Subjects -> INSTRUMENTS (Total: 63 journals)
Showing 1 - 16 of 16 Journals sorted by number of followers
International Journal of Remote Sensing     Hybrid Journal   (Followers: 161)
IEEE Sensors Journal     Hybrid Journal   (Followers: 119)
Remote Sensing of Environment     Hybrid Journal   (Followers: 96)
Journal of Applied Remote Sensing     Hybrid Journal   (Followers: 87)
Modern Instrumentation     Open Access   (Followers: 58)
Remote Sensing     Open Access   (Followers: 57)
International Journal of Remote Sensing Applications     Open Access   (Followers: 48)
International Journal of Instrumentation Science     Open Access   (Followers: 42)
Experimental Astronomy     Hybrid Journal   (Followers: 39)
Measurement and Control     Open Access   (Followers: 36)
Photogrammetric Engineering & Remote Sensing     Full-text available via subscription   (Followers: 34)
Journal of Instrumentation     Hybrid Journal   (Followers: 32)
Remote Sensing Science     Open Access   (Followers: 30)
Applied Mechanics Reviews     Full-text available via subscription   (Followers: 27)
Review of Scientific Instruments     Hybrid Journal   (Followers: 20)
European Journal of Remote Sensing     Open Access   (Followers: 17)
Videoscopy     Full-text available via subscription   (Followers: 15)
Flow Measurement and Instrumentation     Hybrid Journal   (Followers: 15)
Transactions of the Institute of Measurement and Control     Hybrid Journal   (Followers: 12)
Journal of Sensors and Sensor Systems     Open Access   (Followers: 11)
Remote Sensing Applications : Society and Environment     Full-text available via subscription   (Followers: 9)
Instrumentation Science & Technology     Hybrid Journal   (Followers: 8)
International Journal of Applied Mechanics     Hybrid Journal   (Followers: 8)
Imaging & Microscopy     Hybrid Journal   (Followers: 7)
Microscopy     Hybrid Journal   (Followers: 7)
Metrology and Measurement Systems     Open Access   (Followers: 7)
Science of Remote Sensing     Open Access   (Followers: 7)
Optoelectronics, Instrumentation and Data Processing     Hybrid Journal   (Followers: 6)
International Journal of Metrology and Quality Engineering     Full-text available via subscription   (Followers: 5)
Measurement : Sensors     Open Access   (Followers: 5)
PFG : Journal of Photogrammetry, Remote Sensing and Geoinformation Science     Hybrid Journal   (Followers: 5)
Computational Visual Media     Open Access   (Followers: 5)
Journal of Medical Devices     Full-text available via subscription   (Followers: 4)
Sensors and Materials     Open Access   (Followers: 4)
IEEE Sensors Letters     Hybrid Journal   (Followers: 4)
Journal of Astronomical Instrumentation     Open Access   (Followers: 4)
Journal of Optical Technology     Full-text available via subscription   (Followers: 4)
IEEE Journal on Miniaturization for Air and Space Systems     Hybrid Journal   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Sensors International     Open Access   (Followers: 3)
Solid State Nuclear Magnetic Resonance     Hybrid Journal   (Followers: 3)
Measurement Techniques     Hybrid Journal   (Followers: 3)
Journal of Instrumentation Technology & Innovations     Full-text available via subscription   (Followers: 3)
International Journal of Sensor Networks     Hybrid Journal   (Followers: 2)
International Journal of Measurement Technologies and Instrumentation Engineering     Full-text available via subscription   (Followers: 2)
Geoscientific Instrumentation, Methods and Data Systems     Open Access   (Followers: 2)
International Journal of Testing     Hybrid Journal   (Followers: 1)
Medical Devices & Sensors     Hybrid Journal   (Followers: 1)
Instruments and Experimental Techniques     Hybrid Journal   (Followers: 1)
Geoscientific Instrumentation, Methods and Data Systems Discussions     Open Access   (Followers: 1)
Journal of Research of NIST     Open Access   (Followers: 1)
Journal of Vacuum Science & Technology B     Hybrid Journal   (Followers: 1)
Invention Disclosure     Open Access   (Followers: 1)
Metrology and Instruments / Метрологія та прилади     Open Access  
Measurement Instruments for the Social Sciences     Open Access  
Труды СПИИРАН     Open Access  
Standards     Open Access  
Jurnal Informatika Upgris     Open Access  
InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan     Open Access  
Devices and Methods of Measurements     Open Access  
EPJ Techniques and Instrumentation     Open Access  
Journal of Medical Signals and Sensors     Open Access  
Documenta & Instrumenta - Documenta et Instrumenta     Open Access  
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Journal Cover
Transactions of the Institute of Measurement and Control
Journal Prestige (SJR): 0.41
Citation Impact (citeScore): 1
Number of Followers: 12  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0142-3312 - ISSN (Online) 1477-0369
Published by Sage Publications Homepage  [1174 journals]
  • Robust secure consensus of multiagent systems with DoS attacks

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      Authors: Shengli Du, Qiushuo Yan, Junfei Qiao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The secure consensus problem of multiagent systems with fixed topology and external disturbances is investigated in this paper. Along with external disturbances, the studied multiagent system is also subjected to denial-of-service (DoS) attacks. First, some graph-based Lyapunov functions are presented for the robust consensus analysis. Second, the duration and attack frequency are introduced to quantitatively analyze the DoS attacks’ effects on the consensus. Third, the gain of the controller is acquired by solving an algebraic Riccati equation (ARE), which can always be guaranteed compared with solving linear matrix inequalities (LMIs). Finally, a numerical simulation of a microgrid test system is provided to demonstrate the effectiveness of the proposed strategy.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-08T11:44:08Z
      DOI: 10.1177/01423312221114704
       
  • Early warning of reciprocating compressor valve fault based on deep
           learning network and multi-source information fusion

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      Authors: Hongyi Wang, Jiwei Chen, Xinjun Zhu, Limei Song, Feng Dong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An early warning method of compressor valve fault based on multi-parameter signals (vibration, pressure, and temperature) is presented in this work. Due to the complexity working condition, the run data of the compressor are of problems like noise and feature aliasing, which makes it difficult to extract useful features and find out the running law from the original signals. In this work, an improved deep learning network Multi-Level Fusion long short-term memory based on Component Evaluating Empirical Mode Decomposition and Fuzzy C-Means (CEEMD-FCM & MLF-LSTM) for parameter prediction of reciprocating compressor and an information fusion strategy is proposed for compressor valve fault warning. The CEEMD-FCM & MLF-LSTM network consists of data processing block, information learning block, and prediction output block, which is mainly responsible for parameter prediction. In the data processing block, the CEEMD-FCM algorithm is used for parameter decomposition, noise removal, and fuzzy mode (FM) reconstruction, which generates the input for the information learning block to ensure the predicting accuracy and reduce model complexity. MLF-LSTM is constructed to predict the parameter in the future by learning the temporal and spatial characteristics of FMs of the run data. Then, an early warning strategy for compressor valve fault based on multi-source information fusion is developed. Experimental results have verified that the proposed CEEMD-FCM & MLF-LSTM model and early warning strategy could realize early warning of compressor valve fault effectively.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-08T11:43:51Z
      DOI: 10.1177/01423312221110896
       
  • Incremental adaptive optimal control for nonlinear systems with
           disturbance and input time-delay

