Subjects -> INSTRUMENTS (Total: 63 journals)
Showing 1 - 16 of 16 Journals sorted alphabetically
Applied Mechanics Reviews     Full-text available via subscription   (Followers: 27)
Bulletin of Social Informatics Theory and Application     Open Access   (Followers: 1)
Computational Visual Media     Open Access   (Followers: 4)
Devices and Methods of Measurements     Open Access  
Documenta & Instrumenta - Documenta et Instrumenta     Open Access  
EPJ Techniques and Instrumentation     Open Access  
European Journal of Remote Sensing     Open Access   (Followers: 9)
Experimental Astronomy     Hybrid Journal   (Followers: 39)
Flow Measurement and Instrumentation     Hybrid Journal   (Followers: 18)
Geoscientific Instrumentation, Methods and Data Systems     Open Access   (Followers: 4)
Geoscientific Instrumentation, Methods and Data Systems Discussions     Open Access   (Followers: 1)
IEEE Journal on Miniaturization for Air and Space Systems     Hybrid Journal   (Followers: 2)
IEEE Sensors Journal     Hybrid Journal   (Followers: 103)
IEEE Sensors Letters     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Imaging & Microscopy     Hybrid Journal   (Followers: 9)
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan     Open Access  
Instrumentation Science & Technology     Hybrid Journal   (Followers: 6)
Instruments and Experimental Techniques     Hybrid Journal   (Followers: 1)
International Journal of Applied Mechanics     Hybrid Journal   (Followers: 7)
International Journal of Instrumentation Science     Open Access   (Followers: 40)
International Journal of Measurement Technologies and Instrumentation Engineering     Full-text available via subscription   (Followers: 2)
International Journal of Metrology and Quality Engineering     Full-text available via subscription   (Followers: 4)
International Journal of Remote Sensing     Hybrid Journal   (Followers: 282)
International Journal of Remote Sensing Applications     Open Access   (Followers: 45)
International Journal of Sensor Networks     Hybrid Journal   (Followers: 4)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Journal of Applied Remote Sensing     Hybrid Journal   (Followers: 83)
Journal of Astronomical Instrumentation     Open Access   (Followers: 3)
Journal of Instrumentation     Hybrid Journal   (Followers: 32)
Journal of Instrumentation Technology & Innovations     Full-text available via subscription   (Followers: 2)
Journal of Medical Devices     Full-text available via subscription   (Followers: 5)
Journal of Medical Signals and Sensors     Open Access   (Followers: 3)
Journal of Optical Technology     Full-text available via subscription   (Followers: 5)
Journal of Sensors and Sensor Systems     Open Access   (Followers: 11)
Journal of Vacuum Science & Technology B     Hybrid Journal   (Followers: 3)
Jurnal Informatika Upgris     Open Access  
Measurement : Sensors     Open Access   (Followers: 3)
Measurement and Control     Open Access   (Followers: 36)
Measurement Instruments for the Social Sciences     Open Access  
Measurement Science and Technology     Hybrid Journal   (Followers: 7)
Measurement Techniques     Hybrid Journal   (Followers: 3)
Medical Devices & Sensors     Hybrid Journal  
Medical Instrumentation     Open Access  
Metrology and Instruments / Метрологія та прилади     Open Access  
Metrology and Measurement Systems     Open Access   (Followers: 6)
Microscopy     Hybrid Journal   (Followers: 8)
Modern Instrumentation     Open Access   (Followers: 50)
Optoelectronics, Instrumentation and Data Processing     Hybrid Journal   (Followers: 4)
PFG : Journal of Photogrammetry, Remote Sensing and Geoinformation Science     Hybrid Journal  
Photogrammetric Engineering & Remote Sensing     Full-text available via subscription   (Followers: 29)
Remote Sensing     Open Access   (Followers: 55)
Remote Sensing Applications : Society and Environment     Full-text available via subscription   (Followers: 8)
Remote Sensing of Environment     Hybrid Journal   (Followers: 93)
Remote Sensing Science     Open Access   (Followers: 24)
Review of Scientific Instruments     Hybrid Journal   (Followers: 23)
Science of Remote Sensing     Open Access  
Sensors and Materials     Open Access   (Followers: 2)
Solid State Nuclear Magnetic Resonance     Hybrid Journal   (Followers: 3)
Standards     Open Access  
Transactions of the Institute of Measurement and Control     Hybrid Journal   (Followers: 13)
Труды СПИИРАН     Open Access  
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Transactions of the Institute of Measurement and Control
Journal Prestige (SJR): 0.41
Citation Impact (citeScore): 1
Number of Followers: 13  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0142-3312 - ISSN (Online) 1477-0369
Published by Sage Publications Homepage  [1151 journals]
  • A generalized control scheme for system uncertainty estimation and
           cancellation
    • Authors: Qing-Guo Wang, Tao Liu, Zhuo-Yun Nie, Shoulin Hao, Xuhui Ren, Dan Zhang, Lei Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper addresses the control of a continuous-time system with possibly large uncertainty of unknown internal dynamics or external disturbance. A novel control scheme is proposed to estimate and cancel the system uncertainty effectively so as to enhance disturbance rejection (DR) performance. Unlike asymptotic analysis with infinite gain in the literature, the estimation transient analysis is carried out for the proposed scheme with a finite estimator gain and the precise error formulas are derived, based on a classical low-order plant description. The control performance associated with a realizable gain is quantified by tight bounds with respect to the ideal case, which enables easy parameter tuning. The necessary and sufficient condition for the internal stability of the control system is established, along with a D-decomposition method for determining the complete set of the gain intervals that could internally stabilize the plant. In the presence of measurement noise, a low-pass filter is introduced to attenuate its adverse effect. Simulations and semi-realistic experiments are performed to demonstrate the effectiveness of the proposed scheme, which shows evident improvement on DR performance over the well-known active DR control.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-05-11T05:07:12Z
      DOI: 10.1177/01423312211010509
       
  • Adaptive neural network command filtered backstepping impedance control
           for uncertain robotic manipulators with disturbance observer
    • Authors: Gaorong Lin, Bingqiang Shan, Yumei Ma, Xincheng Tian, Jinpeng Yu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an adaptive neural network command filtered backstepping impedance control method is developed for uncertain robotic manipulators with disturbance observer. First, an adaptive neural network algorithm is used to estimate the uncertain dynamics in the robot system. Second, impedance control is introduced to adjust the force and position relationship in physical human–robot interaction (pHRI). Third, a disturbance observer is employed to estimate the unknown external disturbance in the environment and compensate the control system to improve the safety of pHRI. Then, the command filtered technique can overcome problems of the ‘computational complexity’ and ‘singularity’ of traditional backstepping design. Finally, the simulation results are provided to illustrate the effectiveness of the proposed control method in pHRI.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-05-04T06:22:21Z
      DOI: 10.1177/01423312211009376
       
  • Experimental and numerical validation of a proportional solenoid valve
           based on the data-driven model
    • Authors: Kaiwen Ma, Junqiang Xi, Yanfei Ren, Yanyu Liu, Fei Meng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Solenoid valves are widely used in mechatronics, robotic systems and industrial occasions. An accurate model is very important for the design and control of a solenoid valve. The dynamical model of the solenoid valve is difficult to obtain due to the complexity of the structure and the interaction of multiple physical fields. This paper proposes two kinds of model of solenoid valve: grey box model and black box model, on the basis of experimental data. ARX model is selected as the basic structure of the grey box model. After clustering the data with the fuzzy c-means algorithm, the overall experimental data is divided into several local linear sub-models, and the model coefficients of the local linear model are obtained by partial least square regression. The overall expression of the model is obtained by combining the local sub-models with membership degree. For the black box model, support vector regression algorithm is used to identify. On the basis of selecting the appropriate parameters, we obtain the black box model of solenoid valve based on data. For the above two models, we carry out experimental verification and error analysis, and compare with the traditional modelling method. According to the results, it can be seen that on the basis of the experimental data, using the data-driven method to construct the model has many advantages, avoiding complex physical analysis, and has high accuracy. The model with high precision will be used in the accurate control and observing estimation of the solenoid valve.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-05-04T06:19:20Z
      DOI: 10.1177/01423312211003363
       
  • Choosing the number of time intervals for solving a model predictive
           control problem of nonlinear systems
    • Authors: Jasem Tamimi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Model predictive control (MPC) is a control strategy that can handle state and control multi-variables at same time. To use the MPC using direct methods for solving the a dynamic optimization problem, one needs, for example, to transform the optimization problem into a nonlinear programming (NLP) problem by dividing the prediction horizon into equal time intervals. In this work, we suggest a tool and procedures for helping to choose a ‘compromise’ number of time intervals with a needed accuracy, objective cost, number of turned NLP iterations and computational time. On the other hand, we offer a simplified nonlinear program to ensure the convergence of a class of finite optimal control problem by modifying the state box constraints. In particular, a special type of box constraints were used to the constrained optimal control problem to enforce the state trajectories to reach the desired stationary point. These box constraints are characterized by some parameters that are easily optimized by our proposed nonlinear program. Our proposed tools are tested using two case studies; nonlinear continuous stirred tank reactor (CSTR) and nonlinear batch reactor.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-27T12:00:55Z
      DOI: 10.1177/01423312211007315
       
  • Inter-turn fault stability enrichment and diagnostic analysis of power
           system network using wavelet transformation-based sample data control and
           fuzzy logic controller
    • Authors: Arunesh Kumar Singh, Abhinav Saxena, Nathuni Roy, Umakanta Choudhury
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, performance analysis of power system network is carried out by injecting the inter-turn fault at the power transformer. The injection of inter-turn fault generates the inrush current in the network. The power system network consists of transformer, current transformer, potential transformer, circuit breaker, isolator, resistance, inductance, loads, and generating source. The fault detection and termination related to inrush current has some drawbacks and limitations such as slow convergence rate, less stability and more distortion with the existing methods. These drawbacks motivate the researchers to overcome the drawbacks with new proposed methods using wavelet transformation with sample data control and fuzzy logic controller. The wavelet transformation is used to diagnose the fault type but contribute lesser for fault termination; due to that, sample data of different signals are collected at different frequencies. Further, the analysis of collected sample data is assessed by using Z-transformation and fuzzy logic controller for fault termination. The stability, total harmonic distortion and convergence rate of collected sample data among all three methods (wavelet transformation, Z-transformation and fuzzy logic controller) are compared for fault termination by using linear regression analysis. The complete performance of fault diagnosis along with fault termination has been analyzed on Simulink. It is observed that after fault injection at power transformer, fault recovers faster under fuzzy logic controller in comparison with Z-transformation followed by wavelet transformation due to higher stability, less total harmonic distortion and faster convergence.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-27T11:58:34Z
      DOI: 10.1177/01423312211007006
       
  • Application of semi-active inerter in a two-body point absorber via force
           tracking
    • Authors: Yinlong Hu, Tianyang Hua, Michael Z. Q. Chen, Shang Shi, Yonghui Sun
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a self-reaction point absorber (PA) wave energy converter is studied, where wave energy is collected by the relative motion of the on-board plate and the buoy. The purpose of this study is to increase the relative displacement to obtain the maximum power. A semi-active inerter (SAI) is applied in the system, which is controlled by a force-tracking (FT) strategy. Two parts are required in the FT strategy: a target active control law; and a proper control law to adjust the inertance to track the active force (AF). The target control law is obtained by the full-state feedback of the state-space model of a two-body PA . The control law to adjust the inertance is to saturate the AF between the maximal and minimal semi-active force of an SAI. Both linear time-invariant system and linear time-varying system are studied. Power absorption is improved in both two systems by the application of SAIs. Moreover, the influence of dimensionless parameters on the ratio of power absorption improvement in the considered linear time-varying system is studied. Numerical simulation shows that the ratio of power absorption improvement is most sensitive to the changes of mass ratio of the on-board plate and the buoy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-25T03:59:24Z
      DOI: 10.1177/01423312211009374
       
  • Capacitance pressure sensor with S-type electrode for improved sensitivity
    • Authors: Santhosh KV, Swetha Rao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper aims at designing a differential pressure sensor. The objective of the work is to design and fabricate the electrodes of a capacitive pressure sensor, so as to measure absolute and differential pressure accurately with improved sensitivity. In place of conventional parallel plate diaphragm, S-type electrodes are proposed in the present work. The work comprises of study of the proposed design in terms of a mathematical model, input-output behavior along with detailed analysis of pressure distribution pattern. Output capacitance obtained for changes in pressure is converted to voltage with the suitable signal conditioning circuit and data acquisition system to acquire the signal on to a PC. A neural network model is designed to compensate the nonlinearities present in the sensor output. Input-output characteristics of the designed sensor shows an improved response as compared with existing pressure sensors.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-25T03:49:01Z
      DOI: 10.1177/01423312211008001
       
  • Design of back propagation optimized Nagar-Bardini structure-based
           interval type-2 fuzzy logic systems for fuzzy identification
    • Authors: Yang Chen, Jiaxiu Yang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In recent years, fuzzy identification based on system identification theory has become a hot academic topic. Interval type-2 fuzzy logic systems (IT2 FLSs) have become a rising technology. This paper designs a type of Nagar-Bardini (NB) structure-based singleton IT2 FLSs for fuzzy identification problems. The antecedents of primary membership functions of IT2 FLSs are chosen as Gaussian type-2 primary membership functions with uncertain standard deviations. Then, the back propagation algorithms are used to tune the parameters of IT2 FLSs according to the chain rule of derivation. Compared with the type-1 fuzzy logic systems, simulation studies show that the proposed IT2 FLSs can obtain better abilities of generalization for fuzzy identification problems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-25T03:44:39Z
      DOI: 10.1177/01423312211006635
       
  • Transmission rate conditions for distributed filtering in sensor networks
           against eavesdropper
    • Authors: Bingya Zhao, Ya Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the distributed secure estimation problem of sensor networks (SNs) in the presence of eavesdroppers. In an SN, sensors communicate with each other through digital communication channels, and the eavesdropper overhears the messages transmitted by the sensors over fading wiretap channels. The increasing transmission rate plays a positive role in the detectability of the network while playing a negative role in the secrecy. Two types of SNs under two cooperative filtering algorithms are considered. For networks with collectively observable nodes and the Kalman filtering algorithm, by studying the topological entropy of sensing measurements, a sufficient condition of distributed detectability and secrecy, under which there exists a code–decode strategy such that the sensors’ estimation errors are bounded while the eavesdropper’s error grows unbounded, is given. For collectively observable SNs under the consensus Kalman filtering algorithm, by studying the topological entropy of the sensors’ covariance matrices, a necessary condition of distributed detectability and secrecy is provided. A simulation example is given to illustrate the results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-25T03:39:18Z
      DOI: 10.1177/01423312211005607
       
