuracy. Specifically, the absolute mean error of the estimation of state-of-charge and internal temperature based on the proposed method is about 0.5% and 0.3°C respectively, which is about half of that based on the off-line prediction method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-01-06T06:58:33Z
      DOI: 10.1177/01423312211067293
       
  • MP-CRJ: Multi-parallel cycle reservoirs with jumps for industrial
           multivariate time series predictions

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      Authors: Hongguang Li, Wenjing Zhao, Yilin Shi, Jince Li
      First page: 2093
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Nowadays, echo state networks (ESNs) with a variety of model structures are available for industrial process time series predictions. However, most existing ESNs employ a uniform timescale for data knowledge learning, which obviously ignores the influences of multivariate status at different timescales to the prediction target, usually leading to unsatisfactory model approximation performances. In response to this problem, this paper proposes a multi-parallel cycle reservoir with jumps (MP-CRJ) which is embedded with the feature knowledge of different timescales contained in the multivariate data. The MP-CRJ uses a more concise and superior circular jump reserve pool and a more memorable leaky integral neuron-filled parallel structure able to reduce the spatial complexity resulted from parallel ESNs and relatively improve the dynamic diversity of reserve pools. In addition, grey relational analysis algorithms are used to select relevant variables contributing to the prediction in filtering unnecessary data information. Applying to practical plant data for methanol productions, it shows that the MP-CRJ can help increase the prediction accuracy while maintain prediction speeds, as well as enjoy better adaptions to dynamics of complex industrial processes.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-01T12:26:23Z
      DOI: 10.1177/01423312211069483
       
  • Adaptive quantized controller design for synchronization of uncertain
           fractional-order nonlinear systems satisfying incremental quadratic
           constraints

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      Authors: Leipo Liu, Yilin Shang, Yifan Di, Zhumu Fu, Xiushan Cai
      First page: 2106
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes the adaptive quantized controller design for the synchronization of a class of fractional-order nonlinear systems satisfying incremental quadratic constraints governed by an incremental multiplier matrix. The incremental quadratic constraints can describe many commonly encountered nonlinearities in existing literature. The adaptive quantized controller are designed and formulated in terms of matrix inequalities to make the error system asymptotically stable. Meanwhile, the sufficient conditions can be obtained via solving linear matrix inequalities. Moreover, an algorithm is presented to illustrate the steps of designing adaptive quantized controllers. Finally, examples about fractional-order Lorenz chaotic system and fractional-order Bloch system are provided to illustrate the effectiveness of the designed controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-01T12:33:40Z
      DOI: 10.1177/01423312211072625
       
  • Event-triggered passivity and synchronization of coupled
           reaction–diffusion neural networks with and without time-varying delay

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      Authors: Shanrong Lin, Xiwei Liu, Yanli Huang
      First page: 2117
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is devoted to deal with the event-triggered passivity and synchronization problems for two types of coupled reaction–diffusion neural networks (CRDNNs). In the first type, several passivity and synchronization criteria for CRDNNs are acquired through designing suitable event-triggered controllers, combining some inequality techniques and Lyapunov functional approach. In the second type, the problems of event-triggered synchronization and passivity for coupled delayed reaction–diffusion neural networks (CDRDNNs) are investigated. Finally, two numerical examples are provided to illustrate the effectiveness of the derived passivity and synchronization conditions.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-01T12:41:31Z
      DOI: 10.1177/01423312211073223
       
  • Robust iterative learning control design based on iterative integral
           sliding mode for nonlinear systems with unrepeatable disturbance