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      Authors: Shaojie Zhang, Kun Ji, Han Zhang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a model-free incremental adaptive optimal control scheme is proposed for nonlinear systems in presence of disturbance and input time-delay. The linear time-varying approximate model of the nonlinear system is obtained by incremental method, in which the relevant matrix parameters are identified by recursive least squares (RLS) estimation. A time-delay matrix function is constructed by neural network (NN) to eliminate the input time-delay, and the external disturbance of nonlinear system is dealt with by [math] optimal control; incremental adaptive dynamic programming (IADP) algorithm is used to get the control law by solving Hamilton–Jacobi–Isaacs (HJI) equation. Convergence analysis of the proposed control scheme is provided. Simulations are given to verify the effectiveness of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-05T12:39:29Z
      DOI: 10.1177/01423312221114687
       
  • Remaining useful life prediction for lithium-ion batteries in later period
           based on a fusion model

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      Authors: Li Cai
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Lithium-ion batteries are broadly used in many fields. Accurate remaining useful life (RUL) prediction ensures the reliable operation and the safety of battery systems. However, no single model can realize long-term prediction for RUL with the reliable uncertainty management in the later period. To this end, a competitive model based on an improved autoregressive (AR) and particle filter (PF) model is proposed. Specifically, the similarity capacity series is creatively employed in the AR model, while the underlying capacity is introduced as a new approach for the parameter estimation of the observation equation in PF. Then, average weight is used to update the state equation and describe the future system states. After that, the RUL and its probability density function are obtained by PF again. The effectiveness and robustness are verified by the National Aeronautics and Space Administration (NASA) dataset. Results illustrate that the fusion model outperforms others and accurately predicts RUL with narrow uncertainty representation in the later period.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-05T12:37:22Z
      DOI: 10.1177/01423312221114506
       
  • Integrated navigation system (INS/auxiliary sensor) based on adaptive
           robust Kalman filter with partial measurements

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      Authors: Seyed Mostafa Hosseini, Abolfazl Ranjbar Noei, Seyed Jalil Sadati Rostami
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Inertial navigation system (INS) is the most common positioning system in the underwater vehicle due to the limitations of penetration of the global navigation system. Amendment of INS cumulative error is made possible using data of auxiliary sensors such as Doppler velocity log (DVL). Due to the environmental conditions of the seabed, access to full DVL beams is impractical. Moreover, the statistical characteristics of measuring noise are unknown. These dramatically reduce the performance of the navigation system. Therefore, a loosely coupled (LC) approach is used to fuse partial DVL measurements in this study. This approach benefits from a virtual beam containing the velocity obtained in the last INS step instead of inaccessible DVL beams. To deal with the unknown statistical characteristics of the measurement and the limitations of access to DVL beams, an adaptive robust Kalman filter (ARKF) based on the Huber cost function is proposed. The performance of the proposed integrated navigation system for a remotely operated vehicle is investigated in the presence of observation noise and outliers. Results show that the proposed ARKF is robust against vigorous maneuvers, improves the estimation accuracy effectively, and can effectively reject measurement outliers.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-05T12:34:29Z
      DOI: 10.1177/01423312221112192
       
  • A hybrid Aquila optimizer and its K-means clustering optimization

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      Authors: Cheng Huang, Jinglin Huang, Youquan Jia, Jiazhong Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Aiming at the defects of the Aquila optimizer (AO) in dealing with some complex optimization problems, such as slow convergence speed, low convergence accuracy, and easy to fall into local optimum, in this paper, a hybrid Aquila optimizer (HAO) algorithm based on Gauss map and crisscross operator is proposed. First, Gauss map is introduced to initialize the Aquila population to improve the quality of the initial population. Then use the crisscross operator to promote the exchange of information within the population and maintain the diversity of the population in each iteration, which not only enhances the ability of the algorithm to jump out of the local optimum but also accelerates the global convergence of the algorithm. The results of experiments using 21 classical benchmark functions indicate that HAO has better global search ability, faster convergence speed, and better stability than AO. The overall optimization performance of HAO in different dimensions is better than particle swarm optimization (PSO) algorithm, gray wolf optimization (GWO) algorithm, whale optimization algorithm (WOA), and crisscross optimization (CSO) algorithm. Finally, the results of K-means clustering optimization on six University of California (UCI) standard data sets demonstrate that HAO has significant advantages over three algorithms that are good at clustering optimization.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-05T12:30:49Z
      DOI: 10.1177/01423312221111607
       
  • Finite time adaptive neural tracking control for non-strict-feedback
           uncertain non-linear systems with disturbance and input delay

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      Authors: Junchang Zhai, Huanqing Wang, Jiaqing Tao, Zuowei He
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, based on neural networks (NNs), we consider finite time adaptive tracking control scheme for non-strict-feedback uncertain non-linear systems with time-variant external disturbance and input delay. A novel auxiliary system has been introduced to degrade the design difficulty caused by input delay. For the unknown non-linear functions and uncertainties in each step, radial basis function NNs are introduced to approximate them such that the control objective can be obtained. Furthermore, based on the idea of backstepping technique, an effective finite time adaptive neural tracking controller has been obtained in the presence of finite time Lyapunov theory, and the singularity problem that may occur in the design process has been overcome using the piecewise functions method. Using the Lyapunov stability theorem, which shows that all the signals of the closed-loop systems are finite time bounded, and the tracking error fluctuates around the origin. Consequently, the proposed scheme not only solves the tracking problem of non-strict-feedback systems with input delay but also realizes the finite time stability performance constraint. Finally, the simulations of two examples show the superiority of the proposed scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-05T12:28:29Z
      DOI: 10.1177/01423312221110437
       
  • Dynamic event-triggered [math] filtering for discrete-time singular
           networked control system subject to cyberattacks

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      Authors: Qiyi Xu, Linshuai Ge
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the event-triggered filtering problem for the discrete-time singular networked control systems (DSNCS) with random cyberattacks. To more effectively utilize the limited network resource, a new dynamic event-triggered mechanism is proposed, which can effectively reduce network information transmission and save bandwidth on the premise of ensuring system performance. By considering the effect of the event-triggered mechanism and two types of cyberattacks, the filtering error system model has been constructed. Two independent random variables obeying the Bernoulli distribution are introduced to describe the two types of cyberattacks. Sufficient conditions that can guarantee the admissibility of the filtering error system have been developed with Lyapunov stability theory and LMIs techniques. Moreover, the co-design method is present in terms of LMIs to derive the parameters of dynamic event-triggered mechanism and the designed [math] filter synchronously. Finally, an illustrative example is employed to verify the usefulness of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-05T12:26:29Z
      DOI: 10.1177/01423312221107989
       
  • Nonlinear time-varying sliding mode synchronous control of double-lift
           overhead cranes under unknown disturbances

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      Authors: Xinlei Zhu, Weimin Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      During the synchronous operation of the double-container, the double-lift overhead cranes suffer from the perturbation of system internal parameters, friction and external unknown disturbances. To address the impact of the above-mentioned negative factors, based on the mathematical model of induction motor and the coupled dynamics model of double-container, this paper proposes a synchronous control method combining variable gain extended state observer and nonlinear time-varying sliding mode surface for the synchronous coordination control of double-lift overhead cranes system. The load dynamics model of the double-container interlocking mode is established. Then, a nonlinear time-varying sliding mode surface is designed by means of nonlinear function and dynamic exponential term, which effectively speeds up the convergence of the system state and enhances the robustness of the system. Furthermore, the design adaptive reaching law is used to weaken the unwanted chattering and improve the performance of the controller. At the same time, the designed variable gain extended state observer estimates the aggregated disturbances in the system and then compensates them into the controller. The Lyapunov stability theory is used to prove the stability of the control system. The simulation experiments illustrate the effectiveness of the proposed synchronization control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-04T12:57:49Z
      DOI: 10.1177/01423312221105699
       