  • Guaranteed cost and finite-time event-triggered control of
           fractional-order switched systems
    • Authors: Yilin Shang, Leipo Liu, Yifan Di, Zhumu Fu, Bo Fan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper considers the problem of guaranteed cost and finite-time event-triggered control of fractional-order switched systems. Firstly, an event-triggered scheme including both the information of current state and an exponential decay function is proposed, and a novel cost function that adopts the characteristics of fractional-order integration is presented. Secondly, some sufficient conditions are derived to guarantee that the corresponding closed-loop system is finite-time stable with a certain cost upper bound, using multiple Lyapunov functions and average dwell time approach. Meanwhile, the event-triggered parameters and state feedback gains are simultaneously obtained via solving linear matrix inequalities. Moreover, Zeno behavior does not exist by finding a positive lower bound of the triggered interval. Finally, an example about fractional-order switched electrical circuit is provided to show the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-25T03:37:19Z
      DOI: 10.1177/01423312211004802
       
  • Fixed-time leader-following flocking and collision avoidance of
           multi-agent systems with unknown dynamics
    • Authors: Tingruo Yan, Xu Xu, Zongying Li, Eric Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The fixed-time flocking of multi-agent systems with a virtual leader is investigated in this paper. The motion dynamics of the agents are assumed to be unknown and only satisfy the boundedness, which does not need to be modelled by the Lipschitz condition. To achieve the flocking and collision avoidance for all agents in the fixed time, a control protocol in the high-dimensional space is developed by using the graph theory and the theoretical properties of differential equations. Moreover, the upper bound of the settling time only depending on the control protocol and the topology of network is estimated. Numerical examples are used to verify the theoretical results, and show that the proposed method provides an applicable method for the control of the nonlinear dynamic systems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-21T04:06:06Z
      DOI: 10.1177/01423312211005277
       
  • Development of ring-shaped electrostatic coupled capacitance sensor for
           the parameter measurement of gas-solid flow
    • Authors: Hui Ding, Jian Li, Haoran Wang, Chuanlong Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper develops a novel non-intrusive ring-shaped electrostatic coupled capacitance sensor (ECCS) for the parameter measurement of gas-solid flow to eliminate the temperature drift of traditional capacitance sensor and to improve the reliability of velocity measurement. In ECCS, one source electrode and two detection electrodes are housed in a sensing head to simultaneously derive two pairs of capacitance and electrostatic signals, which can achieve the simultaneous measurement of the particle velocity, concentration and mass flow rate within the same sensing space of gas-solid flow system. The effects of the isolation electrodes on the capacitance sensitivity and the temperature drift of the sensor standing capacitance are further investigated. Then, a weighted velocity is determined by fusing the capacitance correlation velocity and the electrostatic correlation velocity based on the correlation coefficients, which are useful for the reliable measurement of gas-solid flow. Finally, experiments are carried out to test the performance of the developed ring-shaped ECCS. Results demonstrate that the developed ECCS triples the capacitance sensitivity for the radial position from -15 mm ∼15 mm. The temperature drift of the capacitance signal is less than 0.075 mV/oC from the room temperature to 65 oC, and thus the sensor standing capacitance is almost impervious to the temperature. After calibrating the relationship between the particle concentration and the capacitance signal, the developed ECCS can measure the particle mass flow rate with a relative error less than ±8%.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-20T12:23:44Z
      DOI: 10.1177/01423312211006640
       
  • Event-triggered stochastic consensus for networked Lagrangian systems with
           semi-Markov switching topologies and communication delays
    • Authors: Suying Pan, Zhiyong Ye, Zhonghua Miao, Jin Zhou
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the event-triggered stochastic consensus for networked Lagrangian systems with semi-Markov switching topologies and communication delays is considered. An event-triggered sampling control strategy is used to design the distributed stochastic consensus scheme of networked Lagrangian systems for two cases with leader and leaderless. Two delay-dependent consensus criteria are derived in the sense of mean square by use of a suitable Lyapunov-Krasovskii functional and the stochastic delayed Halanay inequality, respectively. A key feature of the developed event-triggered consensus algorithm is to introduce a suitable adjustment parameter on consensus control gains characterizing the effect of both semi-Markov switching topology and communication delay. Finally, a numerical example of four manipulators with two links is presented to illustrate the effectiveness of the developed event-triggered methodology.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-20T12:21:04Z
      DOI: 10.1177/01423312211004033
       
  • Event-triggered integral sliding mode fixed time control for trajectory
           tracking of autonomous underwater vehicle
    • Authors: Bo Su, Hongbin Wang, Ning Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an event-triggered integral sliding mode fixed-time control method for trajectory tracking problem of autonomous underwater vehicle (AUV) with disturbance is investigated. Initially, the global fixed time stability is ensured with conventional periodic sampling method for reference trajectory tracking. By introducing fixed time integral sliding mode manifold, fixed time control strategy is expressed for the AUV, which can effectively eliminate the singularity. Correspondingly, in order to reduce the damage caused by chattering phenomenon, an adaptive fixed-time method is proposed based on the designed continuous integral terminal sliding mode (ITSM) to ensure that the trajectory tracking for AUV is achieved in fixed-time with external disturbance. In order to reduce resource consumption in the process of transmission network, the event-triggered sliding mode control strategy is designed which condition is triggered by an event. Also, Zeno behavior is avoided by proof of theoretical. It is shown that the upper bounds of settling time are only dependent on the parameters of controller. Theoretical analysis and simulation experiment results show that the presented methods can realize the control object.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-20T12:18:25Z
      DOI: 10.1177/0142331221994380
       
  • Fractional order system modelling with Legendre wavelet multi-resolution
           analysis
    • Authors: Zishuo Wang, Chunyang Wang, Shuning Liang, Qifeng Niu, Shuai Ma
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a method of fractional order system (FOS) modelling with Legendre wavelet multi-resolution analysis. The proposed method expands the input and output signals of the system in the form of a Legendre wavelet, and constructs the Legendre wavelet integration operational matrix by use of a block-pulse function. To address the problem of the considerable volume of system identification data and system noise in practical engineering applications, the multi-resolution characteristics of the wavelet are combined to build a wavelet integration operational matrix from the multi-scale space. By continuously discarding the high-frequency information to reduce the length of the identification data, the identification speed of the system is accelerated and the influence of noise on the identification accuracy is reduced. In addition, the least squares method is used to find the optimal order in the identification interval and further accelerate the FOS modelling process. The proposed method rapidly identifies the FOS parameters with high accuracy, and is thus feasible for engineering applications. Its effectiveness is verified by simulation and photoelectric stabilized sighting platform experiment.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:36:13Z
      DOI: 10.1177/01423312211005865
       
  • Hybrid adaptive observer-based output feedback predictive control for the
           alternating activated sludge process
    • Authors: Afef Boudagga, Habib Dimassi, Salim Hadj Said, Faouzi M’Sahli
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an adaptive observer-based predictive controller is designed for the alternating activated sludge process which represents a nonlinear hybrid system. Precisely, our objective is to control the dissolved oxygen concentration during the aerobic phase. First, a hybrid adaptive observer is designed to estimate conjointly the unmeasured state (the ammonia concentration) and the unknown parameter (the coefficient of performance of heterotrophic biomass). Then the estimated signals are used in the output feedback predictive control law. The convergence of the state estimation, parameter reconstruction and tracking control errors are established through a Lyapunov stability analysis. Numerical simulations are dedicated to highlight the good performances of the developed output feedback control approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:34:09Z
      DOI: 10.1177/01423312211005624
       
  • Novel topology convolutional neural network fault diagnosis for aircraft
           actuators and their sensors
    • Authors: Ruonan Wei, Ju Jiang, Haiyan Xu, Danmeng Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The variable working conditions and frequent turns make the aircraft actuator system prone to failure, seriously threatening flight safety. The identification of the airplane actuator system is critical for flight decisions and safety. Most fault diagnosis methods of actuators only focus on the actuators themselves, ignoring the disturbance caused by the fault of the actuator position sensor, which may easily lead to wrong decisions. In order to distinguish the actuator fault from its position sensor fault and identify the fault type accurately, an offline diagnosis method of convolutional neural network (CNN) with novel topology for processing time series is proposed. A new shift layer is added after the input layer, which avoids the loss of a large number of features due to the direct connection between the time series and the convolutional layer. A local topological network learning complex pattern with inception module is designed to improve the diagnostic accuracy in different working conditions. The wide residual structure is introduced to expand the convolutional channel, which allows the network features at the bottom level to propagate directly to the top level to prevent network degradation. Simulation results show that this method can accurately diagnose the actuator fault and its position sensor, with an average accuracy of 96.8%. Compared with the current mainstream data-driven methods, the precision and recall are increased by 6.3% and 6.7% respectively.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:30:06Z
      DOI: 10.1177/01423312211005612
       
  • Observer-based adaptive neural sliding mode trajectory tracking control
           for remotely operated vehicles with thruster constraints
    • Authors: Zhenzhong Chu, Yunsai Chen, Daqi Zhu, Mingjun Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      For a class of remotely operated vehicle (ROV) systems with thruster constraints, immeasurable states, and unknown nonlinearities, the trajectory tracking control problem was discussed in this paper. The unknown nonlinear functions were approximated by radial basis function (RBF) neural networks. An adaptive state observer based on neural networks was designed and the immeasurable states were estimated. Considering the problem of thruster saturation constraints, an auxiliary system for saturation compensation was designed and a saturation factor was constructed by the auxiliary system state. By applying the backstepping design method, an adaptive neural sliding mode trajectory tracking controller was developed, in which the saturation factor is contained in adaptive laws. It was proved that the uniformly ultimately bounded (UUB) of trajectory tracking errors can be obtained. Finally, the effectiveness of the proposed trajectory tracking control approach was checked by simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:27:29Z
      DOI: 10.1177/01423312211004819
       
  • Fixed time steps discrete-time sliding mode consensus protocols for two
           degree of freedom helicopter systems
    • Authors: Keyurkumar Patel, Axaykumar Mehta
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents analysis of number of steps required for the consensus in a leader-following discrete multi-agent system (DMAS) with discrete-time sliding mode protocols designed by Gao’s reaching law and power rate reaching laws. The DMAS is configured for communication with a fixed, undirected graph topology having one leader and other agents as followers. The sufficient condition for global stability is established using the Lyapunov function in both the cases. The efficacy of both the protocols is compared in simulation for number of steps required for the consensus of a homogeneous multiple two degree of freedom helicopter systems where the pitch angle and its velocity and yaw angle and its velocity are used for consensus. The simulation results reveal that the consensus performance due to protocol with power rate reaching law outperforms the protocol with Gao’s reaching law.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:24:20Z
      DOI: 10.1177/01423312211004778
       
  • Estimation and rejection of sinusoidal disturbance with unknown frequency
           using cascade disturbance observer
    • Authors: Wen Xinyu, Zhang Junjie, Yao Xiuming
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A disturbance rejection approach is presented for a class of uncertain systems subject to sinusoidal disturbance with unknown frequency. The proposed disturbance estimation method includes two types of observers that are connected in cascade form. The disturbance property is excited through an auxiliary filter, and then a frequency factor observer is constructed to generate the information required by full-order state observer. Thus, with the disturbance and system state estimation values, the composite control structure including a cascade disturbance observer (CDO) and a robust feedback controller is designed. As a result, the uncertain system with unknown-frequency sinusoidal component can be controlled within the disturbance observer-based control (DOBC) framework, where the asymptotic stability performance can be guaranteed.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:22:39Z
      DOI: 10.1177/01423312211002799
       
  • Adaptive event-triggered fault detection for Markovian jump systems with
           network time-delays
    • Authors: Mengmeng Liu, Jinyong Yu, Yiming Sun, Jiahao Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the adaptive event-triggered fault detection (FD) problem is investigated for Markovian jump systems (MJSs) with network time-delays and data package dropouts. First, a novel event-triggered communication strategy with an adaptive threshold is introduced to screen the sampled signals and reduce the data releasing frequency. Consequently, the limited communication resources and network bandwidth are saved as much as possible. Second, since communication links between the plant and filter are considered to be unreliable, the effects of intermittent package dropouts phenomenon and network time-delays are taken into account simultaneously. By using time-delay system method, the network-induced phenomena, adaptive event-triggered strategy and MJSs are unified into a networked MJSs time-delay system. Then, sufficient conditions are developed such that the resulting residual system is mean-square exponentially stable with the desired [math] performance. Finally, a numerical example of the F-404 aircraft engine system is provided to illustrate the effectiveness and potential of the proposed design method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:21:04Z
      DOI: 10.1177/01423312211002591
       
  • A smooth optimized input shaping method for two-dimensional crane systems
           using Bezier curves
    • Authors: AbdulAziz Al-Fadhli, Emad Khorshid
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Conventional input shaping commands have been successfully employed to suppress residual vibration in the payload rest-to-rest transportation process. Most of these methods introduce an impractical large and sudden variation on the acceleration profile. This paper presents a new smooth command input with adjustable time length and limited jerks. The command input is generated from the trolley displacement using a Bezier curve function by adjusting the position of the control points, which were divided into boundary and intermedium points. The boundary control points are selected to accurately move the trolley to its desired position with zero velocity and acceleration at the closing motion. The positions of the intermedium points were optimized using a particle swarm scheme for reducing maneuvering time while suppressing the payload oscillations at the end of the process and satisfying physical system constraints. Several cases were discussed for fixed cable length, variable cable involving single and multi-hoisting mechanisms, and different maneuver times. Simulated results were validated experimentally on a laboratory size crane. The results demonstrated that the proposed input Bezier-curve shaper provides an effective, reliable, and practical technique to be used for the payload transportation process. Moreover, the proposed method can generate asymmetrical acceleration and deceleration motions, which cannot be achieved using existing smoother commands.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:19:13Z
      DOI: 10.1177/0142331221995305
       
  • Disturbance estimator-based switching function for discrete-time sliding
           mode control systems with control saturation
    • Authors: Haifeng Ma, Zhenhua Xiong, Yangmin Li, Zhanqiang Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a new disturbance estimator-based switching function (SF) is presented dedicated to discrete-time sliding mode control (DSMC) systems with disturbances and control saturation (CS). This SF is featured by an (n+1)th-order disturbance estimator, which utilizes n+1 past disturbance terms to attain accurate disturbance rejection. Moreover, an auxiliary state is integrated into the SF to address the CS problem. One uniqueness of the developed method is that it is capable of achieving the ideal quasi-sliding mode and produces a zero-convergence error of the SF under the influence of disturbances and CS, which is rarely realized in DSMC methods. In addition, system states dynamics is rigorously analysed adopting the Lyapunov technique. The feasibility and virtue of the designed results are verified by a numerical example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:17:12Z
      DOI: 10.1177/01423312211004791
       
  • Multi-unmanned aerial vehicle swarm formation control using hybrid
           strategy
    • Authors: Zain Anwar Ali, Han Zhangang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study proposes a novel hybrid strategy for formation control of a swarm of multiple unmanned aerial vehicles (UAVs). To enhance the fitness function of the formation, this research offers a three-dimensional formation control for a swarm using particle swarm optimization (PSO) with Cauchy mutant (CM) operators. We use CM operators to enhance the PSO algorithm by examining the varying fitness levels of the local and global optimal solutions for UAV formation control. We establish the terrain and the fixed-wing UAV model. Furthermore, it also models different control parameters of the UAV as well. The enhanced hybrid algorithm not only quickens the convergence rate but also improves the solution optimality. Lastly, we carry out the simulations for the multi-UAV swarm under terrain and radar threats and the simulation results prove that the hybrid method is effective and gives better fitness function.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-19T09:16:10Z
      DOI: 10.1177/01423312211003807
       