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      Authors: Xiaoyu Zhang
      First page: 2141
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      For the repetitive tracking control tasks, the unrepeatable disturbance is an obstruction to learning control schemes. This paper discussed the robust iterative learning control (RILC) design based on the sliding mode control (SMC) technique for a class of nonlinear systems with unrepeatable disturbances. In order to make the tracking error converge to zero in the iteration domain under the sliding mode and eliminate the reaching phase of the SMC, an iterative integral sliding mode (IISM) surface design was proposed. The IISM leads to linear tracking error dynamics in the iteration domain, which guarantees the convergence if the sliding mode parameters meet the given condition. After that, the iterative learning control (ILC) based on the IISM was designed, which drove the sliding mode variable of the closed-loop system to reach the origin with iterations from the initial time instant, despite the effect of the unrepeatable disturbances. The robustness to the unrepeatable disturbance and the fast convergence were achieved. Finally, the proposed IISM method was applied to a one-link robotic manipulator, and the simulation results validated the performance of the proposed control design.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-03T06:56:57Z
      DOI: 10.1177/01423312211069268
       
  • Observer-based adaptive neural network control for stabilized platform in
           rotary steerable system with unknown input dead-zone

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      Authors: Min Wan, Shanshan Huang, Guorong Wang, Qiang Zhang
      First page: 2152
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The core task of the stabilized platform in the rotary steerable system is to control the toolface angle, so that the trajectory of the whole bit can move forward to the set direction. Due to many downhole interference factors, the uncertainties of parameters related to internal friction and interference torque of stabilized platform always exist, which poses great challenges to model establishment and controller design. Moreover, the actuator dead-zone nonlinearity makes the control more complicated. Hence, a dynamic model of stabilized platform considering a variety of nonlinear factors is established, and an observer-based adaptive neural network (NN)-control law is proposed. An NN state observer is developed to cope with the uncertain states composed of unknown friction parametric uncertainties and unmodeled disturbances, the dead-zone inverse is constructed to compensate for a dead-zone, and the dynamic surface control (DSC) strategy is used to solve the “differential explosion,” all signals in the system are proved to be semi-global uniformly ultimately bounded (SGUUB) by the Lyapunov function. Finally, the MATLAB simulation is set up, and the accurate tracking effect of the system is proved by the simulation in the presence of friction, modeling error, and dead-zone nonlinearity. The validity and the superior performance of the proposed control method under the downhole harsh environment and parameter perturbation is verified by the comparison simulation experiments.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-08T06:23:10Z
      DOI: 10.1177/01423312221075481
       
  • Nonfragile [math] tracking control strategies for classes of linear and
           bilinear uncertain Takagi-Sugeno fuzzy systems

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      Authors: Chekib Ghorbel, Naceur Benhadj Braiek
      First page: 2166
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents fuzzy tracking control strategies for classes of linear and bilinear Takagi-Sugeno Fuzzy System with Uncertainties and Disturbances (T-S FSUD). For both classes, the Lyapunov direct approach and the parallel distributed compensation concept are used to design nonfragile H∞ tracking controllers, which ensure the robust asymptotic stability of augmented systems despite the presence of parameter uncertainties, external disturbances, and controllers fragility. Besides that, based on the Schur complement, the separation lemma, and through some variable transformations, sufficient stability conditions of each augmented T-S FSUD are established and formulated in terms of linear matrix inequalities. Finally, numerical simulations are carried out to demonstrate the validity and the applicability of designed control schemes on tracking control of an inverted pendulum and a nonlinear mechanical system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-08T06:20:55Z
      DOI: 10.1177/01423312221075473
       
  • L1 adaptive output-feedback fault-tolerant control for uncertain nonlinear
           systems subject to unmodeled actuator dynamics and faults

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      Authors: Yan Zhou, Huiying Liu, Huijuan Guo
      First page: 2177
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper develops a L1 adaptive output-feedback fault-tolerant controller for uncertain nonlinear systems in the presence of unmodeled actuator dynamics and actuator faults. The proposed controller consists of the output predictor, adaptive laws, and the control law. The output predictor is a dynamic system expressed as a linear system with adaptive parameters which mean the matched uncertainties and the unmatched uncertainties. Piecewise-constant adaptive laws are designed to update the adaptive parameters so that the estimation error is driven to zero at each integration time step. The control law with low-pass filters is introduced to compensate for the performance degradation because of system uncertainties, unmodeled actuator dynamics and faults, and to guarantee the uniform boundedness of the input and output signals of the system. Two simulation examples verify the effectiveness of the proposed controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-09T09:18:33Z
      DOI: 10.1177/01423312221075470
       