  • Security switching control of cyber-physical system with incremental
           quadratic constraints under denial-of-service attack

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      Authors: Younan Zhao, Fanglai Zhu, Wei Zhang, Housheng Su
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper presents an observer-based security control scheme for a nonlinear cyber-physical system (CPS). Specially, the nonlinearity satisfies the incremental quadratic constraints ([math]) which can represent many types of common nonlinearities. The problems are discussed under the assumption that both the feedback and forward channels may suffer from denial-of-service (DoS) attacks. The attack model is constructed in the form of time-delayed switching system with four subsystems corresponding to different attack situations. Then by using the attack model, an observer-based controller is constructed in the cyber layer to stabilize the CPS encountering DoS attacks. The closed-loop stability is analyzed based on H∞ index of switching systems in view of average dwell time (ADT) concept. Besides, the gain matrices of the controller and the observer are obtained by solving a series of matrix inequalities using an algorithm designed in this paper. Finally, the performance of security control scheme is presented by a simulation example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-04T12:56:10Z
      DOI: 10.1177/01423312221105141
       
  • Output feedback control for nonholonomic systems with nonvanishing
           disturbances and asymmetric time-varying constraints

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      Authors: Jie Zhang, Jing Yang, Zhongcai Zhang, Yuqiang Wu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, an adaptive output feedback control scheme is introduced for nonholonomic systems with nonliner uncertainties, nonvanishing disturbances, and output constraints. A tan-type barrier Lyapunov function is considered to address asymmetric time-varying output constraints. We define the disturbance as the generalized system state. The extended state observer is proposed for uncertain external disturbance. A new estimator is designed for unknown parameter and states. It is shown that under the backstepping technique the output feedback adaptive controller ensures the stability of the closed loop system, while the asymmetric time-varying output constraints are not violated. The simulation results of mobile robot system are provided to validate the effectiveness of the presented control approach.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-04T01:01:50Z
      DOI: 10.1177/01423312221111003
       
  • Observer-based integrated event–triggered sliding mode control for
           Internet of vehicles with communication constraints

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      Authors: Wei Yue, Hongxia Shen, Liyuan Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the co-design problem of the integrated event-triggering (IET) scheme and integral sliding mode control (ISMC) for the non-linear Internet of vehicles (IoVs) with communication constraints. The main goal is to improve the tracking performance and increase the bandwidth utilization of vehicular ad hoc networks (VANETs) with various external disturbances. First, a non-linear IoV dynamic model is established by considering the disturbance from the preceding vehicle, internal and external resistance, and uncertainty of the engine time constant. Second, an IET transmission mechanism based on both absolute and relative restriction conditions of sampled-data error is proposed to reduce unnecessary data transmissions among vehicles. Third, co-design IET mechanisms and ISMC controller based on estimated H∞ observer are designed, which can obtain the disturbance attenuation and asymptotic stability, and the result is complemented by additional conditions established for guaranteeing string stability. Finally, extensive simulations are conducted to verify the theoretical analysis and prove the effectiveness and superiority of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-04T01:00:09Z
      DOI: 10.1177/01423312221105969
       
  • Improving trajectory tracking performance of autonomous farming vehicles
           using adaptive extended state observer and finite-time technique

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      Authors: Ting Zhang, Xiaohong Jiao, Zhong Wang, Zhanmeng Lin
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The ability of the autonomous farming vehicle to accurately and quickly track complex reference trajectories in the field is critical to crop yields and farmer incomes. The novelty of this paper is to design a new adaptive finite-time trajectory tracking control strategy with an adaptive extended state observer to improve the autonomous farming vehicle’s trajectory tracking accuracy and convergence speed in the complex farm operating environment. The adaptive extended state observer is constructed to deal with the slip disturbance and parameter uncertainty to improve the tracking accuracy. The finite-time control strategy is adopted to improve the convergence speed of the trajectory tracking of the autonomous farming vehicle. The effectiveness and advantages of the proposed control strategy are verified by comparing it with the active disturbance rejection control and traditional PID control strategies under MATLAB/Simulink environment.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-03T12:56:08Z
      DOI: 10.1177/01423312221111614
       
  • A multi-model fusion soft measurement method for cement clinker f-CaO
           content based on K-means ++ and EMD-MKRVM

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      Authors: Rongfeng Zhang, Shizeng Lu, Xiaohong Wang, Hongliang Yu, Zhao Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The content of free calcium oxide (f-CaO) in cement clinker is a key indicator for testing the quality of cement clinker. To address the problem that the content of f-CaO cannot be detected online, a multi-model fusion soft measurement method based on K-means++ clustering, empirical modal decomposition combined with multi-kernel relevance vector machines (EMD-MKRVM) is proposed to predict f-CaO content under different operating conditions. First, time-series analysis and matching of input variables with f-CaO content were performed, based on which a combination of empirical modal decomposition (EMD) and sample entropy (SE) denoising method was used to filter out high- frequency noise from the original data and extract effective signal information for reconstruction. Second, the K-means++ algorithm was used to cluster the processed training sample data, and multi-kernel relevance vector machine (MKRVM) sub-models were established by training the sample data of each sub-class and then the affiliation between the test samples and each sub-class was calculated as the weights of the sub-model output values, and the final model prediction output was obtained by multi-model fusion. Finally, the real data from cement plants were used for validation. The results show that compared with the single MKRVM model, multi–relevance vector machine (RVM) model, multi–support vector machine (SVM) model, and multi-MKRVM model using only EMD denoising method, the mean absolute error (MAE) of the multi-MKRVM model proposed in this paper was reduced by 42%, 7%, 14%, and 35%; root mean square error (RMSE) is reduced by 28%, 10%, 12%, and 21%; squares due to error (SSE) is reduced by 51%, 24%, 27%, and 41%; Theils inequality coefficient (TIC) is reduced by 27%, 17%, 21%, and 19%; [math] is improved by 64%, 18%, 39%, and 91%; and Index of agreement (IA) is improved by 28%, 9%, 22%, and 13%. The multi-MKRVM model proposed in this paper has higher accuracy, better generalization ability and stability, and provides an effective method for f-CaO content prediction under complex multiple working conditions.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-02T11:58:58Z
      DOI: 10.1177/01423312221111001
       
  • State of charge estimation based on active disturbance rejection control
           for power batteries in engine waste heat recovery system

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      Authors: Zhengling Lei, Tao Liu, Hui Xie, Qiang Sun, Xiaoming Sun
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The Coulomb counting (CC) method is the most widely accepted state of charge (SOC) estimation method in the industry. However, the cumulative error generated during operation is a huge challenge for the engineering application. A feedback regulation framework is designed to address this situation; however, the basic problem of this framework is that the error regulation occurs only after the error is generated. As a result, its initiative to suppress system disturbance is insufficient. To overcome this problem, an active disturbance rejection control–based-feedback-estimator is proposed in this paper. The regulation is designed based on the terminal voltage error between actual measurement and theoretical value. And active disturbance rejection control is employed to improve the estimation accuracy and adaptability. The power batteries’ SOC estimation in engine waste heat recovery system is studied in this paper. Compared with the traditional CC method and a proportional–integral (PI) feedback estimation method, the proposed active disturbance rejection control-feedback-estimator exhibits better estimation performance and adaptability to system disturbances and uncertainties. There are only three parameters [math], [math], and [math] to tune, and estimation performance can be maintained without having to retune parameters when boundary conditions change, proving the effectiveness of the proposed active disturbance rejection control-feedback-estimator.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-02T11:57:18Z
      DOI: 10.1177/01423312221110439
       