  • Design of an optimal preview controller for linear discrete-time periodic
           systems
    • Authors: Mengyuan Sun, Fucheng Liao, Jiamei Deng
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the preview tracking control problem for linear discrete-time periodic systems is considered. First, to overcome the difficulty arising from periodicity of the system, the linear discrete-time periodic system is transformed into an ordinary time-invariant system by lifting method. Secondly, the difference between a system state and its steady-state value is used to derive an augmented system instead of the usual difference between system states. Then, the preview controller for the augmented system is proposed by the preview control theory, which solves the preview tracking control problem for the periodic systems. Moreover, an integrator is introduced to ensure that the output can track the reference signal without static error. Finally, the obtained results are illustrated by the simulation examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-13T04:35:14Z
      DOI: 10.1177/01423312211002585
       
  • A novel hybrid grey wolf optimization algorithm and artificial neural
           network technique for stochastic unit commitment problem with uncertainty
           of wind power
    • Authors: C. Venkatesh Kumar, M. Ramesh Babu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The unit commitment (UC) is highly complex to solve the increasing integrations of wind farm due to intermittent wind power fluctuation in nature. This paper presents a hybrid methodology to solve the stochastic unit commitment (SUC) problem depending on binary mixed integer generator combination with renewable energy sources (RESs). In this combination, ON/OFF tasks of the generators are likewise included to satisfy the load requirement as for the system constraints. The proposed hybrid methodology is the consolidation of grey wolf optimization algorithm (GWOA) and artificial neural network (ANN), hence it is called the hybrid GWOANN (HGWOANN) technique. Here, the GWOA algorithm is used to optimizing the best combination of thermal generators depending on uncertain wind power, minimum operating cost and system constraints – that is, thermal generators limits, start-up cost, ramp-up time, ramp-down time, etc. ANN is utilized to capture the uncertain wind power events, therefore the system ensures maximal application of wind power. The combination of HGWOANN technique guarantees the prominent use of sustainable power sources to diminish the thermal generators unit operating cost. The proposed technique is implemented in MATLAB/Simulink site and the efficiency is assessed with different existing methods. The comparative analysis demonstrates that the proposed HGWOANN approach is proficient to solve unit commitment problems and wind integration. Here, the HGWOANN method is compared with existing techniques such as PSO, BPSO, IGSA to assess the overall performance using various metrics viz. RMSE, MAPE, MBE under 50 and 100 count of trials. In the proposed approach, the range of RMSE achieves 9.26%, MAPE achieves 0.95%, MBE achieves 1% in 50 count of trials. Moreover, in 100 count of trials, the range of RMSE achieves 7.38%, MAPE achieves 1.91%, MBE achieves 2.87%.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-13T04:31:52Z
      DOI: 10.1177/01423312211001987
       
  • Robust control of a DC-DC three-port isolated converter
    • Authors: Clauson SN Rios, Fabricio G Nogueira, Bismark C Torrico, Walter Barra Junior
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This work presents the design of state-feedback robust control law for a DC-DC three-port isolated converter, which interfaces a photovoltaic panel, a rechargeable battery, and an isolated output DC bus. First, the converter is represented through a state-space model that considers disturbances in both the photovoltaic and bidirectional (battery) input ports. The system is linearized around an average operational point, such that robust control techniques can be applied. Due to varying solar irradiation, battery charge, and load levels, the converter is subjected to step-like disturbances. The proposed controller is designed to maintain stabilization and voltage tracking performance in the presence of these disturbances. This approach is different from multiport control strategies usually employed in the literature, which are based on decentralized controllers that require the use of decoupling techniques that can lead to control problems. To ensure robustness, stabilization, and voltage tracking, an [math] approach with pole placement restrictions and based on linear matrix inequality (LMI) constraints is formulated and solved. Finally, the performance of the proposed controller has been verified via hardware-in-the-loop (HIL) experiments and compared with a decentralized control strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-12T07:17:14Z
      DOI: 10.1177/01423312211002928
       
  • Deep regression of convolutional neural network applied to resolved
           acceleration control for a robot manipulator
    • Authors: Yong-Lin Kuo, Shih-Chien Tang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a modified resolved acceleration control scheme based on deep regression of the convolutional neural network. The resolved acceleration control scheme can achieve precise motion control of robot manipulators by regulating the accelerations of the end-effector, and the conventional scheme needs the position and orientation of the end-effector, which are obtained through the direct kinematics of the robot manipulator. This scheme increases the computational loads and might obtain inaccurate position and orientation due to mechanical errors. To overcome the drawbacks, a camera is used to capture the images of the robot manipulator, and then a deep regression of convolutional neural network is imposed into the resolved acceleration control to obtain the position and orientation of the end-effector. The proposed approach aims to enhance the positioning accuracy, to reduce the computational loads, and to facilitate the deep regression in real-time control. In this study, the proposed approach is applied to a 3-DOF planar parallel robot manipulator, and the results are compared with those by the conventional resolved acceleration control and a visual servo-based control. The results show that those objectives are achieved. Furthermore, the robustness of the proposed approach is tested through only the partial image of the end-effector available, and the proposed approach still works functionally and effectively.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-12T07:15:38Z
      DOI: 10.1177/01423312211002795
       
  • Event-triggered adaptive control of a class of nonlinear systems with
           non-parametric uncertainty in the presence of actuator failures
    • Authors: H.R. Ghazisaeedi, M.S. Tavazoei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper deals with event-triggered adaptive tracking control of a class of nonlinear systems with non-parametric uncertainty and unknown control input direction, in the presence of actuator faults. The proposed event-triggered control method takes advantage of the radial basis function neural networks to approximate the non-parametric uncertainties. Moreover, this control method benefits from the Nussbaum-type function-based adaptation laws for simultaneously dealing with unknown input direction and actuator faults. Numerical simulation results confirm the efficiency of the proposed control method to confront the above mentioned limitations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-12T07:13:23Z
      DOI: 10.1177/01423312211002586
       
  • Road surface real-time detection based on Raspberry Pi and recurrent
           neural networks
    • Authors: Junyi Wang, Qinggang Meng, Peng Shang, Mohamad Saada
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper focuses on road surface real-time detection by using tripod dolly equipped with Raspberry Pi 3 B+, MPU 9250, which is convenient to collect road surface data and realize real-time road surface detection. Firstly, six kinds of road surfaces data are collected by utilizing Raspberry Pi 3 B+ and MPU 9250. Secondly, the classifiers can be obtained by adopting several machine learning algorithms, recurrent neural networks (RNN) and long short-term memory (LSTM) neural networks. Among the machine learning classifiers, gradient boosting decision tree has the highest accuracy rate of 97.92%, which improves by 29.52% compared with KNN with the lowest accuracy rate of 75.60%. The accuracy rate of LSTM neural networks is 95.31%, which improves by 2.79% compared with RNN with the accuracy rate of 92.52%. Finally, the classifiers are embedded into the Raspberry Pi to detect the road surface in real time, and the detection time is about one second. This road surface detection system could be used in wheeled robot-car and guiding the robot-car to move smoothly.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-12T06:58:52Z
      DOI: 10.1177/01423312211003372
       
  • Path tracking based on model predictive control with variable predictive
           horizon
    • Authors: Huiran Wang, Qidong Wang, Wuwei Chen, Linfeng Zhao, Dongkui Tan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Model predictive control is one of the main methods used in path tracking for autonomous vehicles. To improve the path tracking performance of the vehicle, a path tracking method based on model predictive control with variable predictive horizon is proposed in this paper. Based on the designed model predictive controller for path tracking, the response analysis of path tracking control system under the different predictive horizons is carried out to clarify the influence of predictive horizon on path tracking accuracy, driving comfort and real-time of the control algorithm. Then, taking the lateral offset, the steering frequency and the real-time of the control algorithm as comprehensive performance indexes, the particle swarm optimization algorithm is designed to realize the adaptive optimization for the predictive horizon. The effectiveness of the proposed method is evaluated via numerical simulation based on Simulink/CarSim and hardware-in-the-loop experiment on an autonomous driving simulator. The obtained results show that the optimized predictive horizon can adapt to the different driving environment, and the proposed path tracking method has good comprehensive performance in terms of path tracking accuracy of the vehicle, driving comfort and real-time.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T12:03:22Z
      DOI: 10.1177/01423312211003809
       
  • Predictive extended state observer-based robust control for uncertain
           linear systems with experimental validation
    • Authors: Sushant N Pawar, Rajan H Chile, Balasaheb M Patre
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper describes a predictive extended state observer-based robust control for uncertain process control applications. The technique discussed in the article uses the extended state observer (ESO) that can estimate the dynamics of the system as well as total disturbance encountered in the system. The disturbances, parametric uncertainties associated with the processes are treated as an extended state variable to be estimated in real-time using ESO. With the implementation of a predictive algorithm with an ESO, the proposed control structure extends its applicability to time-delayed higher-order processes. The proposed control technique utilizes the simple first-order modified predictive ESO even in the case of higher-order processes. The novel predictive ESO is able to obtain a delay less estimation of total disturbance as compared with existing normal ESO. Also, novel predictive ESO maintains its stability margin in presence of time delay as well provides better response as compared with normal ESO. Numerical simulations show that the proposed scheme provides a significant improvement in transient response as compared with internal model control-based proportional-integral-derivative (IMC-PID) control. The proposed scheme requires less knowledge of the process as compared with the IMC-PID structure. The implementation of the proposed control is tested on a real-life single tank level control system. Because of its merit, the suggested technique can be used as automatic for online tuning, as it is less reliant on the process model.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T12:01:41Z
      DOI: 10.1177/01423312211002599
       
  • Quadrotor UAV attitude stabilization using fuzzy robust control
    • Authors: David Lara Alabazares, Abdelhamid Rabhi, Claude Pegard, Fernando Torres Garcia, Gerardo Romero Galvan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a robust controller for attitude stabilization of a small quadrotor helicopter is developed. The TS (Takagi-Sugeno) fuzzy model approach and the [math] robust control are combined to produce the proposed algorithm. Besides, disturbances and parametric uncertainties are considered. First, the nonlinear model of the vehicle is linearized around several operating points to obtain the representation of a TS fuzzy model, which represents the nonlinearity of the system dynamics. Then, a robust fuzzy controller is synthesized which guarantees desired control performances. The given controller is designed using numerical tools such as linear matrix inequalities (LMI). Finally, simulation results and real-time experiments are presented to validate the performance of the proposed scheme to robustly stabilize the quadrotor dynamics at the desired reference.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T11:59:59Z
      DOI: 10.1177/01423312211002588
       
  • An improved sliding-mode observer-based equivalent-input-disturbance
           approach for permanent magnet synchronous motor drives with faults in
           current measurement circuits
    • Authors: Gang Huang, Wei Huang, Zhengtan Li, Jiajun Li, Jing He, Changfan Zhang, Kaihui Zhao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The reliability of permanent magnet synchronous motor (PMSM) systems is very important in high-precision industrial drives. However, disturbance or sensor fault may cause the performance degradation of the system. This paper presents an improved sliding-mode-observer (SMO)-based equivalent-input-disturbance (EID) approach for the rejection of faults in current measurement circuits of a PMSM drive. A system model, which contains faults in current measurement circuits, is first constructed by using EIDs in control input circuits. Then, an improved SMO is designed to estimate the equivalent-input-faults. The effect of the faults on the system is rejected based on the EID theory. Moreover, the global stability and convergence analysis is also provided. Experiments and comparisons demonstrate the effectiveness of the method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T11:57:53Z
      DOI: 10.1177/01423312211002584
       
  • Extended state Kalman filter-based path following control of underactuated
           autonomous vessels
    • Authors: Yi Zhang, Wenchao Xue, Li Sun, Jiong Shen
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Path following control of underactuated autonomous vessels remains a challenging issue in recent years due to its inherent underactuation and nonlinearities as well as the widely existing disturbances in the marine environment. In order to accommodate all the difficulties simultaneously, a novel extended state Kalman filter, which adopts the idea of extended state observer in estimating and compensating system lumped disturbance and optimizes the filter gain in a real-time fashion using Kalman filter technique, is constructed to estimate system states and disturbances in the presence of model uncertainties and measurement noise. Based on the estimated states and disturbances, an enhanced model predictive controller is proposed to steer the underactuated autonomous vessels along a predefined path at a desired speed after considering system state and input constraints. Simulation results have proved the superiority of extended state Kalman filter over traditional extended state observer and extended Kalman filter under various disturbance and noise scenarios. Moreover, the comparison results with conventional proportion-integration-differentiation controller have demonstrated the feasibility and efficacy of the proposed extended state Kalman filter-based model predictive controller in both set-point tracking and disturbance rejection.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T11:52:32Z
      DOI: 10.1177/0142331221994410
       
  • Sliding mode projective synchronization for fractional-order coupled
           systems based on network without strong connectedness
    • Authors: Xin Meng, Baoping Jiang, Cunchen Gao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper considers the Mittag-Leffler projective synchronization problem of fractional-order coupled systems (FOCS) on the complex networks without strong connectedness by fractional sliding mode control (SMC). Combining the hierarchical algorithm with the graph theory, a new SMC strategy is designed to realize the projective synchronization between the master system and the slave system, which covers the globally complete synchronization and the globally anti-synchronization. In addition, some novel criteria are derived to guarantee the Mittag-Leffler stability of the projective synchronization error system. Finally, a numerical example is given to illustrate the validity of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-05T08:29:38Z
      DOI: 10.1177/01423312211000924
       
  • Experimental measurement of force, torque control and vibration absorber
           system for intraoperative tele-operated robotic-assisted femoral shaft
           drilling using air-controlled soft balloon damper
    • Authors: Orelaja Oluseyi Adewale, Donghua Shen, Xingsong Wang, Lan Li, Tianzheng Zhao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The use of closed intramedullary nailing fixation and drilling technique is a very common, safe and standard method for treating diaphyseal femoral fractures. However, it has several demerits such as high cutting forces and torque during drilling and this could cause high vibration and result in cracks, tool breakage and necrosis of the already fractured bone. This paper presents the measure of force, torque control and vibration absorber system for intra-operative tele-operated robotic-assisted femoral shaft drilling using air-controlled balloon damper experimentally, since bone is surrounded by soft tissues that can cause more severe injury to the tissue due to high traction force. Simulated femur bone and tissue are used for this experiment. A sensor-based model clamping system embedded with controlled pressurized air balloon to damp drilling vibration was developed; the drilling forces were monitored by the force sensor attached to the end robot effector, while the resulted vibration was measured by contact sensor during the entire surgical drilling. Forces and vibration caused by drilling forces acting on the bone at varying damper pressure at varying spindle drill speed were obtained using (EMS 309 data acquisition and then the data were processed using MATLAB R2015b. The vibration results were processed with wavelet packet transform (WPT) using Fast Fourier transform to analyze the vibration signals, frequencies and amplitude of the vibration. This modeled control system is a good concept, results clearly justify that soft clamping fixation system can be employed to reduce force, torque and vibration without causing harm to the delicate surrounding tissues. This control measures can provide surgeons with real-time information which can assist them in repositioning and repair of fracture bone within control and safe margins. It is believed that this idea will have greater future developmental prospect.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-01T09:23:13Z
      DOI: 10.1177/01423312211000928
       