  • Predefined-time sliding manifold-based fixed-time attitude stabilization
           control of receiver aircraft with measurement noises

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      Authors: Cihang Wu, Jianguo Yan, Xiwei Wu, Yiming Guo, Peng Mou, Bing Xiao
      First page: 2193
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the challenging attitude stabilization control problem of receiver aircraft subject to uncertain and time-varying inertia, and wind disturbances in the aerial refueling task. An adaptive fixed-time control strategy is proposed. In this approach, a predefined-time sliding manifold is preliminarily developed. The main feature is that the settling time is not only independent of initial conditions but also can be simply and explicitly defined in advance through a single parameter in the sliding mode phase. On this basis, an adaptive control law is developed to guarantee that the trajectory of attitude can be stabilized into a small region containing the origin. The upper bound of unknown disturbance is not required to implement the proposed controller, which relaxes the restrictions of design for control systems. Moreover, the measuring noises are explicitly considered and addressed to make this approach still available in the noisy measurement environment. The Lyapunov stability analysis and numerical simulations verify the effectiveness of the proposed control strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-17T09:19:46Z
      DOI: 10.1177/01423312221077759
       
  • Finite-time composite control for gimbal system in SGCMG under
           high-frequency disturbance

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      Authors: Yangyang Cui, Yongjian Yang, Jianzhong Qiao, Wenshuo Li, Yukai Zhu, Lei Guo
      First page: 2204
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the velocity-tracking problem of the gimbal system in a single gimbal control moment gyro (SGCMG) suffering from high-frequency disturbance. In order to accurately and quickly reject the high-frequency disturbance resulted from nonuniform mass distribution and manufacturing imperfection, a finite-time harmonic disturbance observer (FTHDO) is constructed according to the available information about the high-frequency disturbance. Then, a composite controller is developed to achieve simultaneous disturbance rejection and attenuation. The nominal control performance can be recovered under the high-frequency disturbance. It has been demonstrated that the velocity-tracking error can be stabilized by the proposed composite controller within finite time. Finally, numerical simulation results are presented to verify the superiority of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-21T12:41:31Z
      DOI: 10.1177/01423312221077746
       
  • Observer-based self-organizing adaptive fuzzy neural network control for
           non-linear, non-affine systems with unknown sign of control gain and dead
           zone: A case study of pneumatic actuators

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      Authors: Peyman Mawlani, Mohammadreza Arbabtafti
      First page: 2214
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an observer-based self-organizing adaptive fuzzy neural network (OSOAFNN) control for non-linear, non-affine systems with the unknown sign of control gain and dead zone is presented. First, a reverse dead-zone compensator scheme to cope with the impact of dead-zone phenomenon existing in control input is investigated. Then, an observed-based control approach to address immeasurable states of the system is proposed, utilizing this approach all states of the system are not needed to be available. A self-organizing fuzzy neural network (SOFNN) technique is presented to approximate the non-linear and unknown function of the observer error dynamics. The proposed fuzzy neural network (FNN) model benefits from two main advantages: (1) the number of rules is automatically generated or pruned and (2) the parameters of antecedent and consequent part of SOFNN are updated through the hybrid tuning, simultaneously. Furthermore, the control law contains a Nussbaum function which deals with the unknown sign of control gain. As the system states are immeasurable, the strictly positive real (SPR) Lyapunov function to guarantee the closed-loop system stability, and tracking error convergence to zero is employed, as well as the boundedness of control parameters are assured through a projection law merged with adaptive law. Finally, the controller is practically implemented on a non-linear, non-affine pneumatic system with unknown dead zone which exploits just a sensor for output measuring. Experimental results show that the proposed controller has satisfactory performance in tracking different trajectories, and tracking error for desired signal case I and case II is limited to [−1.5, 1.5] and [−1,1]mm, respectively.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-24T11:19:33Z
      DOI: 10.1177/01423312221074181
       