  • Reference-trajectory-planner–based integrated guidance and control under
           input saturation and impact angle constraint

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      Authors: Haibin Wang, Peng Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the integrated guidance and control (IGC) problem for intercepting maneuvering targets subject to the impact angle and input saturation. In order to elegantly implement tracking control under constraints, the whole controller includes the reference trajectory planner for generating reference trajectory, and the reference trajectory tracking controller for tracking the generated reference trajectory. The trajectory tracking controller is based on the command filter backstepping design under the time-domain separation, and the reference trajectory planner with a kind of reference model governor takes into account the available regulation ability of the trajectory tracking controller, so as to improve the adaptability of the proposed control scheme. The two cooperate with each other to improve the stability of guidance interception system and come out a more reasonable interception path. The simulation comparison results are provided to illustrate the superiority of the reference-trajectory-planner–based IGC law.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-02T11:55:37Z
      DOI: 10.1177/01423312221110045
       
  • Active damping control strategy for a parallel hybrid electric vehicle
           based on model predictive control

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      Authors: DF Song, DP Yang, XH Zeng, ZW Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Since the coupling relationship of excitation sources is complicated, meantime the motor torque changes quickly under the acceleration condition, the problem of torsional vibration is prominent. This paper studies an active damping control (ADC) strategy for a parallel hybrid electric vehicle (HEV) under acceleration condition. Primarily, a full-order dynamic model is built, and the corresponding motion equations are derived. Moreover, a controller design–oriented model is established based on model reduction algorithm. Furthermore, a method that considers time delay characteristics of actuator based on model predictive control (MPC) theory is proposed to solve the torsional vibration problem. The controller handles delay characteristics of an actuator by state-space reorganization method, and the optimal control sequence is obtained by solving the objective function. Finally, the controller is tested using Simulink simulation and hardware-in-loop simulation platform, which mainly includes the verification of model reduction and vibration damping effect. The results show that simplified third-order model has a good consistency with the original full-order model in time and frequency domain. Meanwhile, the designed controller has a considerable damping effect and ensures the comfort performance of the vehicle. This study provides an important reference for vibration control of the hybrid powertrain.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-02T11:53:58Z
      DOI: 10.1177/01423312221105936
       
  • A 3D LiDAR odometry for UGVs using coarse-to-fine deep scene flow
           estimation

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      Authors: Chi Li, Fei Yan, Sen Wang, Yan Zhuang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Light detection and ranging (LiDAR) odometry plays a crucial role in autonomous mobile robots and unmanned ground vehicles (UGVs). This paper presents a deep learning–based odometry system using two successive three-dimensional (3D) point clouds to estimate their scene flow and then predict their relative pose. The network consumes continuous 3D point clouds directly and outputs their scene flow and uncertain mask in a coarse-to-fine fashion. A pose estimation layer without trainable parameters is designed to compute the pose with the scene flow. We also introduce a scan-to-map optimization algorithm to enhance the robustness and accuracy of the system. Our experiments on the KITTI odometry data set and our campus data set demonstrate the effectiveness of the proposed deep learning–based point cloud odometry.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-02T11:52:44Z
      DOI: 10.1177/01423312221105165
       
  • Improvement of multi-item order systems and inventory management models
           using optimal control theory

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      Authors: Mahdi Nakhaeinejad, Hassan Khademi Zare, Mohsen Habibi, Mohammad Reza Khodoomi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In the competitive market, applying effective and efficient inventory control and order management methods to reduce costs and improve service efficiency and quality, leading to profit maximization, becomes an absolute necessity at the organizational and supply chain level. Therefore, this study used the optimal control theory to propose an order system and inventory management model. The model is presented from the company’s resourcing stage with a desirable accountability level from the supplier side in a continuous review period with dynamic multi-item demand and budget constraints. In the present model, the order was regarded as a time-dependent function and a control variable. In addition, the need for each item is time-dependent and specified. The present model indicates the order and inventory system as an optimal control problem. In addition, Pontryagin’s maximum principle for optimal control problems, Generalized Reduced Gradient Method (GRG), and Kuhn–Tucker conditions were used to seek the optimal order. The model aimed to maximize the total order profit and inventory management systems. Finally, the results were presented numerically and graphically, and some management decisions were derived.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-01T12:06:16Z
      DOI: 10.1177/01423312221109724
       
  • Wavelet-based multi-class support vector machine for stator fault
           diagnosis in induction motor

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      Authors: Abdelelah Almounajjed, Ashwin Kumar Sahoo
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This work proposes a novel online detection scheme to diagnose incipient inter-turn short circuit fault and estimate the failure severity in induction motor. Incipient detection of the stator failure during the machine running, as well as identification of its intensity can reduce the risk of additional damage to the phase winding, improve the operational efficiency, and ensure machine availability. Hence, the incipient fault diagnosis provides a safe operating area for the motor. This work aims to specify the percentage of defective turns in the shorted winding by proposing a new mathematical parameter based on wavelet analysis, in addition to employ a multi-class support vector machine to perform the classification task. Discrete Wavelet Transform is used to analyze the stator currents after modeling the motor utilizing Clarke-Concordia transformation. From the detailed coefficients, Max and L2 norms are calculated. The adopted parameter is computed depending on the previous norms, which form the input vector to feed the classifier. The multi-class support vector machine–based one versus one algorithm is used to determine accurately the defect intensity. The acquired outcomes prove that the proposed approach, depending on the novel parameter along with multi-class support vector machine can give a robust and accurate indication about the machine status, which enables the estimation of the fault severity. To verify the competency of the methodology, various hardware experiments are carried out on the motor. The experimental results demonstrate the validity and practicability of the method, with a higher level of correctness, exceeding 96%.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-08-01T11:08:40Z
      DOI: 10.1177/01423312221109725
       
  • Adaptive invariant Kalman filtering for lie groups attitude estimation
           with biased and heavy-tailed process noise

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      Authors: Jiaolong Wang, Chengxi Zhang, Jinyu Liu, Caisheng Wei, Haitao Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Attitude determination is fundamental for spacecraft missions in aerospace engineering. Kalman filter (KF) is the optimal estimator in least square sense and, using the symmetry properties of matrix Lie groups system, the invariant Kalman filter (IKF) has been developed to boost the filtering performance for attitude estimation. However, due to presence of frequent and severer maneuvers, the Lie groups attitude dynamics is usually corrupted by significant biases and heavy-tailed outliers, which usually leads to decreased precision of IKF. For attitude estimation problem troubled by biased and heavy-tailed process noise, this work proposes a new invariant Kalman filter (VBAIKF) by constructing the hierarchical Gaussian system model: the probability density function of prior estimate state is first described using the student’s t distribution, while the unknown scale covariance matrix and degrees of freedom (dof) of the employed student’s t distribution are defined as the inverse Wishart distribution (IWD) and Gamma distribution. In VBAIKF, the Lie groups rotation matrix of spacecraft, the biased mean, the parameters of dof and scale covariance matrix are online estimated together by variational Bayesian fixed-point iterations. The simulation results with Lie groups attitude estimation system further verify the superior filtering adaptability and precision of proposed approach VBAIKF than other methods for attitude determination with biased mean and heavy-tailed process noise.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-29T09:35:07Z
      DOI: 10.1177/01423312221110956
       
  • Non-fragile consensus control for nonlinear singular multi-agent systems:
           An event-triggered sampling scheme