  • Discrete-time estimation of switched stochastic polynomial systems and its
           application to reconstruction of induction motor variables
    • Authors: Miguel Hernandez–Gonzalez, Michael Basin, Oleg Stepanov
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents a solution to the filtering problem for a class of stochastic discrete-time nonlinear polynomial systems with switching in the state equation over linear observations and its application to a mechatronic system. The switching in the state equation is performed between two different nonlinear functions according to a sequence of independent Bernoulli random variables that take the quantities of zero and one. The mean-square filtering solution is obtained for a general nonlinear discrete-time polynomial system and a finite-dimensional system of filtering equations is then obtained for a second degree polynomial system as a particular case. The mean-square estimates of polynomial state terms are expressed as functions of the estimate and covariance matrix. Finally, some numerical simulations are carried out to reconstruct the variable states given a vector output measurement for a linear system, a second degree polynomial system, and an induction motor model to show effectiveness of the proposed algorithm. The proposed method is compared with an extended Kalman filter-based algorithm for discrete-time switched nonlinear systems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-24T12:11:44Z
      DOI: 10.1177/0142331221998856
       
  • Configuration optimization of photogrammetry system based on spectral
           radius for on-orbit measurement
    • Authors: Wei Wang, Wangbai Pan, Dike Hu, Guoan Tang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Non-contact optical measurement is a potential approach to on-orbit vibration measurement for flexible appendages, providing dynamic information for spacecraft control system. Binocular photogrammetry system is a practical configuration to achieve this measurement. In this paper, optimization approach and strategy for configuration parameters of this system are raised. Measurement matrix is specially defined to obtain the objective function for the optimization. Successive linear programming algorithm is used for optimization iteration. Transient responses of flexible appendages calculated by finite element model and corresponding images generated by OpenGL help to achieve this simulation-based optimization. The feasibility and effectiveness of the optimization are verified both by numerical study and experiment. Error analysis of the optimal system reveals great improvement in accuracy and robustness after optimization. This optimization is a promising approach to designing the configuration of binocular photogrammetry system and helping to achieve reliable on-orbit dynamic measurement results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-23T11:31:50Z
      DOI: 10.1177/0142331221991763
       
  • Path planning of surgical needle: A new adaptive intelligent particle
           swarm optimization method
    • Authors: Zhen Tan, Hua-Geng Liang, Dan Zhang, Qing-Guo Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Percutaneous puncture interventional therapy is an important method for pathological examination, local anesthesia, and local drug delivery in modern clinics. Due to the existence of complex obstacles such as nerves, arteries, bones and so on in the puncture path, it is a challenging work to design the optimal path for surgical needle. In this paper, we propose a new path planning method based on the adaptive intelligent particle swarm optimization (PSO) algorithm with parameter adjustment mechanism. First, force and motion analysis are carried out on the bevel-tip flexible needle after piercing into human tissues, the motion model of the needle and the spatial transformation model of puncture route in three-dimensional space are obtained, respectively. Then, a multi-objective function is established, which includes puncture path length function, puncture error function and collision detection function. Finally, the optimal puncture path is obtained based on the adaptive intelligent PSO algorithm. The simulation results show that the newly proposed path planning method has higher efficiency, better adaptability to complex environments and higher accuracy than other path planning methods in literature.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-22T10:06:40Z
      DOI: 10.1177/0142331221998832
       
  • Motion planning approach for car-like robots in unstructured scenario
    • Authors: Xuehao Sun, Shuchao Deng, Tingting Zhao, Baohong Tong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      When a car-like robot travels in an unstructured scenario, real-time motion planning encounters the problem of unstable motion state in obstacle avoidance planning. This paper presents a hybrid motion planning approach based on the timed-elastic-band (TEB) approach and artificial potential field. Different potential fields in an unstructured scenario are established, and the real-time velocity of the car-like robot is planned by using the conversion function of the virtual potential energy of the superimposed potential field and the virtual kinetic energy of the robot. The optimized TEB approach plans the local optimal path and solves the problems related to the local minimum region and non-reachable targets. The safety area of the dynamic obstacle is constructed to realize turning or emergency stop obstacle avoidance, thereby effectively ensuring the safety of the car-like robot in emergency situations. The simulation experiments show that the proposed approach has superior kinematic characteristics and satisfactory obstacle avoidance planning effects and can improve the motion comfort and safety of the car-like robot. In the practical test, the car-like robot moves stably in a dynamic scenario, and the proposed approach satisfies the actual application requirements.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-01T08:16:24Z
      DOI: 10.1177/0142331221994393
       
  • RFID multi-tag dynamic detection measurement based on conditional
           generative adversarial nets and YOLOv3
    • Authors: Lin Li, Xiaolei Yu, Zhenlu Liu, Zhimin Zhao, Ke Zhang, Shanhao Zhou
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The quality of multi-tag imaging greatly affects the effective detection of multi-tag. When multi-tag moves rapidly, the image may have serious dynamic blur, and tags can not be detected efficiently. In previous work, it is generally assumed that blur kernel and noise stationary to improve image quality. However, the dynamic deblurring of Radio Frequency Identification (RFID) multi-tag imaging is an ill-posed inverse problem. In this paper, firstly, blur-sharp multi-tag image pairs are made by superimposing and averaging the adjoin random frames. Then, we propose blind deblurring for dynamic RFID multi-tag imaging based on conditional generative adversarial nets (CGANs), which adds perceptual loss and content loss to generator to make image sharper. Finally, tags are detected by YOLOv3 in real time in end-to-end manner. Experimental results demonstrate that PSNR is at least 0.56dB higher and speed is at least 31.25 % faster than that of the current improved convolution neural networks (CNN). CGANs can remove image blur better, which has great superiority in the field of dynamic multi-tag imaging. In addition, YOLOv3 detects multi-tag quickly, thereby improving the detection accuracy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-22T12:57:40Z
      DOI: 10.1177/0142331221991765
       
  • Quadratic programming-based cooperative adaptive cruise control under
           uncertainty via receding horizon strategy
    • Authors: Serdar Coskun, Cong Huang, Fengqi Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Cooperative longitudinal motion control can greatly contribute to safety, mobility, and sustainability issues in today’s transportation systems. This article deals with the development of cooperative adaptive cruise control (CACC) under uncertainty using a model predictive control strategy. Specifically, uncertainties arising in the system are presented as disturbances acting in the system and measurement equations in a state-space formulation. We aim to design a predictive controller under a common goal (cooperative control) such that the equilibrium from initial condition of vehicles will remain stable under disturbances. The state estimation problem is handled by a Kalman filter and the optimal control problem is formulated by the quadratic programming method under both state and input constraints considering traffic safety, efficiency, as well as driving comfort. In the sequel, adopting the CACC system in four-vehicle platoon scenarios are tested via MATLAB/Simulink for cooperative vehicle platooning control under different disturbance realizations. Moreover, the computational effectiveness of the proposed control strategy is verified with respect to different platoon sizes for possible real-time deployment in next-generation cooperative vehicles.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-22T11:52:10Z
      DOI: 10.1177/0142331221992741
       
  • A fast-moving horizon estimation method based on the symplectic
           pseudospectral algorithm
    • Authors: Xinwei Wang, Jie Liu, Haijun Peng, Xudong Zhao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a fast-moving horizon state estimation algorithm for nonlinear continuous systems with measurement noises and model disturbances is developed. The optimization problem required to be solved at each sampling instant is formulated into a backward nonlinear optimal control problem over the finite past. Once prior knowledge of the observed system is available, constraints can be further imposed. The highly efficient and accurate symplectic pseudospectral algorithm is taken as the core solver, which leads to the symplectic pseudospectral moving horizon estimation (SP-MHE) method. The developed SP-MHE is first evaluated by numerical simulations for a hovercraft. Then the developed method is extended to parameter estimation and applied to a chaotic system with an unknown parameter. Simulation results show that the SP-MHE can generate accurate estimations even under large sampling periods or large noise where regular filters fail. In addition, the SP-MHE exhibits excellent online efficiency, suggesting it can be used for scenarios where the sampling period is relatively small.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-22T01:33:02Z
      DOI: 10.1177/0142331221992691
       
  • Scanning control based on real-time contact force feedback for ultrasonic
           thickness measurement
    • Authors: Haibo Liu, Xu Li, Qile Bo, Meng Lian, Te Li, Yongqing Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An effective contact force control strategy is of great significance for accurate and stable ultrasonic thickness on-machine measurement. However, it is difficult to adjust the contact force dynamically due to the uncertainty of the geometric characteristics of the measured workpiece. In this paper, a contact force control method based on the combination of adaptive impedance controller and sliding mode variable structure position controller is proposed. First, the control process with the force tracking impedance control and a normal contact force calculation model is established. Then, a force-position conversion model and a sliding mode variable structure controller are proposed. Further, a simulation with a typical S-shaped measured surface is given to show that the algorithm for controlling contact force can achieve good real-time tracking performance and has stronger robustness than traditional methods. Finally, an arc-shaped aluminum alloy thin-wall part thickness is sampled along the scan trajectory to verify the effectiveness of the algorithm. The experimental results show that the proposed algorithm for controlling contact force can quickly adjust the measuring device to the target position and maintain the stability of the normal contact force to ensure the accuracy of ultrasonic thickness on-machine measurement.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-16T06:06:12Z
      DOI: 10.1177/0142331221990924
       
  • A visual terrain classification method for mobile robots’ navigation
           based on convolutional neural network and support vector machine
    • Authors: Wanli Wang, Botao Zhang, Kaiqi Wu, Sergey A Chepinskiy, Anton A Zhilenkov, Sergei Chernyi, Aleksandr Yu Krasnov
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a hybrid method based on deep learning is proposed to visually classify terrains encountered by mobile robots. Considering the limited computing resource on mobile robots and the requirement for high classification accuracy, the proposed hybrid method combines a convolutional neural network with a support vector machine to keep a high classification accuracy while improve work efficiency. The key idea is that the convolutional neural network is used to finish a multi-class classification and simultaneously the support vector machine is used to make a two-class classification. The two-class classification performed by the support vector machine is aimed at one kind of terrain that users are mostly concerned with. Results of the two classifications will be consolidated to get the final classification result. The convolutional neural network used in this method is modified for the on-board usage of mobile robots. In order to enhance efficiency, the convolutional neural network has a simple architecture. The convolutional neural network and the support vector machine are trained and tested by using RGB images of six kinds of common terrains. Experimental results demonstrate that this method can help robots classify terrains accurately and efficiently. Therefore, the proposed method has a significant potential for being applied to the on-board usage of mobile robots.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-15T05:41:00Z
      DOI: 10.1177/0142331220987917
       
  • Adaptive finite-time neural backstepping control for
           multiple-input–multiple-output uncertain nonlinear systems with full
           state constraints
    • Authors: Yan Wei, Pingfang Zhou, Yueying Wang, Dengping Duan, Jiwei Tang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the issue of finite-time tracking control for multiple-input–multiple-output nonlinear systems subject to uncertainties and full state constraints. To deal with full state constraints directly, integral barrier Lyapunov functionals (iBLF) are introduced. By using finite-time stability theory, an iBLF-based adaptive finite-time neural control scheme is presented. To solve the problem of “explosion of complexity” in the design of traditional backstepping control, a new finite-time convergent differentiator is presented. Through stability analysis, all closed-loop signals are proved to be semi-globally uniformly ultimately bounded, the finite time convergence can be guaranteed, and the state constraints are never violated. Finally, the attitude tracking simulations for an autonomous airship are conducted to verify the effectiveness of the proposed scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-08T06:09:30Z
      DOI: 10.1177/0142331221989121
       
  • Method for acquiring time of flight from high aliasing signal in heat
           exchange fouling ultrasonic testing
    • Authors: Xia Li, Lingfang Sun, Jing Li, Heng Piao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In heat exchange fouling ultrasonic testing, the time-domain signal waveform often contains high aliasing due to small fouling thickness or high order echo interference, and so forth. This paper studies the method of acquiring time of flight from heat exchange fouling ultrasonic testing signal with high aliasing and presents the method that combined the Wiener deconvolution and high order cumulative spectrum estimation. For reference signal distortion problem, which may exist in real application, an iterative correction process is introduced in the form of Incremental Wiener algorithm. Simulation and experimental results show that the proposed method has better anti-noise ability, better time of flight accuracy and practicability.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-01T01:56:40Z
      DOI: 10.1177/0142331221989119
       
  • Study of B-spline collocation method for solving fractional optimal
           control problems
    • Authors: Yousef Edrisi-Tabriz, Mehrdad Lakestani, Mohsen Razzaghi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this article, a class of fractional optimal control problems (FOCPs) are solved using a direct method. We present a new operational matrix of the fractional derivative in the sense of Caputo based on the B-spline functions. Then we reduce the solution of fractional optimal control problem to a nonlinear programming (NLP) one, where some existing well-developed algorithms may be applied. Numerical results demonstrate the efficiency of the presented technique.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-29T05:36:12Z
      DOI: 10.1177/0142331220987537
       
  • Defect identification in magnetic tile images using an improved nonlinear
           diffusion method
    • Authors: Mohamed Ben Gharsallah, Ezzedine Ben Braiek
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Visual inspection of surface defects is a crucial step in the magnetic tile manufacturing process. Magnetic tile images suffer from a non-uniform illumination, texture and noise that disperse irregularly in flawless image areas. As a result, common edge detection and threshold segmentation techniques fail to identify these kinds of defects. In this work, we present a robust algorithm for defect identification in magnetic tile images. The proposed method is based on a new anisotropic diffusion filtering model. Unlike traditional anisotropic diffusion models that take into account only gradient magnitude information, the proposed model combines together gradient magnitude and a new local difference image feature. The aim is to remove bright shapes and undesirable artifacts in the faultless region in magnetic tile images. In addition, the method activates a smoothing process in the flawless region to homogenize the background and simultaneously a sharpening in the defect boundaries to highlight anomalies. Experimental results on a number of magnetic tiles samples containing different types of defects have demonstrated the efficiency of the proposed diffusion method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-25T05:39:15Z
      DOI: 10.1177/0142331220982220
       
  • Multimodal data fusion framework enhanced robot-assisted minimally
           invasive surgery
    • Authors: Wen Qi, Hang Su, Ke Fan, Ziyang Chen, Jiehao Li, Xuanyi Zhou, Yingbai Hu, Longbin Zhang, Giancarlo Ferrigno, Elena De Momi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The generous application of robot-assisted minimally invasive surgery (RAMIS) promotes human-machine interaction (HMI). Identifying various behaviors of doctors can enhance the RAMIS procedure for the redundant robot. It bridges intelligent robot control and activity recognition strategies in the operating room, including hand gestures and human activities. In this paper, to enhance identification in a dynamic situation, we propose a multimodal data fusion framework to provide multiple information for accuracy enhancement. Firstly, a multi-sensors based hardware structure is designed to capture varied data from various devices, including depth camera and smartphone. Furthermore, in different surgical tasks, the robot control mechanism can shift automatically. The experimental results evaluate the efficiency of developing the multimodal framework for RAMIS by comparing it with a single sensor system. Implementing the KUKA LWR4+ in a surgical robot environment indicates that the surgical robot systems can work with medical staff in the future.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-18T09:37:58Z
      DOI: 10.1177/0142331220984350
       