  • Multi-objective H2/H∞ saturated non-PDC static output feedback control
           for path tracking of autonomous vehicle

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      Authors: Amine Kennouche, Dounia Saifia, Mohammed Chadli, Salim Labiod
      First page: 2235
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a new fuzzy output feedback control design for autonomous vehicle steering under actuator saturation, unavailability of the sideslip angle measurement, unknown road curvature, and lateral wind force. To take into account the actuator constraint, the saturation effect is transformed into dead-zone nonlinearity. A static output controller based on non-compensation parallel distributed technic and a Takagi-Sugeno (T-S) model of vehicle lateral dynamics is proposed to consider the unavailability of some vehicle states. To avoid the problem of imposing bounds on membership functions time derivatives resulting from the use of the fuzzy Lyapunov approach, a proper integral structure based on the non-quadratic Lyapunov approach is investigated. The mixed [math] stabilization conditions of the augmented closed-loop system are expressed in terms of linear matrix inequalities (LMIs). Finally, the robustness and the advantages of the proposed approaches are demonstrated through different tests.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-02T08:58:30Z
      DOI: 10.1177/01423312221080461
       
  • Three-dimensional piecewise guidance strategy for multi-UAVs guaranteeing
           simultaneous arrival and field-of-view constraint

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      Authors: Zhou Jun, Liu Zequn, Guo Jianguo, Guo Zongyi
      First page: 2248
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a three-dimensional (3D) piecewise guidance scheme for multiple UAVs) guaranteeing simultaneous arrival even under the field-of-view (FOV) constraint. The guidance law does not require to consider the estimation of the time-to-go and can be divided into two stages: cooperative stage and proportional navigation guidance (PNG) stage. In the cooperative stage, a decentralized consensus control approach is proposed for multi-UAV systems and does not rely on global information about the communication topography. Moreover, the neighbors’ new auxiliary states are introduced to ensure the states achieving consensus under FOV constrain. The guidance strategy transfers to the PNG stage while the UAV formation is close enough to the target and the simultaneous arrival to hit the target is guaranteed for UAVs via the PNG guidance law. Numerical simulation results demonstrate the effectiveness of the proposed cooperative guidance law.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-03T12:28:55Z
      DOI: 10.1177/01423312221075491
       
  • Vibration control of a translational coupled double flexible beam system
           using sliding mode neural network fuzzy control

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      Authors: Zhi-cheng Qiu, Si-wen Chen
      First page: 2264
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A sliding mode neural network fuzzy control (SMNNFC) method is investigated to suppress the vibration of a translational coupled double flexible beam system, equipped with an AC servomotor and several piezoelectric actuators. Adjacent beams and slider moving frame are connected at the tip by elastic springs. Based on the finite element method, the system model is established to recognize the vibration characteristics. Furthermore, two laser displacement sensors are used to decouple the first two bending modes of the double flexible beam system. In the applied SMNNFC strategy, a neural-fuzzy framework is designed to obtain robust control performance and alleviate the chattering phenomenon. Considering unknown and varying system uncertainty, a parameter updating algorithm is adopted. The stability of SMNNFC is analyzed. The experimental setup is constructed and experiments are conducted, including set-point vibration control and simultaneous translation and vibration control under trapezoidal and sinusoidal trajectories. The experimental results demonstrate that the SMNNFC scheme has advantages in suppressing both the large and low amplitude vibrations of the coupling double flexible beam system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-03-04T12:40:06Z
      DOI: 10.1177/01423312221081505
       
 
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