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      Authors: Qi Niu, Lin Li, Chaoli Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is devoted to the problem of non-fragile consensus control for a class of nonlinear singular multi-agent systems based on an event-triggered control strategy. To reduce the resource occupancy, a decentralized event-triggered sampling consensus control protocol for each agent is proposed, which does not require continuous communication among agents. Analysis of non-fragile consensus problem in the multi-agent systems is transformed into asymptotical stability issues of some lower dimensional subsystems via nonsingular transformation. Using the Lyapunov theory, sufficient conditions are obtained such that for all possible norm-bounded parameter variations in the protocol gains, the designed protocol can bring all agents’ states to a point of agreement. Furthermore, the corresponding protocol design method is also given. Numerical examples are included to illustrate the effectiveness of the derived results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-27T11:45:13Z
      DOI: 10.1177/01423312221107977
       
  • Fault monitoring of batch process based on multi-stage optimization
           regularized neighborhood preserving embedding algorithm

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      Authors: Xiaoqiang Zhao, Kai Liu, Yonyong Hui
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Batch process is an important type of industrial production process, and the process mechanism is complex. It is difficult to accurately describe the dynamic changes of the production process of multi-stage time-varying batch process. In addition, the data of batch process contain not only global information but also local information. The traditional neighborhood preserving embedded algorithm is used to maintain the local geometric structure of data while ignoring the global information, and the extracted latent variables cannot fully characterize batch process. Therefore, we propose a multi-stage optimization regularized neighborhood preserving embedding (ORNPE) algorithm. First, the multiple process stages are separated by affinity propagation (AP) algorithm. Second, based on maintaining local information of neighborhood preserving embedding algorithm, slow feature analysis algorithm is used to extract dynamic time-varying global information. Then, cross-entropy is used to optimize the global information, and the extraction ability of the global information is improved. Finally, a monitoring index based on support vector data description is constructed to eliminate adverse effects of non-Gaussian data for monitoring performance. The effectiveness and advantages of the proposed algorithm based on monitoring strategy are illustrated by the penicillin fermentation process and a semiconductor industry process.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-27T06:43:09Z
      DOI: 10.1177/01423312221108519
       
  • Outlier-resilient iterative-extended Kalman filter based on maximum
           correntropy criterion

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      Authors: Wenshuo Li, Lei Guo
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The extended Kalman filter (EKF) is the most popular tool for state estimation of nonlinear stochastic systems. The conventional EKF can be refined via iterative re-linearization, leading to the so-called iterative EKF (IEKF). The performance of either EKF or IEKF will deteriorate in the presence of outliers. In this article, an outlier-resilient IEKF method is proposed using a more robust cost function, the correntropy, to replace the traditional mean squared error criterion. An iterative procedure is derived to maximize the correntropy criterion in a similar way to the Gauss–Newton optimization. Simulation results demonstrate the superiority of the proposed method as compared to the existing methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-25T07:02:06Z
      DOI: 10.1177/01423312221105935
       
  • A robust model predictive control-based method for fault detection and
           fault tolerant control of quadrotor UAV

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      Authors: Arman Mohammadi, Amin Ramezani
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, first a model predictive control (MPC) solution is utilized to control the quadrotor model in both fault-free and faulty modes by employing a cost function. For this aim, the obtained non-linear continuous model has been discretized after linearization around an equilibrium point. Then, a fault detection and diagnosis (FDD) and fault tolerant control (FTC) strategy is proposed based on MPC in order to neutralize the effect of fault. The method of FDD and FTC designing is based on analytical redundancy relations (ARRs) which detects and tolerates the fault by producing a residual signal. Therefore, this method presents a complete FTC solution to fault issue without using observer. In addition, this solution has robustness against the uncertainties and disturbances which may challenge the model in practical situations. The discussed fault in this paper is a sensor fault which is modeled as an undesired function which affects the sensor of roll angle. However, the proposed FTC can tolerate all types of faults. The results of implementation of this method are validated under various simulation scenarios.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-19T01:09:51Z
      DOI: 10.1177/01423312221107971
       
  • Disturbance observer–based finite-time control for a class of systems
           with multiple heterogeneous disturbances

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      Authors: Huifeng Zhang, Xinjiang Wei, Hanxu Zhao, Xin Hu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The finite-time anti-disturbance control problem is studied for systems with multiple heterogeneous disturbances, which include the disturbance with partially known information and the external disturbance. A disturbance observer is designed to online estimate the disturbance with partially known information. Based on this, a disturbance observer–based finite-time control (DOBFTC) scheme is presented by combining disturbance observer–based control (DOBC) with finite-time control method to guarantee that the composite system is globally finite-time stable. Two simulation examples including a numerical example and a doubly fed induction generators (DFIG) system are given to show the effectiveness of the proposed method compared with the existing schemes.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-19T01:07:43Z
      DOI: 10.1177/01423312221105971
       
  • Event-triggered cluster consensus for two classes of nonlinear multi-agent
           systems

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      Authors: Yaping Xia, Jiaxu Ma, Renfei Liu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the cluster consensus problems of two classes of leader-following nonlinear multi-agent systems (LFNMASs). The event-triggered strategies are applied to solve the problems, which can significantly reduce energy consumption and the frequency of the controller updates. The sufficient conditions are presented to realize the cluster consensus for two classes of LFNMASs. Then, it is proved that the Zeno behavior can be avoided under the proposed event-triggered control strategies. Finally, two numerical examples are given to demonstrate the effectiveness of the theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-19T01:04:48Z
      DOI: 10.1177/01423312221105943
       
  • An energy storage coordinated control strategy based on model predictive
           control for smoothing wind power fluctuations

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      Authors: Yao Zhao, Lina Deng, Dongdong Li, Fan Yang, Yang Mi, Miao Zhu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Based on the nature of wind, wind power fluctuations can cause significant problems in the distribution network. One of the solutions is to integrate an energy storage system with wind farm to mitigate the output power fluctuations. Therefore, an energy storage coordinated control strategy based on model predictive control is proposed to smooth minute-scale fluctuations of wind power. By analysing the limitations of traditional control strategy, four operating modes of battery energy storage system which are determined by the predicted state of charge obtained by model predictive control, are designed to avoid violating the state of charge limitation, and an energy state feedback control is designed to adjust the initial power allocation orders of batteries. Finally, the effectiveness of the proposed control strategy can be verified by the real-time digital simulator. The results indicate that the developed approach reduces the switching times of batteries and improves the ability of the battery energy storage system to smooth wind power fluctuations significantly.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-14T06:23:35Z
      DOI: 10.1177/01423312221104482
       
  • Autonomous deck landing of a vertical take-off and landing unmanned aerial
           vehicle based on the tau theory

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      Authors: Biao Wang, Haiwei Lin, Chaoying Tang, Guili Xu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The research on autonomous landing of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs) is well established. However, the research on autonomous deck landing using visual methods is relatively not so mature and many of them require the support of ground infrastructures. In order to reduce such dependencies, a ship landing guidance strategy based on on-board vision is studied. Considering the characteristics of the ship landing issue, we propose a three-phase landing scheme and a decision-making method to ensure landing safety is also studied. For improving the traditional two-dimensional (2D) optical-flow method, a three-dimensional (3D) velocity vector estimation method using image spherical optical flow is studied. Furthermore, a guidance law based on the tau theory is employed by only using the visual information of the line of sight to the target. In this phase, a trajectory-tracking controller is applied to generate the velocity commands of the UAV. Finally, the whole algorithm is validated by simulation in different wave conditions developed with Unity3D. Compared with traditional trajectory planning methods, our method does not require complex optimization iterations and can meet both the real-time and accuracy requirements of deck landing. The average tracking error of our method maintains in 0.2 m. Moreover, the whole algorithm runs efficiently at around 30 fps on a Raspberry-Pi 3B+ microcomputer which meets the real-time requirements.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-14T06:19:36Z
      DOI: 10.1177/01423312221104424
       