  • Support vector machine and its difficulties from control field of view
    • Authors: Maryam Yalsavar, Paknoosh Karimaghaei, Akbar Sheikh-Akbari, Pancham Shukla, Peyman Setoodeh
      First page: 1833
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The application of the support vector machine (SVM) classification algorithm to large-scale datasets is limited due to its use of a large number of support vectors and dependency of its performance on its kernel parameter. In this paper, SVM is redefined as a control system and iterative learning control (ILC) method is used to optimize SVM’s kernel parameter. The ILC technique first defines an error equation and then iteratively updates the kernel function and its regularization parameter using the training error and the previous state of the system. The closed loop structure of the proposed algorithm increases the robustness of the technique to uncertainty and improves its convergence speed. Experimental results were generated using nine standard benchmark datasets covering a wide range of applications. Experimental results show that the proposed method generates superior or very competitive results in term of accuracy than those of classical and state-of-the-art SVM based techniques while using a significantly smaller number of support vectors.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-25T12:34:53Z
      DOI: 10.1177/0142331220977436
       
  • Soft sensor hybrid model of dynamic liquid level for sucker rod pump oil
           wells
    • Authors: Bingjun Chen, Xianwen Gao
      First page: 1843
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The measurement of the dynamic liquid level is of great importance during the oil-producing process of rod pumping wells. It may affect the production of oil fields and motor efficiency. However, the dynamic liquid level is difficult to detect because of the circumstances in the downhole of rod pump wells. In this paper. Firstly, according to the working principles of the sucker rod pump, the mechanical models of the pumping motor and four-bar linkage mechanism are respectively built. Secondly, for the underground frictions, a mechanical model based on the energy conservation equation is built and then the mechanism model is built between the dynamic liquid level and power of the motor. To improve the accuracy of the mechanism model, a novel method based on an artificial fish swarm algorithm optimization Gaborc-kernel extreme learning machine is used to establish a soft sensor dynamic liquid level error compensation model. The mechanism model is paralleled with the soft sensor model to establish a hybrid model of dynamic liquid level. Eventually, the AFSA-Gaborc-KELM soft sensor hybrid model is verified by using the oil dataset collected from the electrical parameter acquisition equipment. This hybrid model is compared with some other models. In the comparison, the proposed hybrid model has better performance and prediction accuracy for the dynamic liquid level than the BP hybrid model, GA-ELM hybrid model, and LSSVM hybrid model.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-15T05:37:19Z
      DOI: 10.1177/0142331220979498
       
  • Robust finite frequency [math] control for Lipschitz nonlinear systems
    • Authors: Wajdi Saad, Anis Sellami
      First page: 1858
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the [math] control problem for Lipschitz nonlinear systems in the finite-frequency domain. Both parameter uncertainties and external disturbances are considered. In contrast to existing full-frequency methods, the proposed approach takes into account of the frequency information of disturbances during the design proceeding. Sufficient analysis conditions for the closed-loop system are firstly derived. Then, synthesis conditions are formulated in terms of linear matrix inequalities (LMIs). In fact, the control gain is designed to attenuate the influence of disturbances in different frequency ranges (low, middle and high). Finally, the model of the Chua circuit is used to validate the effectiveness of the proposed finite-frequency approach and to prove its superiority compared to the full-frequency counterpart.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-11T07:55:24Z
      DOI: 10.1177/0142331220981326
       
  • Variational method-based distributed optimal guidance laws for
           multi-attackers’ simultaneous attack
    • Authors: Xiaoqian Wei, Jianying Yang, Xiangru Fan
      First page: 1868
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      To solve the problem of cooperative encirclement and simultaneous attack of multiple unmanned aerial vehicles, variational method and Hamiltonian optimization are utilized to design an optimal attack trajectory of multiple attackers pursuing a single target that has fixed initial relative state, fixed final relative state and fixed duration of the attack under condition that the acceleration of the target being estimable. When terminal relative state and attack duration are unknown, online calculation algorithm is used to compute a chain of key intermediate points to create the guidance law and ensure successful deliverance of multiple attackers’ simultaneous attack of the target. The only requirement for the multi-attacker communication network is that it contains a directed spanning tree. The guidance laws can function properly as long as one or more attacker can observe the target. The novel guidance laws practicability are verified by simulation results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-11T07:59:46Z
      DOI: 10.1177/0142331220981430
       
  • Adaptive tracking control of stochastic nonlinear systems with unknown
           time-varying powers
    • Authors: Huijuan Li, Wuquan Li, Jianzhong Gu
      First page: 1880
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the adaptive output tracking problem for a class of high-order stochastic nonlinear systems with unknown time-varying powers and nonlinear parameterized uncertainties. By using the parameter separation technique and adding a power integrator design method, an adaptive controller with upper and lower bounds of the unknown time-varying power is successfully designed to guarantee that all the states of the closed-loop system are bounded in probability and the output tracking error can be regulated into a small neighborhood of the origin in probability. Finally, a simulation example is provided to illustrate the effectiveness of the designed controllers.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-18T09:31:16Z
      DOI: 10.1177/0142331220982231
       
  • Aperiodic sampled-data control of distributed networked control systems
           with time-delay
    • Authors: Kritika Bansal, Pankaj Mukhija
      First page: 1891
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a hybrid aperiodic sampled-data mechanism for the control of interconnected subsystems with time-delay. The proposed aperiodic sampled-data mechanism comprises of two stages. In the first stage, the next sampling instant for each subsystem is computed using self-triggering strategy. Thereafter, in the second stage, an event-triggering condition is checked at these sampling instants for each subsystem and signal is transmitted to the controller only if the event-triggering condition is violated. Further, to reduce the computational complexity involved in the proposed triggering mechanism, another triggering mechanism with integrated event-triggering and self-triggering is developed. Also, an upper bound on delay for each subsystem is computed to ensure the stability of distributed networked control system. The results proposed are validated using a simulation example. A comparison of the proposed technique with other triggering mechanisms in terms of sampling instants, number of transmissions to the controller, maximum delay bound and other performance measures is drawn through simulation example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-18T09:40:36Z
      DOI: 10.1177/0142331220982504
       
  • Optimal model predictive rejection control for nonlinear parabolic trough
           collector with lumped disturbances
    • Authors: Xian-hua Gao, Shangshang Wei, Zhi-gang Su
      First page: 1903
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      It is challenging and crucial to achieve unbiased tracking control for parabolic trough collector field as it is vulnerable to various types of disturbances or uncertainties such as unmeasured external disturbances, parameter perturbation and model mismatch. To solve this issue, an optimal model predictive rejection control strategy is put forward in a composite designed manner, in which all disturbances/uncertainties are dealt with as lumped disturbances. A generalized extended state observer is firstly employed to estimate the lumped disturbances, and then a feedback controller is devised based on optimal model predictive control to compensate the influences of the lumped disturbances on output. Stability analysis of the closed-loop system has been presented. It shows that the proposed composite controller can track given references without offset in the presence of lumped disturbances while not sacrificing its nominal performance in the absence of disturbances. Simulations conducted on a numerical example and a practical application for parabolic trough collector validate our conclusions.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-25T05:40:34Z
      DOI: 10.1177/0142331220983651
       
  • An observer-based H∞ linear parameter varying controller for time
           delayed linear parameter varying systems using dilated linear matrix
           inequalities and Wirtinger inequality
    • Authors: Mohamed Hechmi Bouazizi
      First page: 1915
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, we give a method for the design of linear parameter varying (LPV) observers in order to perform an LPV time delayed state feedback control for LPV systems with time varying delay. We derive some tractable analysis and synthesis conditions expressed in terms of linear matrix inequalities (LMIs). We show how it is possible to reduce significantly the conservatism of the quadratic approach by using parameter dependent Lyapunov-Krasovskii functional and LMI dilation techniques jointed to the Wirtinger integral inequality.We also present a method that makes it possible to do without the separation principle when determining the observer and the state feedback parameters. The synthesis problem is formulated without this principle. A numerical example is provided to illustrate the effectiveness of our approach that leads to a better H∞ level compared with other results, from literature, for the same example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-27T07:44:26Z
      DOI: 10.1177/0142331220983629
       
  • Fixed-time tracking control for two-link rigid manipulator based on
           disturbance observer
    • Authors: Heli Gao, Mou Chen
      First page: 1924
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the fixed-time disturbance estimate and tracking control for two-link manipulators subjected to external disturbance. A fixed-time extended-state disturbance observer (FxTESDO) is proposed by improving the extended state observer. Also, a fixed-time inverse dynamics tracking control (FxTIDTC) scheme based on the FxTESDO is given for two-link manipulators. The fixed-time convergence of the FxTESDO and FxTIDTC is proved by the Lyapunov stability theory and with the aid of the bi-limit homogeneous technique. Numerical simulations are employed to illustrate the effectiveness of the proposed FxTIDTC.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-27T07:46:01Z
      DOI: 10.1177/0142331220983637
       
  • Adaptive control based on Barrier Lyapunov function for a class of
           full-state constrained stochastic nonlinear systems with dead-zone and
           unmodeled dynamics
    • Authors: Fei Shen, Xinjun Wang, Xinghui Yin
      First page: 1936
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the problem of adaptive control based on Barrier Lyapunov function for a class of full-state constrained stochastic nonlinear systems with dead-zone and unmodeled dynamics. To stabilize such a system, a dynamic signal is introduced to dominate unmodeled dynamics and an assistant signal is constructed to compensate for the effect of the dead zone. Dynamic surface control is used to solve the “complexity explosion” problem in traditional backstepping design. Two cases of symmetric and asymmetric Barrier Lyapunov functions are discussed respectively in this paper. The proposed Barrier Lyapunov function based on backstepping method can ensure that the output tracking error converges in the small neighborhood of the origin. This control scheme can ensure that semi-globally uniformly ultimately boundedness of all signals in the closed-loop system. Two simulation cases are proposed to verify the effectiveness of the theoretical method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-27T07:46:20Z
      DOI: 10.1177/0142331220985637
       
  • Stabilization for a class of delayed switched inertial neural networks via
           non-reduced order method
    • Authors: Xuan Chen, Dongyun Lin
      First page: 1949
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper tackles the issue of global stabilization for a class of delayed switched inertial neural networks (SINN). Distinct from the frequently employed reduced-order technique, this paper studies SINN directly through non-reduced order method. By constructing a novel Lyapunov functional and using Barbalat Lemma, sufficient conditions for the global asymptotic stabilization issue and global exponential stabilization issue of the considered SINN are established. Numerical simulations further confirm the feasibility of the main results. The comparative research shows that global stabilization results of this paper complement and improve some existing work.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-18T09:42:37Z
      DOI: 10.1177/0142331220985944
       
  • Adaptive event-triggered control for master-slave switched systems subject
           to attacked state-dependent switching law
    • Authors: Lingcong Nie, Xindi Xu, Yan Li, Weiyu Jiang, Yiwen Qi, Yanhui Liu
      First page: 1958
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates adaptive event-triggered [math] control for network-based master-slave switched systems subject to actuator saturation and data injection attacks. It is an important and unrecognised issue that the switching signal is affected from both event-triggering scheme and network attacks. An adaptive event-triggering scheme is proposed that can adjust the triggering frequency through a variable threshold based on system performance. Furthermore, considering the impacts of transmission delays and actuator saturation, an event-triggered time-delay error switched system is developed. Subsequently, by utilizing piecewise Lyapunov functional technique, sufficient conditions are derived to render the time-delay error switched system to have an [math] performance level. In particular, the coupling between switching instants and data updating instants is analyzed during the system performance analysis. Moreover, sufficient conditions for the desired state-feedback controller gains and event-triggering parameter are presented. Finally, a numerical example is given to verify the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-27T07:54:07Z
      DOI: 10.1177/0142331220985945
       
  • Adaptive fuzzy backstepping control of underactuated multi-cable parallel
           suspension system with tension constraint
    • Authors: Naige Wang, Guohua Cao
      First page: 1971
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Multi-cable parallel suspension system (MCPSS) is designed to lift a heavy object with rapid development of deep resources exploitation. An adaptive fuzzy backstepping control strategy combining with nonlinear disturbance observer is studied to synthetically control the posture for the underactuated MCPSS with tension constraint in this article. Firstly, a theoretical modelling of the MCPSS with boundary constraints is derived by the extended Hamilton’s Principle. Secondly, the parameter uncertainties and time-varying disturbances are compensated by the fuzzy system and nonlinear disturbance observer, respectively. Thirdly, an adaptive fuzzy backstepping feedback controller based on the reference model is proposed to suppress vibration and control posture of the suspension platform. Finally, an Automatic Dynamic Analysis of Mechanical Systems (ADAMS) simulation and a numerical calculation are used to illustrate the theoretical model and the proposed control performance.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-27T07:56:46Z
      DOI: 10.1177/0142331220985947
       
  • Stability of switched Markovian jump systems with time-varying generally
           bounded transition rates
    • Authors: Dunke Lu, Xiaohang Li
      First page: 1985
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper addresses the exponential mean-square stability for a kind of switched Markovian jump systems, which have time-varying generally bounded transition rates and mode-dependent time delay. Since these transition rates are time-varying and generally bounded, they turn out to be more practical. In fact, those existing transition rates can be treated as special cases of the proposed ones in this paper. By constructing a new Lyapunov-Krasovskii function, sufficient conditions in a tractable form are derived for the exponential mean-square stability of the considered systems. For good measure, a numerical example is given to show the efficiency and potential of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-01-27T08:00:51Z
      DOI: 10.1177/0142331220987536
       
  • The use of magnetostrictive intelligent sensors for fault tolerant control
           of induction motors with energy harvesting principle
    • Authors: Meddad Mounir, Eddiai Adil, Chakhchaoui Nabil, Idiri Mohamed
      First page: 1996
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Asynchronous machines are omnipresent in automated production systems, due to their robustness and ease of use. These electric motors, however, also concede faults (e.g. short-circuit between turns) leading to unplanned stoppages. Defects with their effects are reflected in the magnitudes of the motors, mainly in flux, current, speed and torque. Our research work in this article presents a contribution of a new approach to the fault tolerant control. This simple and efficient method based solely on the measurement of the electrical energy applied by the magnetostrictive material requires expert knowledge in the field of intelligent materials.In this work, our method is focused on an additive term in the backstepping control that is based on the error of the current during the appearance of the default and the energy recovered by magnetostrictive sensors and the adaptive gain of the Kalman filter. This method improves the performance of backstepping control to maintain the operation despite the appearance of defects. The target is to ensure a minimum performance level of the drive system that is malfunctioning. The obtained results have provided useful information on multiple electrical malfunctions and show the overall performance of this complementary methodology for the fault tolerant control.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-24T10:48:52Z
      DOI: 10.1177/0142331220987532
       
  • A systematic decomposition approach of nonlinear systems by combining gap
           metric and stability margin
    • Authors: Mahdi Ahmadi, Mohammad Haeri
      First page: 2006
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, in order to control a nonlinear dynamic system via multi-model controller, we propose a systematic approach to determine the nominal local linear models. These models are selected from the local models bank and results in a reduced nominal models set that provides enough information to design a multi-model controller. To determine the initial local models bank, gap metric is used so that the distance between two successive local models is smaller than a threshold value. Then, a systematic approach that aims to get a reduced nominal models bank is developed. Based on this approach, first, a binary gap matrix is defined by combining gap metric and stability information. Then, several rows of this matrix are selected such that the sum of them becomes a non-zero vector. The proposed approach along with a designed robust controller is validated on a pH neutralization regarding to its highly nonlinear behavior.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-01T01:54:00Z
      DOI: 10.1177/0142331221989009
       
  • Signal filtering method of variational mode decomposition and Euclidean
           distance based on optimizing parameters of classification particle swarm
           optimization algorithm
    • Authors: Jingyi Lu, Xue Qu, Dongmei Wang, Jikang Yue, Lijuan Zhu, Gongfa Li
      First page: 2018
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to deal with the problem that the noise of leakage signals from natural gas pipelines has a great influence on the feature extraction of pipeline leakage, this paper proposes a signal denoising method of variational mode decomposition (VMD) and Euclidean distance (ED) based on optimizing parameters of classification particle swarm optimization (CPSO) algorithm. First, CPSO algorithm is used to optimize parameters K and [math] of VMD, adaptively. The sum of the ratio of the mean and variance of the cross-correlation coefficient and the ratio of the mean and variance of kurtosis is used as the fitness function of CPSO. Then, the optimized VMD is used to decompose the signal to obtain several intrinsic mode functions (IMFs). Finally, ED is used to select the effective modes, and the signal is reconstructed to achieve signal noise reduction. The corresponding evaluation indicators show that the accuracy and robustness of the improved method are better than other noise reduction methods. The denoising effect is significant, which proves that the algorithm proposed in this paper is effective in signal filtering.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-15T05:30:58Z
      DOI: 10.1177/0142331221989003
       
  • Aircraft system modeling under turbulence conditions and aircraft adaptive
           turbulence compensation
    • Authors: Zhaoyu Wang, Liyan Wen, Shaohua Yang
      First page: 2030
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An adaptive disturbance rejection control scheme is developed for solving the wind turbulence compensation problem. The turbulence wind studied in this paper is based on the mutual switch of several dominant wind directions. The linear models of aircraft under wind turbulence with different dominant directions are given. An adaptive controller is designed based on the model reference adaptive control when the aircraft encounters the wind turbulence in different dominant directions. Desired closed-loop system stabilization and output tracking have been proven. A simulation study on aircraft compensation has been presented to verify the effectiveness of our designed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-15T05:34:39Z
      DOI: 10.1177/0142331221989007
       
  • Gas pipeline leakage detection in the presence of parameter uncertainty
           using robust extended Kalman filter
    • Authors: Mohadese Jahanian, Amin Ramezani, Ali Moarefianpour, Mahdi Aliari Shouredeli
      First page: 2044
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      One of the most significant systems that can be expressed by partial differential equations (PDEs) is the transmission pipeline system. To avoid the accidents that originated from oil and gas pipeline leakage, the exact location and quantity of leakage are required to be recognized. The designed goal is a leakage diagnosis based on the system model and the use of real data provided by transmission line systems. Nonlinear equations of the system have been extracted employing continuity and momentum equations. In this paper, the extended Kalman filter (EKF) is used to detect and locate the leakage and to attenuate the negative effects of measurement and process noises. Besides, a robust extended Kalman filter (REKF) is applied to compensate for the effect of parameter uncertainty. The quantity and the location of the occurred leakage are estimated along the pipeline. Simulation results show that REKF has better estimations of the leak and its location as compared with that of EKF. This filter is robust against process noise, measurement noise, parameter uncertainties, and guarantees a higher limit for the covariance of state estimation error as well. It is remarkable that simulation results are evaluated by OLGA software.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-22T11:44:08Z
      DOI: 10.1177/0142331221989117
       
  • Real-time footstep planning including capture point trajectory
           optimization for stable biped navigation
    • Authors: Young-Dae Hong
      First page: 2058
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      For stable and efficient biped navigation, a real-time footstep planner taking bipedal dynamics for walking stability control into consideration is proposed. A capture point (CP)-based walking controller is utilized, and footstep planning including reference CP trajectory generation is formulated as an optimization problem. The footstep planning problem is solved using a particle swarm optimization algorithm. The walking period at every footstep is also planned to achieve more effective footstep planning, along with foot placement. Consequently, footstep placement, walking period, and reference CP trajectory for each footstep are optimized by the proposed method. The footstep optimization is performed in real-time without any approximations or precomputations. The effectiveness of the proposed method is demonstrated through experiments in a three-dimensional environment.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-08T07:18:33Z
      DOI: 10.1177/0142331221989512
       
  • Simultaneous stable control of temperature field distribution uniformity
           and consistency for multi-temperature zone systems
    • Authors: Xiaoyue Sang, Zhaohui Yuan, Xiaojun Yu, GaoXi Xiao, Muhammad Tariq Sadiq, Pengfei Yang, Yu Li
      First page: 2069
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      As a key factor characterizing the control accuracy of multi-temperature zone systems (MTZSs), the stable control of temperature field distribution uniformity and consistency is of critical importance for MTZSs, and it largely determines the product quality and production efficiency. Due to the complicated multiple input and output properties, as well as the various external variations in practice, however, it is extremely difficult to monitor the temperature field distribution in production process. To address the uniform and consistent temperature field distribution problem in MTZSs, a multi-variable dynamic matrix control (DMC)-based predictive control mechanism is proposed in this paper. Specifically, we first establish a finite element-based heat transfer model to analyse heat transfer within the multi-temperature zone, and then propose a multi-variable DMC-based decoupling design method to decompose the entire system into multiple subsystems with single-input single-output for temperature uniformity distribution control in MTZS. By utilizing the ANSYS tools to analyse the transient field temperatures, we obtain both time and space distribution characteristics of the transient temperature field with the proposed control method, and also compare such results with those obtained using the PID control method. Finally, we apply the proposed multi-variable DMC control mechanism onto a multi-temperature sintering furnace of a practical industrial product line for verification. Results show that, with the proposed control mechanism adopted, the difference between the highest and lowest temperature of any workpiece could be maintained within 5°C in the heat rising up period, which convincingly verifies the effectiveness of the proposed predictive control algorithm in different cases.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-12T05:11:25Z
      DOI: 10.1177/0142331221989849
       
  • Chattering-suppression sliding mode control of an autonomous underwater
           vehicle based on nonlinear disturbance observer and power function
           reaching law
    • Authors: Qirong Tang, Yinghao Li, Ruiqin Guo, Daopeng Jin, Yang Hong, Hai Huang
      First page: 2081
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      To improve the performance of autonomous underwater vehicle in trajectory tracking control, which is subject to system uncertainties and time-varying external disturbances, a nonlinear disturbance observer-based sliding mode controller is proposed in the study. First, a reaching law with a special power function and a hyperbolic tangent function is presented. Then an improved sliding mode controller based on the new reaching law is combined to decrease the reaching time and avoid chattering during the trajectory tracking control. Furthermore, to reduce the influence of the system uncertainties and external disturbances, a nonlinear disturbance observer is introduced to identify them. The error asymptotic convergence of the trajectory tracking control is proved by the Lyapunov-like function. Finally, under different environmental disturbances, plenty of simulations are carried out to verify the efficiency and robustness of the proposed method. Results show that when it is tracking different trajectories, the proposed method can suppress the chattering and reduce the disturbances effectively, while ensuring tracking performance.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-12T05:23:27Z
      DOI: 10.1177/0142331221989867
       
  • Output regulation for switched discrete-time systems with output signal
           quantization
    • Authors: Yaoli Zhang, Jun Zhao
      First page: 2094
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the output regulation problem for switched discrete-time systems with output quantization. We adopt the quantized output in feedback controllers and allow each subsystem to have its own quantization density, so that the communication network can be efficiently utilized. By using the different coordinates transformation, the solvability of the output regulation problem is guaranteed under deigned output feedback controllers with the switching signals satisfying a dwell time constraint. In the simulation, a pulse-width modulation driven boost converter model is employed to validate the result.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-12T05:26:47Z
      DOI: 10.1177/0142331221989887
       
  • Finite-time higher-order moment state estimation for Markov jump linear
           system with time-correlated measurement noise
    • Authors: Ziheng Zhou, Xiaoli Luan, Fei Liu
      First page: 2103
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In the present study, a higher-order moment state estimation problem in a finite time interval for the discrete-time Markov jump linear systems (MJLS) is investigated. Moreover, time-correlated noise in measurements is considered. Initially, the measruement differencing approach is applied to convert the time-correlated measurement noise to an uncorrelated noise. Then the cumulant generating function is utilized to solve the stochastic jumping problem of MJLS, by which the discrete-time MJLS is transformed into a deterministic system. In this way, the transformed deterministic system has the same norm with a higher-order moment of the original state. Finally, a finite-time state estimation algorithm is proposed to guarantee that the higher-order moment of error trajectory remains within a pre-specified bound over a given time interval. In order to evaluate the performance of the proposed method, some test cases are applied. Obtained results prove the accuracy and efficiency of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-12T05:28:27Z
      DOI: 10.1177/0142331221990126
       
  • Event-triggered boundary quantization control for flexible manipulator
           based on partial differential equations dynamic model
    • Authors: Jiacheng Wang, Jinkun Liu
      First page: 2111
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, we consider boundary control for a single-link flexible manipulator system described by partial differential equations (PDEs). Existing researches on controller design rarely consider the problem of communication capacity constrains during signal transmission. To deal with this problem, an adaptive control is designed to achieve the input quantization by using the random quantizer. Besides, a triggering event is addressed on the basis of relative threshold strategy for relieving communication load between controller and actuator. The proposed scheme is able to ensure that all closed-loop signals are globally uniformly bounded, and the angular tracking error and vibration converge to a residual set. Simulation results are presented to illustrate the effectiveness of the proposed scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-22T11:56:52Z
      DOI: 10.1177/0142331221990522
       
  • A novel full-order and reduced-order fault detection filters design method
           for continuous-time singular Markov jump systems with complexity
           transition rates
    • Authors: Yunling Shi, Xiuyan Peng
      First page: 2127
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This work is concerned with the problem of full-order and reduced-order fault detection filters (FDFs) design in a convex optimization frame for continuous-time singular Markov jump systems (CTSMJSs) with complexity transition rates (TRs). A novel Lyapunov function construct approach is utilized to cope with the stochastic admissibility problem for CTSMJSs with complexity TRs. In order to obtain effective full-order and reduced-order FDFs, we decoupled the inequality using the presupposed Lyapunov matrix. Owing to the use of Lyapunov stochastic admissibility theory and a novel decoupling method based on convex polyhedron technique, some sufficient conditions are obtained to guarantee that the resulting full-order and reduced-order FDFs are suitable for CTSMJSs with complexity TRs. In particular, the reduced-order FDF has the advantages of small storage space and fast detection speed compared with the full order FDF. Four illustrative examples are given to explain the effectiveness of the proposed full-order and reduced-order FDFs design method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-09T04:22:29Z
      DOI: 10.1177/0142331221990963
       
  • Fixed-time adaptive general type-2 fuzzy logic control for air-breathing
           hypersonic vehicle
    • Authors: Chaojun Yu, Ju Jiang, Shuo Wang, Bing Han
      First page: 2143
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper proposes a novel fixed-time adaptive general type-2 fuzzy logical control (FAGT2FLC) scheme for an air-breathing hypersonic vehicle (AHV) with uncertainties. Firstly, the AHV dynamic model is transformed into a strict feedback form. Then, the FAGT2FLC is designed based on the transformed model to improve robustness and guarantee fixed-time convergence of the closed-loop system. The general type-2 fuzzy logic system (GT2FLS) is utilized to approximate the model uncertainties; for the purpose of designing adaptive laws, the [math]-plane method is employed to represent the GT2FLS. A parameter projection operator is used to solve the possible singularity problem of parameter adaption. Besides, a fixed-time differentiator is used to deal with the “explosion of terms” inherent in backstepping method. Theoretical analysis based on relevant lemmas shows that the closed-loop system will converge into a small error band in fixed time. Lastly, detailed simulations are carried out to demonstrate the effectiveness and superiority of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-14T06:43:19Z
      DOI: 10.1177/0142331221991414
       
  • Robust preview control for polytopic nonlinear control systems
    • Authors: Li Li, Xiao Yu
      First page: 2159
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, the preview tracking control problem for Lipschitz nonlinear system, where future reference signals over a finite horizon can be previewed. First, an augmented error system including previewed information is constructed, which transforms a preview tracking control problem into a regulation problem. Furthermore, sufficient conditions on polytopic nonlinear systems, which guarantee the corresponding closed-loop system to be asymptotically stable, are derived by employing parameter-dependent Lyapunov function. A linear matrix inequality approach for designing preview controllers in state feedback and output feedback settings is presented. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-26T08:06:30Z
      DOI: 10.1177/0142331221992171
       
  • A single-step identification strategy for the coupled TITO process using
           fractional calculus
    • Authors: Kajal Kothari, Utkal Mehta, Ravneel Prasad
      First page: 2169
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The reliable performance of a complete control system depends on accurate model information being used to represent each subsystem. The identification and modelling of multivariable systems are complex and challenging due to cross-coupling. Such a system may require multiple steps and decentralized testing to obtain full system models effectively. In this paper, a direct identification strategy is proposed for the coupled two-input two-output (TITO) system with measurable input–output signals. A well-known closed-loop relay test is utilized to generate a set of inputs–outputs data from a single run. Based on the collected data, four individual fractional-order transfer functions, two for main paths and two for cross-paths, are estimated from single-run test signals. The orthogonal series-based algebraic approach is adopted, namely the Haar wavelet operational matrix, to handle the fractional derivatives of the signal in a simple manner. A single-step strategy yields faster identification with accurate estimation. The simulation and experimental studies depict the efficiency and applicability of the proposed identification technique. The demonstrated results on the twin rotor multiple-input multiple-output (MIMO) system (TRMS) clearly reveal that the presented idea works well with the highly coupled system even in the presence of measurement noise.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-22T11:47:48Z
      DOI: 10.1177/0142331221992732
       
  • Generalized Hotelling T2 control chart based on bivariate ranked set
           techniques with runs rules
    • Authors: Rashid Mehmood, Muhammad Riaz, Iftikhar Ali, Muhammad Hisyam Lee
      First page: 2180
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, we have introduced a generalized Hotelling T2 control chart based on bivariate ranked set techniques with runs rules to identify small and moderate variations in a process mean vector. To achieve this aim, plotting statistic and control limits are formulated in generalized approaches. For evaluation purposes, power and power curves are used as performance indicators. Afterwards, power curves are drawn through Monte Carlo simulation procedures by taking into account different choices of factors. A detailed discussion about the role of factors on the performance of the proposed generalized control chart is included. Furthermore, the proposed generalized control chart with double bivariate ranked set techniques is noted to be superb compared to the other cases of single bivariate ranked set techniques. Among single and double versions of bivariate ranked set techniques, the proposed generalized control chart on the basis of median bivariate ranked set techniques is recorded as more efficient relative to the other choices under consideration. Also, comparative analysis shows that the proposed generalized control chart with supplementary runs rules performs outstandingly for detection of small and moderate variations relative to existing control charts. Special cases of the proposed generalized control chart are elaborated to highlight its features for accommodating the existing control charts. To amplify the uses and advantages of the proposed generalized control chart, a real-world example from agriculture is presented.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-24T10:44:13Z
      DOI: 10.1177/0142331221992670
       