  • Terminal sliding mode observer based–asymptotic tracking control of
           electro-hydraulic systems with lumped uncertainties

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      Authors: Shuai Li, Qing Guo, Yao Yan, Yan Shi
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Since the existence of lumped uncertainties caused by uncertain parameters and unmeasured external load, the disturbance suppression is always a significant issue in research of electro-hydraulic system (EHS). In this paper, a type of terminal sliding mode observer (TSMO) is introduced for EHS, based on which the disturbances can be converged in a finite time. Then, based on TSMO, a controller is designed via recursive backstepping method to realize the displacement tracking control of EHS. Finally, simulated results are given to verify the feasibility of the proposed theoretical conclusions and a series of contrast experimental results are also given to illustrate the better performance of TSMO and proposed control strategy than others.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-13T09:53:11Z
      DOI: 10.1177/01423312221105136
       
  • Finite frequency fault estimation and fault-tolerant control for dynamics
           of high-speed train based on descriptor systems

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      Authors: Tiantian Liang, Xin Liu, Xiang Zheng, Mao Wang
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, novel fault estimation and fault-tolerant control methods are proposed for dynamics of high-speed train based on descriptor systems with uncertainties in finite frequency domain. Dynamics of high-speed train is established based on multi-particle model considering that basic resistance is seen as the coefficient of state variables, and additive resistance and the operating noise are seen as multi-source disturbance. Concurrent actuator, sensor faults, and wind gust are considered simultaneously; wind gust is modeled as a disturbance generated by the exogenous system, and an uncertain descriptor system with actuator fault and the exogenous disturbance is established by seeing the sensor fault of high-speed train as the state variables. A robust disturbance-observer-based fault estimation method is proposed to decouple the non-linearity of the descriptor system, so that the combining estimation of the fault and wind gust is implemented. This observer has an unknown input structure, and its gain matrices are formulated as linear matrix inequalities. The observer not only guarantees the augmented state estimation error is asymptotic stable but also the actuator fault estimation and wind gust estimation errors are robust to the multi-source disturbance and the uncertainties. Based on the estimation results, the fault-tolerant controller associated with the state estimation, faults estimation, and wind gust estimation results is proposed to implement a stable close-loop fault-tolerant control for dynamics of high-speed train. Simulation examples are given to illustrate the effectiveness of this method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-09T11:47:46Z
      DOI: 10.1177/01423312221104091
       
  • Output containment control for heterogeneous discrete-time linear
           descriptor multi-agent systems by a feedforward output regulation approach
           

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      Authors: Yanrong Lu, Yajing Lin, Zhiwen Wang, Dawei Ding, Liang Qiao
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper studies the cooperative output containment control of the heterogeneous linear discrete-time descriptor multi-agent systems based on the output regulation theory. First, the output containment control problem is transformed into a standard cooperative output regulation problem. Second, since only a portion of the followers can directly obtain the information of the leaders, a new distributed observer is designed for each follower to estimate the combinations of the leaders’ states by using the local state containment errors. Third, two types of distributed control algorithms, as well as the corresponding sufficient conditions, are provided to ensure the achievement of the output containment control. Finally, numerical simulation results illustrate the validity of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-07T10:29:11Z
      DOI: 10.1177/01423312221105944
       
  • Observer-based guaranteed cost control for networked control systems with
           packet dropout and nonlinear disturbance

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      Authors: Hongchun Qu, Na Wei, Mengyue Li, Yu Li
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this article, the observer-based guaranteed cost control method is investigated for the networked control systems (NCSs) with packet dropout and nonlinear disturbance involving event-triggered mechanism (ETM). The packet dropout processes, which appear in both the sensor-to-controller and the controller-to-actuator links, are represented by two mutually independent Bernoulli distributions, and the nonlinear disturbance is supposed to satisfy the Lipschitz condition. Since the systems states are unmeasurable, a state observer is designed to estimate the values of system state. The sufficient condition for the stability of the closed-loop system is addressed by applying the Lyapunov theorem, and a guaranteed cost controller is obtained based on the stability condition with the satisfaction of some given specified value of cost function. Furthermore, the controller design issue can be formulated as a convex optimization problem that is addressed by the linear matrix inequality (LMI) technique using the cone complementarity linearization algorithm. Finally, the availability of above method is proved by a simulation example.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-07T10:23:49Z
      DOI: 10.1177/01423312221105140
       
  • Exponential H∞ stabilization of uncertain neural networks with
           time-varying delay and external disturbance via periodically intermittent
           control

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      Authors: Liangliang Guo, Yali Dong, Yuhao Cong
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper is concerned with the exponential [math] stabilization for a class of uncertain neural networks with interval time-varying delay and external disturbance via periodically intermittent control. By constructing a novel Lyapunov–Krasovskii functional (LKF) and applying some inequality techniques, delay-dependent sufficient conditions are derived to guarantee the exponential [math] stabilization of the considered closed-loop system. These conditions are given in the form of linear matrix inequalities (LMIs). The intermittent state-feedback controller can reduce the effect of external disturbance to a prescribed attenuation level [math]. Furthermore, the desired controller gain matrix can be obtained by solving the obtained LMIs. Finally, numerical simulations are given to show the effectiveness and the benefits of the proposed method.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-07-02T06:38:47Z
      DOI: 10.1177/01423312221100635
       
  • Unmanned aerial vehicle formation obstacle avoidance control based on
           light transmission model and improved artificial potential field

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      Authors: Jiacheng Li, Yangwang Fang, Haoyu Cheng, Zhikai Wang, Shuaiqi Huangfu
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      To overcome the limitations of the conventional artificial potential field (APF) method, which is commonly used for unmanned aerial vehicle (UAV) formation obstacle avoidance control. A novel UAV formation obstacle avoidance control method based on a light transmission model (LTM) and an improved APF method is proposed. First, inspired by the flight of bird flocks, we combine the LTM with an APF function to present an improved APF model which can help UAV find feasible free space to maneuver. From this, UAV can overcome the drawbacks of non-reachable and local minima under the action of LTM. Then, the obstacle avoidance strategy based on the fixed-wing UAV motion model is proposed, and the obstacle avoidance control algorithm for UAV formation is designed. Finally, simulation results show the effectiveness and superiority of the proposed method, which can result in a dramatic improvement in the performance of UAV formation to obstacle avoidance under the complex and non-deterministic environment.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-06-29T06:24:50Z
      DOI: 10.1177/01423312221100340
       
  • Feature extraction and fault detection scheme via improved locality
           preserving projection and SVDD

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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      Authors: Qiangde Wang, Yang Zhang, Chunling Wei
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper investigates the containment control problem for multiple Euler–Lagrange systems with unknown time-varying disturbances over directed graphs, in which the dynamics of leaders and followers are heterogeneous. First of all, the expected output signals of leaders can only be acquired by some subsystems owing to the limited communication conditions, and the output adjustment errors are obtained indirectly by other subsystems through the network connection. In consequence, a compensator based on relative output information is designed to estimate a trajectory inside the convex hull spanned by states of the leaders. Second, a fully distributed event-triggered adaptive control scheme is proposed, and a disturbance estimator is designed to achieve interference suppression. In addition, the design of the overall control protocol does not use the relative speed of the followers. Finally, a dual-axis manipulator is taken as an example to validate the effectiveness of the proposed control scheme.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-05-01T01:31:23Z
      DOI: 10.1177/01423312221088656
       