  • Regional stabilization and [math] congestion control with input saturation
    • Authors: Sadek Belamfedel Alaoui, El Houssaine Tissir, Noreddine Chaibi, Fatima El Haoussi
      First page: 2196
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Designing robust active queue management subjected to network imperfections is a challenging problem. Motivated by this topic, we addressed the problem of controller design for linear systems with variable delay and unsymmetrical constraints by the scaled small gain theorem. We designed two mechanisms: robust enhanced proportional derivative; and robust enhanced proportional derivative subjected to input saturation. Discussion of their practical implementations along with extensive comparisons by MATLAB and NS3 illustrate the improved performance and the enlargement of the domain of attraction regarding some literature results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-01T08:14:45Z
      DOI: 10.1177/0142331221992739
       
  • A new control approach for a class of linear switched systems with
           time-varying delay
    • Authors: Abbas Zabihi Zonouz, Mohammad Ali Badamchizadeh, Amir Rikhtehgar Ghiasi
      First page: 2213
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a new method for designing controller for linear switching systems with varying delay is presented concerning the Hurwitz-Convex combination. For stability analysis the Lyapunov-Krasovskii function is used. The stability analysis results are given based on the linear matrix inequalities (LMIs), and it is possible to obtain upper delay bound that guarantees the stability of system by solving the linear matrix inequalities. Compared with the other methods, the proposed controller can be used to get a less conservative criterion and ensures the stability of linear switching systems with time-varying delay in which delay has way larger upper bound in comparison with the delay bounds that are considered in other methods. Numerical examples are given to demonstrate the effectiveness of proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-03T11:04:01Z
      DOI: 10.1177/0142331221992729
       
  • Dynamic multi-objective matrix control for a class of switched systems
    • Authors: Ali Thamallah, Anis Sakly, Faouzi M’Sahli
      First page: 2229
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article focuses on the tracking and stabilizing issues of a class of discrete switched systems. These systems are characterized by unknown switching sequences, a non-minimum phase, and time-varying or dead modes. In particular, for those governed by an indeterminate switching signal, it is very complicated to synthesize a control law able to systematically approach general reference-tracking difficulties. Taking into account the difficulty to express the dynamic of this class of systems, the present paper presents a new Dynamic matrix control method based on the multi-objective optimization and the truncated impulse response model. The formulation of the optimization problem aims to approach the general step-tracking issues under persistent and indeterminate mode changes and to overcome the stability problem along with retaining as many desirable features of the standard dynamic matrix control (DMC) method as possible.In addition, the formulated optimization problem integrates estimator variables able to manipulate the optimization procedure in favor of the active mode with an appropriate adjustment. It also provides a progressive and smooth multi-objective control law even in the presence of problems whether in subsystems or switching sequences. Finally, simulation examples and comparison tests are conducted to illustrate the potentiality and effectiveness of the developed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-08T07:27:36Z
      DOI: 10.1177/0142331221993387
       
  • Nonlinear disturbance observer-based fault-tolerant control for flexible
           teleoperation systems with actuator constraints and varying time delay
    • Authors: Padideh Rasouli, Mazda Moattari, Ahmad Forouzantabar
      First page: 2246
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, designing a control law for teleoperation systems with flexible-link slave robots in the presence of dynamic uncertainties, disturbances, actuator faults and actuator constraints with time-varying communication delays is addressed. This study proposes a simple anti-saturation nonlinear fault-tolerant controller incorporating a disturbance observer. The attractive features of the proposed controller include the ability to cope with disturbances, avoiding actuators exceeding their usual bounds, and compensating for the actuator faults. Besides which, the controller has a simple structure, does not need a fault detection mechanism, and coordinates the master’s motion speed with the slave’s actuator. A Lyapunov–Krasovskii functional is used to prove the stability and tracking performance of the teleoperation system. The feasibility and efficiency of the proposed controller are corroborated through simulation results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-23T11:37:50Z
      DOI: 10.1177/0142331221993246
       
  • Nonlinear lateral motion stability control method for electric vehicle
           based on the combination of dual extended state observer and domination
           approach via sampled-data output feedback
    • Authors: Qinghua Meng, Hao Xu, Zong-Yao Sun
      First page: 2258
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies lateral motion stability control method for an electric vehicle (EV) with uncertain disturbances. Aiming to suppress the influence of uncertain disturbances, a novel method based on the combination of dual extended state observer (dESO) and domination approach is proposed. The proposed method enables the designed controller just to adopt a smaller scaling gain than the classic domination method, which is more practical for the controller in engineering. Firstly, a dESO is proposed to estimate the uncertain disturbances of the system. Also, a sampled-data output feedback domination approach is designed to dominate the disturbances by using a scaling gain. Then, the sampled-data output feedback control law is constructed based on the dESO and domination approach called dESOD. Furthermore, the stability analysis is presented to show that the proposed sampled-data controller can guarantee the closed-loop system globally asymptotically stable. Finally, the simulations and experiment results show the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-02-25T02:00:16Z
      DOI: 10.1177/0142331221994369
       
  • Event-triggered consensus control of second-order nonlinear multi-agent
           systems under denial-of-service attacks
    • Authors: Yu Shang, Cheng-Lin Liu, Ke-Cai Cao
      First page: 2272
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the event-triggered consensus problem of second-order nonlinear multi-agent systems subject to denial-of-service (DoS) attacks, which make the communication network unable to provide normal services. Considering a general class of DoS attack with limited duration, a novel distributed event-triggered consensus protocol accompanied with first-order hold is adopted to guarantee the globally bounded consensus convergence under directed network topology. Based on the linear matrix inequality approach and Lyapunov stability method, consensus converging properties are analysed and sufficient criteria are obtained. Furthermore, Zeno-free triggering of our proposed protocol is demonstrated. Finally, a numerical simulation is given to show the effectiveness of our theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-03T11:10:21Z
      DOI: 10.1177/0142331221994378
       
  • A non-overshooting controller for vehicle path following
    • Authors: Tong Xu, Dong Wang, Weigong Zhang
      First page: 2282
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Unmanned pavement construction is of great significance in China, and one of the most important issues is how to follow the designed path near the boundary of the pavement construction area to avoid curbs or railings. In this paper, we raise a simple yet effective controller, named the proportional-integral-radius and improved particle swarm optimization (PIR-IPSO) controller, for fast non-overshooting path-following control of an unmanned articulated vehicle (UAV). Firstly, UAV kinematics model is introduced and segmented UAV steering dynamics model is built through field experiments; then, the raw data collected by differential global positioning system (DGPS) is used to build the measurement error distribution model that simulates positioning errors. Next, line of sight (LOS) guidance law is introduced and the LOS initial parameter is assigned based on human driving behavior. Besides, the initial control parameters tuned by the Ziegler-Nichols (ZN) method are used as the initial iterative parameters of the PSO controller. An improved PSO fitness function is also designed to achieve fast non-overshoot control performance. Experiments show that compared with the PSO, ZN and ZN-PSO controller, the PIR-PSO-based controller has significantly less settling time and almost no overshoot in various UAV initial states. Furthermore, compared with other controllers, the proposed PIR-IPSO-based controller achieves precise non-overshoot control, relatively less settling time and centimeter-level positioning error in various initial deviations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-22T10:04:54Z
      DOI: 10.1177/0142331221994384
       
  • Managing the handling–comfort contradiction of a quarter-car system
           using Kalman filter
    • Authors: Alhelou Muhammed, Alexander Gavrilov
      First page: 2292
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article introduces a new approach to manage the “handling–comfort” contradiction of a vehicle suspension system. The idea is based on determining a specific time constant that reflects the percentage of suspension damping. This time constant is defined using the measurement of the sprung mass acceleration and the suspension deflection. A distinction is made between the control unit design for a semi-active suspension system and the control unit design for an active suspension system. The semi-active design is based on two sensors and a Kalman filter (KF), while the active design is based on three sensors and a dual-estimation KF. For active suspension, a third sensor was added to measure the acceleration of the unsprung mass. Simulation is carried out in Simulink and Simscape environments. The results of the proposed approach were compared with the results achieved by the hybrid-hook system. Simulation results showed a better efficiency of the proposed approach in driving safety during a “comfort” situation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-08T07:21:15Z
      DOI: 10.1177/0142331221994951
       
  • Observer-based adaptive control of robot manipulators using reinforcement
           learning and the Fourier series expansion
    • Authors: Gholamreza Khodamipour, Saeed Khorashadizadeh, Mohsen Farshad
      First page: 2307
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Designing observer-controller structures for nonlinear system with unknown dynamics such as robotic systems is among popular research fields in control engineering. The novelty of this paper is in presenting an observer-based model-free controller for robot manipulators using reinforcement learning (RL). The proposed controller calculates the desired motor voltages that fulfil a satisfactory tracking performance. Moreover, the uncertainties and nonlinearities in the observer model and RL controller are estimated and compensated for by using the Fourier series expansion. Simulation results and comparison with the previous related works (extended state observer and radial basis function neural networks) indicate the satisfactory performance of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-03T11:18:01Z
      DOI: 10.1177/0142331221995336
       
  • Non-fragile quasi-synchronization of delayed heterogeneous dynamical
           networks with memory sampled-data control
    • Authors: Manyu Zhao, Zhengxin Wang, Jun Ye
      First page: 2321
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the quasi-synchronization problem for a class of heterogeneous dynamical networks based on a non-fragile memory sampled-data controller. Considering the effect of controller gain fluctuation and communication delay, a sampled-data control scheme with norm-bounded uncertainty and a constant signal transmission delay is designed. By introducing a leader, the heterogeneous complex delayed networks can be transformed into the corresponding error systems with bounded disturbances. A sufficient criterion to ensure that the error system can be exponentially stable and converge to a bounded region is established by the Lyapunov-Krasovskii function approach. Based on the criterion, the sampled-data control gain matrix is designed. Finally, the numerical examples are presented to illustrate the effectiveness of the theoretical results in this paper.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-09T11:27:37Z
      DOI: 10.1177/0142331221995332
       
  • Iterative learning control realized using an iteration-varying forgetting
           factor based on optimal gains
    • Authors: Baolin Dai, Jun Gong, Cuiming Li, Huifeng Ning
      First page: 2334
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Iterative learning control with forgetting factor (ILCFF) is widely used in control engineering. However, choosing the optimal parameters of ILCFF to improve system-output characteristics has been a challenging issue for controller designers. This paper proposes an iterative learning control (ILC) algorithm that involves a variable forgetting factor based on optimal gains for a class of discrete linear time-invariant systems with aperiodic disturbances. The convergence of the algorithm is analyzed, and the necessary and sufficient condition for its convergence is derived in terms of proportional–integral–derivative coefficients. A design method based on optimal gains is established to determine the algorithm coefficients and to accelerate system convergence. Furthermore, the influence of the forgetting factor on both the system-output error and the scope of the proposed algorithm is analyzed. Additionally, the most suitable system type for the application of the forgetting factor is determined. The effectiveness of the algorithm is verified by performing a theoretical analysis and a case-based simulation. The proposed iteration-varying optimal forgetting-factor-based ILC algorithm undergoes fast convergence with a small system-output error. The findings disrupt the conventional view that the use of the forgetting factor increases system-output error. In fact, in a system with small trajectory and increased disturbances, the error induced by the forgetting factor may be smaller than that of the traditional optimal ILC algorithm.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-10T06:15:00Z
      DOI: 10.1177/0142331221996507
       
  • Global exponential stabilization of a quadrotor by hybrid control
    • Authors: Seyed Hamed Hashemi, Naser Pariz, Seyed Kamal Hosseini Sani
      First page: 2345
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The main purpose of this paper is to introduce a hybrid controller for global attitude tracking of a quadrotor. This controller globally exponentially stabilizes the desired attitude, a task that is impossible to accomplish with memoryless discontinuous or continuous state feedback owing to topological obstruction. Thereafter, this paper presents a new centrally synergistic potential function to construct hybrid feedback that defeats the topological obstruction. This function induces a gradient vector field to globally asymptotically stabilize the reference attitude and produces the synergy gap to generate a switching control law. The proposed control structure is consisting of two major parts. In the first part, a synergetic controller is designed to cooperate with the hybrid controller, whereas it exponentially stabilizes the origin of the error dynamics. In the second part, a hybrid controller is introduced to globally stabilize the attitude of the quadrotor, where an average dwell constraint is considered with the switching control law to guarantee the exponential stability of the switched system. Finally, the effectiveness and superiority of the proposed control technique are validated by a comparative analysis in simulations.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-13T04:00:56Z
      DOI: 10.1177/0142331221996969
       
  • Disturbance-observer-based attitude control under input nonlinearity
    • Authors: Umair Javaid, Hongyang Dong
      First page: 2358
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A disturbance observer-based control scheme is proposed in this paper to deal with the attitude stabilization problems of spacecraft subjected to external disturbances, parameter uncertainties, and input nonlinearities. Particularly, the proposed approach addresses the dead-zone issue, a non-smooth nonlinearity affiliated with control input that significantly increases controller design difficulties. A novel nonlinear disturbance observer (NDO) is developed, which relaxes the strong assumption in conventional NDO design that disturbances should be constants or varying with slow rates. After that, a special integral sliding mode controller (ISMC) is combined with the NDO to achieve asymptotic convergence of system states. Simulations are performed in the presence of time-varying disturbances, parameter uncertainties, and dead-zone nonlinearity to justify the effectiveness of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-15T11:10:03Z
      DOI: 10.1177/0142331221997204
       
  • Online optimum velocity calculation under V2X for smart new energy
           vehicles
    • Authors: Chuan Huang, Ping Hu, Jing Lian
      First page: 2368
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a vector data net solver is proposed, which can reduce bivariate discrete-time dynamic programming (DP) computation time by 98.0% without losing accuracy. Therefore, for the first time, bivariate discrete-time DP can operate under model predictive control rolling optimization to calculate future optimum vehicle velocity in real time considering future road altitude and instant traffic information. Simulation results indicate that with the solution presented in this paper, front vehicles and the proper windows to pass through front intersections can be constantly considered. Meanwhile, the calculated optimum vehicle velocity almost remains the same as the global optimum solutions. Simulation results are validated by real-car tests, and the test new energy vehicle (NEV) electricity consumption is reduced by up to 48.6%. A comparison experiment is performed between the solution presented in this paper and commonly used adaptive dynamic programming (ADP), and the results indicate that the former has better performance and stability. This paper describes a novel solution for online optimum velocity calculation under vehicle to everything (V2X) environment and can be used by all smart NEVs with autonomous driving or active cruise control functions for lower electricity consumption and better riding comfort.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-03-23T11:42:51Z
      DOI: 10.1177/0142331221997280
       