  • A method for robust quadratic pole assignment

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

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

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

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

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

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

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

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

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

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

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      Authors: Manikandan Subramanian, Priyanka Kokil
      First page: 2475
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This paper describes the stability assurance of network-controlled aircraft pitch control system with time delays. A frequency-domain method is used to determine the upper bound of time delay for aircraft pitch control system with gain and phase margin constraint. The effectiveness of proportional-integral (PI) and fractional-order PI controller on aircraft pitch control system stability and performance is investigated in presence of time delay. The parametric space of the PI and fractional-order PI controller are plotted in two-dimensional space to determine the stability region and controller is designed with concern to the time delay. The relation between controller parameters and time delay is estimated and these findings contribute significantly for the design of the controller for aircraft pitch control system. The accuracy of the proposed results is validated using simulation benchmark.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-04T10:52:28Z
      DOI: 10.1177/01423312221083756
       
  • The feedback stabilization of finite-state fuzzy cognitive maps

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      Authors: Wang Xiaojie, Luo Chao, Lv Chen
      First page: 2485
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Fuzzy cognitive maps (FCMs) are a kind of cognitive model for knowledge representation and causal inference. Meanwhile, as fuzzy dynamical systems, FCMs have also been widely applied in the control-related fields, such as mobile robots, unmanned aerial vehicles (UAVs), and industrial controls. However, the existing works mainly focused on the practical applications but lacked the necessary theoretical discussions related to the FCM-based control mechanism. As is known, stabilization is one of the fundamental issues in the control fields. Till date, rigorous research on the stabilization of FCMs is still an issue to be studied. In this article, using state feedback control method, the global stabilizations of finite-state FCMs are investigated. First, utilizing the semi-tensor product (STP) of matrices, the algebraic expression of FCM can be derived. Some theorems ensure the sufficient condition for the existence of the state feedback controller of the global stabilization. Second, the constructive design processes of state feedback controllers are discussed in detail. Third, the global stabilization is further extended into partial stabilization, where only specific concepts of FCMs can be stabilized. The corresponding theoretical analysis is implemented. Finally, the effectiveness of the proposed methods is verified by several examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-05T11:39:09Z
      DOI: 10.1177/01423312221085785
       
  • Dynamic surface control for formation control of quadrotors with input
           constraints and disturbances

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      Authors: Ao Dun, Rui Wang, Fei Lei, Yuning Yang
      First page: 2500
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a novel formation control scheme is presented by integrating the dynamic surface control for multi-quadrotor subject with model uncertainties and external disturbances. First, according to requirements of formation control, the target trajectories of followers are obtained by the designed virtual quadrotors. Then, the formation control problem is transformed into the trajectory tracking control problem. Second, the saturation function and the auxiliary system are developed to make up for nonlinear terms arising from input saturation. A nonlinear extended state observer (ESO) is proposed to estimate and compensate for model uncertainties and external disturbances, and a dynamic surface controller based on the nonlinear ESO is constructed for the desired formation performance. In addition, the amount of communications between the quadrotors is decreased by the constructed distributed speed estimator. And the uniformly ultimately bounded is proved by using the Lyapunov method. Finally, the numerical example is used to demonstrate that the designed controller is effective.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-07T05:10:55Z
      DOI: 10.1177/01423312221085391
       
  • Finite-time bounded control for quadrotors with extended dissipative
           performance using a switched system approach

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      Authors: Liang Nie, Bo Cai, Yunpeng Li, Hui Wang, Lixian Zhang
      First page: 2511
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In order to deal with the problem of attitude tracking control for quadrotors subject to time-varying inertia and external disturbances, a finite-time bounded switched linear parameter-varying (LPV) control method is presented. The attitude dynamics is described by two subsystems, where the inner angular-velocity system is used to track the desired angular velocities that are generated by the outer attitude-angle system. The angular-velocity system of quadrotors is modeled as a switched LPV model, where a family of linear models is developed to approximate the original nonlinear system and the LPV method is applied to model the time-varying inertia. Specially, a mode-dependent persistent dwell-time (MPDT) switching logic, which is more general than the typically used dwell-time (DT) or average dwell-time (ADT) switching logic, is adopted to govern the switching behaviors among these linear models. A state-feedback controller for the switched LPV error-tracking system is designed, which ensures both finite-time boundedness and extended dissipative performance. Finally, the developed theoretical results are verified by numerical simulation.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-07T11:17:47Z
      DOI: 10.1177/01423312221085140
       
  • Consensus of piecewise time-varying multi-agent systems with switching
           topologies

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      Authors: Jian Sun, Chen Guo, Lei Liu
      First page: 2522
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, a consensus problem is first investigated for piecewise time-varying multi-agent systems with switching topologies. Due to the piecewise time-varying characteristics of system matrix, it is challenging to design an appropriate controller to stabilize the error state within each piecewise time period. To overcome this difficulty, a piecewise time-varying Lyapunov function (PTVLF) approach is proposed to analyze the piecewise time-varying systems. Then, a useful lemma guaranteeing the negative definiteness of matrix polynomials is first derived, which is utilized to prove the negative definiteness of the derivative for the PTVLF. Based on this, a novel controller with time-varying gain is presented to stabilize the error state within each piecewise time period. Then, by selecting the dwell time of each topology larger than a positive threshold, the overall consensus of such systems is guaranteed. Finally, a numerical simulation is shown to illustrate the theoretical results.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-08T12:23:55Z
      DOI: 10.1177/01423312221085786
       
  • Multi-objective parametric design of PI/PID controllers via multi-level
           game-theoretic optimization for systems with time delay

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      Authors: SH Ashraf Talesh, N Nariman-zadeh, A Jamali
      First page: 2532
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this research study, a new methodology of multi-objective optimal design is presented for control systems with time delay. Stackelberg method as an approach of game theory is implemented to develop the multi-objective optimization of proportional–integral (PI) and proportional–integral–derivative (PID) controllers. The surface area of control effort and tracking error are put in order of precedence together as the more important conflicting objective functions of the players in Stackelberg game design. Besides, the desirability of other effective criteria including frequency and time domains are measured as constraints in the procedure of the game-theoretic design. The main purpose of the proposed method is to optimally set and formulate controller parameters in the Stackelberg game-control system (SG-CS) design. Mapping the leader’s variables into the optimized values of the follower’s variables obtained via differential evolution (DE), the effectiveness of the proposed method is demonstrated in constructing a simple and explicit approximate model for rational reaction sets (RRSs). These obtained optimal models for the RRS allow the user to access the set of optimal controller parameters in the entire accessible strategic space of design variables in a formulated form. Utilizing the optimal synthesis for two case studies is validated the superiority of SG-CS design in establishing the explicit relationship between the controller’s parameters.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T09:57:14Z
      DOI: 10.1177/01423312221086812
       
  • Feedback error learning neural network for stable control of nonlinear
           nonaffine systems

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      Authors: Masoud Asgari, Mersad Asgari
      First page: 2545
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This study presents a stable feedback error learning (FEL) scheme for nonlinear nonaffine systems in the presence of uncertainty and disturbances. The distinguishing feature of the FEL method, which can have a significant effect on both transient and steady-state performance, has led us to adopt this approach. The nonlinear system studied here is nonaffine. In other words, the function that describes the dynamic equations of the system is an implicit function of the control input rather than a particular class of systems. We aim to develop a stable FEL control system with three components: a neural network (NN), a linear controller, and a robustifying control term. To this end, all the adaptation laws for the NN weights are derived from a Lyapunov function, ensuring that the closed-loop system is uniformly asymptotically stable (UAS). Thus, an NN learning control approach that effectively improves the transient performance, as well as the steady-state performance, is proposed, and its remarkable effectiveness is illustrated in comparison with the existing methods.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T09:53:43Z
      DOI: 10.1177/01423312221086076
       