  • A variational approach to determination of maximum throw-able workspace of
           robotic manipulators in optimal ball pitching motion
    • Authors: Mohsen Asgari, Amin Nikoobin
      First page: 2378
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study is aimed at finding the entire points that a manipulator can launch an object onto by an optimal motion. These points are called throw-able workspace, which are located outside the reachable workspace of the robot. From an optimization point of view, some throwing parameters can be found to decrease motion cost. In this paper, by using this concept, the best combination of throwing and trajectory planning is attempted. The proposed method consists of two basic ideas: first, defining the optimal throwing problem as the optimal control problem (OCP) and solving it using the indirect solution approach based on the fundamental lemma of calculus of variations. To achieve the best release angle and speed, the throwing equation of motion is applied as a moving-end boundary condition (BC). Second, based on the obtained optimal throwing, an algorithm is presented to calculate the maximum throw-able workspace. The simulation results demonstrate the effectiveness of the proposed framework for both single link and spatial two-degree-of-freedom throwing robots.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T11:54:35Z
      DOI: 10.1177/01423312211001694
       
  • Fixed-time consensus of first-order multi-agent systems over signed
           directed graphs
    • Authors: Zhentao Li, Zhengxin Wang, Yuanzhen Feng
      First page: 2392
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the fixed-time consensus problems of first-order multi-agent systems over signed directed graphs. Fixed-time consensus protocols are designed for first-order multi-agent systems without/with disturbances and first-order nonlinear multi-agent systems with disturbances, respectively. With proposed protocols, it is proved that multi-agent systems with strongly connected topologies will achieve consensus in a fixed time if the control parameters satisfy certain conditions. Finally, simulation examples are provided to verify the effectiveness of the theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-06T11:55:53Z
      DOI: 10.1177/01423312211001990
       
  • Hybrid-driven control of networked switched systems with random cyber
           attacks
    • Authors: Yonghui Liu, Jiahui Jin
      First page: 2402
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper considers security control for a class of networked switched systems subject to random cyber attacks. To alleviate the burden of the networked transmission, a hybrid-driven communication strategy is employed. Moreover, based on the hybrid-triggered control scheme, a state-feedback controller and a switching signal depending on the average dwell time are designed simultaneously. It is shown that the switched systems are mean-square exponentially stable despite the presence of the random cyber attacks. Finally, a numerical example is exploited to demonstrate the effectiveness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2021-04-05T08:31:37Z
      DOI: 10.1177/01423312211002598
       
  • Experimental verification of lithium-ion battery prognostics based on an
           interacting multiple model particle filter
    • Authors: Shuai Wang, Wei Han, Lifei Chen, Xiaochen Zhang, Michael Pecht
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A new data-driven prognostic method based on an interacting multiple model particle filter (IMMPF) is proposed for use in the determination of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries and the probability distribution function (PDF) of the uncertainty associated with the RUL. An IMMPF is applied to different state equations. The battery capacity degradation model is very important in the prediction of the RUL of Li-ion batteries. The IMMPF method is applied to the estimation of the RUL of Li-ion batteries using the three improved models. Three case studies are provided to validate the proposed method. The experimental results show that the one-dimensional state equation particle filter (PF) is more suitable for estimating the trend of battery capacity in the long term. The proposed method involving interacting multiple models demonstrated a stable and high prediction accuracy, as well as the capability to narrow the uncertainty in the PDF of the RUL prediction for Li-ion batteries.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-26T06:09:31Z
      DOI: 10.1177/0142331220961576
       
  • Fast battery capacity estimation using convolutional neural networks
    • Authors: Yihuan Li, Kang Li, Xuan Liu, Li Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Lithium-ion batteries have been widely used in electric vehicles, smart grids and many other applications as energy storage devices, for which the aging assessment is crucial to guarantee their safe and reliable operation. The battery capacity is a popular indicator for assessing the battery aging, however, its accurate estimation is challenging due to a range of time-varying situation-dependent internal and external factors. Traditional simplified models and machine learning tools are difficult to capture these characteristics. As a class of deep neural networks, the convolutional neural network (CNN) is powerful to capture hidden information from a huge amount of input data, making it an ideal tool for battery capacity estimation. This paper proposes a CNN-based battery capacity estimation method, which can accurately estimate the battery capacity using limited available measurements, without resorting to other offline information. Further, the proposed method only requires partial charging segment of voltage, current and temperature curves, making it possible to achieve fast online health monitoring. The partial charging curves have a fixed length of 225 consecutive points and a flexible starting point, thereby short-term charging data of the battery charged from any initial state-of-charge can be used to produce accurate capacity estimation. To employ CNN for capacity estimation using partial charging curves is however not trivial, this paper presents a comprehensive approach covering time series-to-image transformation, data segmentation, and CNN configuration. The CNN-based method is applied to two battery degradation datasets and achieves root mean square errors (RMSEs) of less than 0.0279 Ah (2.54%) and 0.0217 Ah (2.93% ), respectively, outperforming existing machine learning methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-11-06T05:35:23Z
      DOI: 10.1177/0142331220966425
       
  • On wavelet-based statistical process monitoring
    • Authors: Achraf Cohen, Mohamed Amine Atoui
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an overview of wavelet-based techniques for statistical process monitoring. The use of wavelet has already had an effective contribution to many applications. The increase of data availability has led to the use of wavelet analysis as a tool to reduce, denoise, and process the data before using statistical models for monitoring. The most recent review paper on wavelet-based methods for process monitoring had the goal to review the findings up to 2004. In this paper, we provide a recent reference for researchers and engineers with a different focus. We focus on: (i) wavelet statistical properties, (ii) control charts based on wavelet coefficients, and (iii) wavelet-based process monitoring methods within a machine learning framework. It is clear from the literature that wavelets are widely used with multivariate methods compared to univariate methods. We also found some potential research areas regarding the use of wavelet in image process monitoring and designing control charts based on wavelet statistics, and listed them in the paper.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-14T05:54:21Z
      DOI: 10.1177/0142331220935708
       
  • An incentive mechanism-based negotiation model for green supply chain
           networks
    • Authors: Fang Yu, Chun Zhang, Yongsheng Yang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This research aims to prompt agents to improve their strategies initiatively in order to decrease carbon dioxide emissions and enhance green factors during production and consumption processes. An incentive negotiation mechanism is proposed for agents in supply chains to improve their strategies. Multiple items, multiple attributes, and multiple echelons are involved in the proposed model. In addition, this research takes both the commerce and the environmental attributes into account. The environmental attributes were transformed into rewards or penalty by setting reward factors or penalty factors, and were taken into account during the calculation of the profits. The simulation results show that the proposed model was feasible to solve the complex negotiation problems, and had a good performance. The green factors of agents in the green supply chain network are increased when the agents have low initial green factors. Moreover, the proposed model can effectively reduce the carbon dioxide emissions as well. The proposed model can be seen as a “win–win” solution from the perspective of both business and environmental protection. The total profit of the green supply chain network is improved, and the harm to the environment is decreased as well.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-07-10T10:42:16Z
      DOI: 10.1177/0142331220929814
       
  • Suboptimal obstacles avoidance control of spacecraft rendezvous
    • Authors: Lu Cao, Bing Xiao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Spacecraft on-orbital services and docking require their autonomous rendezvous control system to have obstacle avoidance capability. Motivated by this, a suboptimal velocity artificial potential function-based control scheme is presented. An ellipsoid model is applied to describe the outer envelopes of the service spacecraft and the obstacles via an eigenvalue algorithm. This has better description precision than the traditional methods. The potential sigmoid function is used to generate repulsive force to avoid obstacles collision. A velocity artificial potential function-based controller is finally developed to ensure that the relative speed of the service spacecraft is reduced to zero before reaching the outer envelops of obstacles. The shaping parameters of the attractive potential function are adaptively optimized. Numerical simulations are performed to demonstrate that the approach can achieve a safe and autonomous rendezvous with fuel cost saved.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-22T10:50:38Z
      DOI: 10.1177/0142331220928886
       
  • Suboptimal midcourse guidance design using generalized model predictive
           spread control
    • Authors: Amin Ebrahimi, Ali Mohammadi, Abdorreza Kashaninia
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      A new generalized model predictive spread control technique is presented for the midcourse guidance of interceptors that are designed to intercept high-speed ballistic missile targets. Because of using the basis functions, this new technique is further computationally efficient over the model predictive static programming technique. Also, the smoothness of the control variable is guaranteed for the smooth basis functions. For demonstrating the performance of the proposed technique, an interceptor midcourse guidance problem with an angle constraint is formulated and solved to intercept an incoming ballistic missile target successfully. Additionally, the results are compared with those of the midcourse guidance design using the model predictive static programming technique. A comparative study of the new technique has also been conducted with the quasi-spectral model predictive static programming technique proposed earlier in the literature. It has been observed that the orthogonality of the basis functions is a necessary assumption and without that, the quasi-spectral model predictive static programming technique is not a near-optimal technique. By using the new technique based on Legendre basis functions, the solution converges to the model predictive static programming method solution by increasing the number of basis functions with less computational load.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-22T10:48:19Z
      DOI: 10.1177/0142331220928888
       
  • Prescribed performance trajectory tracking control of dynamic positioning
           ship under input saturation
    • Authors: Yuanhui Wang, Haibin Wang, Mingyu Fu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates concentrates on the trajectory tracking control problem of dynamic positioning (DP) ship, in the presence of the time-varying disturbance and input saturation. Firstly, a simplified mathematical model of three degrees of freedom is established. According to the characteristics of the DP ship, an adaptive backstepping controller which combine the prescribed performance function with disturbance observer is proposed. The control scheme can guarantee the transient and steady state performance of the trajectory tracking and meet the prescribed performance criteria. In addition, an auxiliary dynamic system is introduced into the controller to deal with the input saturation problem of the actuator, so that the DP ship can accomplish the task of trajectory tracking under the condition of actuator constraint. Subsequently, in combination of barrier Lyapunov function (BLF), it is proved that the DP system can stabilize and converge rapidly to the small neighborhood of the equilibrium point, which can achieve the prescribed performance. Finally, the effectiveness of the DP control law is demonstrated by a series of simulation experiments.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-19T10:37:41Z
      DOI: 10.1177/0142331220928887
       
  • A novel load prediction method for hybrid electric ship based on working
           condition classification
    • Authors: Diju Gao, Yao Jiang, Nan Zhao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to effectively optimize the load distribution between power sources during the navigation of hybrid ships, a method for predicting ship load demand based on real-time classification according to different working conditions is proposed. The k-means clustering algorithm is used to quantify the voyage history data to classify the ship’s navigation conditions into fast-changing conditions and slow-changing conditions. Some characteristic parameters related to working conditions are selected as input. Then, input and the category of working conditions are put into least squares support vector machine to learn and train to get an online working condition classifier. The genetic algorithm is used to optimize the radial-based neural network to predict the load demand under fast-changing conditions, use the Markov chain model to predict the load demand under slow-changing conditions, so as to obtain the most accurate future load demand of the ship. The simulation results show that the proposed prediction models under different conditions have higher precision, which is an effective means of predicting the load demand for hybrid power ships.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-08T04:20:49Z
      DOI: 10.1177/0142331220923767
       
  • Moving sliding mode controller for overhead cranes suffering from matched
           and unmatched disturbances
    • Authors: Xiutao Gu, Weimin Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel time-varying gain extended state observer (ESO)-based moving sliding mode control method is proposed for anti-sway and positioning control of two-dimensional underactuated overhead cranes. The designed moving sliding mode surface can adjust its slope in real time according to the state variable errors; in addition, a dynamic exponential term is added into the moving sliding mode surface so as to drive any initial state variable errors into the sliding surface rapidly, and thereby the robustness of crane systems is improved. Then, a chattering-free reaching law is designed to realize fast convergence of the system state errors, and the input is modelled as a saturated one due to the fact the motor torque is bounded and the control law and adaptive updating law of switching gain are derived in the sense of Lyapunov function, so the stability can be guaranteed even under the input saturation. Moreover, to suppress the matched and unmatched disturbance occurring in crane dynamic systems, a time-varying gain ESO is constructed to estimate the lumped disturbance, then the estimated value is used for feedforward compensation to establish the controller. Finally, the simulation results confirm the effectiveness of the proposed controller.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-04T09:22:19Z
      DOI: 10.1177/0142331220922109
       
  • An improved method for swing measurement based on monocular vision to the
           payload of overhead crane
    • Authors: Jinling Huang, Weimin Xu, Weiwei Zhao, Hesong Yuan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to solve the problem that the blurred image of a moving object decreases accuracy in the process of detecting the payload swing angle of an overhead crane based on vision, and the tracking failure caused by the drastic change of grey targets, a robust real-time detection method of the load swing angle of a bridge crane is proposed. This method uses a spherical marker attached to the load, which is insensitive to rotation and tilt when it is detected. First, it uses the mean shift algorithm combined with Kalman filter to track the moving objects in the image plane continuously, and then integrates the method of minimum area circle to detect the spherical marker image in the region of interest accurately and quickly. Finally, combined with the geometric method, the real-time swing angle is calculated. In addition, the angle diagram method is used to increase the speed of calculating the swing angle. The experimental results show that the method is effective for detecting the load target swing angle of different trolley motion speed.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-04T08:44:10Z
      DOI: 10.1177/0142331220921318
       
  • Sub-fixed-time control for a class of second order system
    • Authors: Boyan Jiang, Hua Chen, Bo Li, Xuewu Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a new concept “sub-fixed-time stability” (SFTS) is proposed and studied, which means the states can converge to a region of equilibrium points in a fixed time for any initial states’ values. Then, a sufficient condition for it is given and proven. Though SFTS is similar to “practical fixed-time stability” (PFTS), they are not the same, and the sufficient condition for SFTS is much clearer and simpler than PFTS. Next, a sub-fixed-time controller is proposed for a class of second order system. The stability analyses are given in the case without disturbance and with disturbance, respectively. Finally, to illustrate the robustness of the proposed sub-fixed-time controller to different initial conditions, 100 numerical simulations are conducted for 100 initial states’ values.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-06-01T09:46:01Z
      DOI: 10.1177/0142331220921008
       
  • Robust model reference control for uncertain second-order system subject
           to parameter uncertainties
    • Authors: Guang-Tai Tian, Guang-Ren Duan
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is devoted to designing a robust model reference controller for uncertain second-order systems subject to parameter uncertainties. The system matrix of the first-order reference model is more general and the parameter uncertainties are assumed to be norm-bounded. The design of robust controller can be devided into two separate problems: problem robust stabilization and problem robust compensation. Based on the solution of generalized Sylvester matrix equations, we obtain some sufficient conditions to guarantee the complete parameterization of the controller. Then, the problem robust compensation of the closed-loop system is estimated by solving a convex optimisation problem with a set of linear matrix equations constraints. Two simulation examples are provided to illustrate the effectiveness of the proposed technique.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2020-02-27T06:48:11Z
      DOI: 10.1177/0142331220904544
       
 
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