  • Full adaptive Kalman filters for nonlinear fractional-order systems
           containing unknown parameters and fractional-orders

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      Authors: Xiaomin Huang, Zhe Gao
      First page: 2557
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this study, full adaptive Kalman filters are designed for continuous-time nonlinear fractional-order systems (FOSs) containing unknown parameters and fractional-orders. First, the estimated FOS is discretized using the Grünwald–Letnikov difference method to transform the fractional-order differential equation into a difference equation. Then, in terms of the nonlinear function contained in the investigated system, the Taylor expansion formula is adopted to linearize the discretized equation. Based on the method of augmented vector, an augmented state equation is established by state equations, unknown parameter equations, and fractional-order equation to achieve the state estimation. Besides, the sigmoid function is brought to ensure that the estimation of the fractional-order is performed in a suitable range. Because the covariance matrices of noises are difficult to be measured in physical systems, we also concern the problems on the state estimation, parameter estimation, and fractional-order estimation under the cases that the covariance matrix of process noise is unknown or the covariance matrix of measurement noise is unknown. Considering that the initial value can produce an error of state estimation and parameter identification for the FOS defined under the Caputo sense, the augmented vector method is used to achieve the initial value compensation. Finally, the effectiveness of the proposed algorithms is validated by four examples.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-12T09:47:40Z
      DOI: 10.1177/01423312221086070
       
  • On real-time creep damage prediction for steam turbine

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      Authors: Yongjian Sun, Bo Xu
      First page: 2603
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      In this paper, in order to solve the calculation problem of creep damage of steam turbine rotor, a real-time calculation method based on finite element model is proposed. The temperature field and stress field of the turbine rotor are calculated using finite element analysis software. The temperature data and stress data of the crucial positions are extracted. The data of temperature, pressure, rotational speed, and stress relating to creep damage calculation are normalized. A real-time creep stress calculation model is established by multiple regression method. After that, the relation between stress and damage function is analyzed and fitted, and creep damage is calculated in real-time. A creep damage real-time calculation system is constructed for practical turbine engineering. Finally, a numerical simulation experiment is designed and carried out to verify the effectiveness of this novel approach. Contributions of present work are that a practical solution for real-time creep damage prediction of steam turbine is supplied. It relates the real-time creep damage prediction to process parameters of steam turbine, and it bridges the gap between the theoretical research works and practical engineering.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-01-17T06:24:25Z
      DOI: 10.1177/01423312211068949
       
  • Self-referenced nanometric displacement sensing assisted by optical
           anapole mode

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      Authors: Jingzhi Wu, Hengze Yang, Yanhong Wang, Mengwei Li
      First page: 2611
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Long range optical rulers measuring distance greater than 10 nm have important applications in monitoring biological processes, nanolithography, and nanometrology. In this work, we show that lateral displacement over 120 nm can be determined by measuring two reflection peaks of the proposed nanostructure. The optical anapole in the nanostructure is excited, resulting from interactions of plasmonic resonance modes of nanoholes perforated in metal films and an array of nanoblocks. Results show that a 120 nm relative displacement between the nanoblocks and nanoholes induces a negative correlated 90% variation of reflection spectrum which can be used for self-referenced measurement. The proposed design could find applications in nanometrology, biosensing, and nanofabrication.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-01-22T06:44:45Z
      DOI: 10.1177/01423312211069742
       
  • Robust gain-scheduled output feedback [math] controller synthesis with
           reduced conservativeness: An application to EMS system

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      Authors: Reza Yavari, Arash Sadeghzadeh, Saeed Shamaghdari
      First page: 2616
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      This article investigates the design problem of gain-scheduled output feedback (GSOF) [math] controller exploiting uncertain scheduling parameters for continuous-time linear parameter-varying (LPV) systems. The problem of coexistence of absolute and proportional uncertainties on the scheduling parameters is considered to address more practical situations. This challenging issue has been tackled by introducing a novel admissible region for the actual and measured scheduling parameters. Furthermore, all the system matrices of the LPV system are assumed to be polynomially dependent on the scheduling parameters with arbitrary degrees. Both Lyapunov and auxiliary matrices are considered to be parameter-dependent. The merit of the proposed method lies in its less conservativeness in comparison with the available approaches. The design method is presented in terms of solutions to a set of parameter-dependent linear matrix inequalities (LMIs) including parameter searches for two scalar values. The application of the provided method on an electromagnetic suspension (EMS) system is considered to demonstrate the applicability and benefits of the proposed approach for practical systems.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-02-23T12:37:27Z
      DOI: 10.1177/01423312221078427
       
  • Analysis of fractional-order dynamics of dengue infection with non-linear
           incidence functions

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      Authors: Rashid Jan, Salah Boulaaras
      First page: 2630
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      The infection of dengue is a devastating mosquito-borne infection around the globe that affects human health, social and economic sectors in low-income areas. Therefore, policymakers and health experts are trying to point out better policies to reduce these losses and provide better information for the development of vaccination and medication. Here, we formulated a compartmental model for the transmission phenomena of dengue fever with nonlinear forces of infection through fractional derivative. We established several results related to the solution of our dengue model by using the basic properties of fractional calculus. We determined the basic reproduction number of our fractional-order system, symbolized by [math]. We established the local asymptotic stability of the infection-free equilibrium of our dengue system for [math], and proved that the infection-free equilibrium is globally asymptotically stable without vaccination. The threshold dynamics [math] is tested through partial rank correlation coefficient method to notice the importance of parameters in the transmission of dengue infection. In addition, we have shown the impact of memory on the basic reproduction number numerically with the variation of different parameters. We conclude that the biting rate, recruitment rate of mosquitoes and index of memory are the most sensitive factors, which can effectively lower the level of dengue fever. The dynamical behavior of the proposed fractional system is presented through a numerical scheme to explore the overall transmission process. We predict that the fractional-order model can explore more accurately and preciously the intricate dengue disease transmission model rather than the integer-order derivative.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-03T09:44:26Z
      DOI: 10.1177/01423312221085049
       
  • An anomaly detection algorithm of rolling bearing combining random matrix
           eigenvalues and principal eigenvectors

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      Authors: Heng Wang, Wenchang Zhu, Wenyuan Zhang, Guangxian Ni, Yupeng Cao
      First page: 2642
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      An anomaly detection algorithm combining eigenvalues and eigenvectors in random matrix is proposed, which can solve the problem that present algorithms based on random matrix theory overly rely on eigenvalues and ignore useful information contained in eigenvectors. Firtsly, the time window method is used to select the original data of rolling bearing, and the sampling feature matrix is constructed by extracting bearing feature. Secondly, the eigenvalues and principal eigenvector of sampling feature matrix are investigated and combined to construct comprehensive feature index and its corresponding threshold. Finally, an anomaly detection based on comprehensive feature index is proposed to detect the early anomaly of rolling bearing. The application research is carried out by using bearing datasets of intelligent maintenance center and Xi’an Jiaotong University; the result shows that compared with the single eigenvalue index and kurtosis index, the algorithm based on the comprehensive feature index can detect the abnormal condition of bearing earlier. And the accuracy and effectiveness of the anomaly detection algorithm are proved through spectrum analysis, which provides guidance and basis for fault warning and equipment maintenance.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-15T07:08:42Z
      DOI: 10.1177/01423312221088390
       
  • Detection of operating mode changes, without a priori model and in
           uncertain environments

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      Authors: José Ragot
      First page: 2653
      Abstract: Transactions of the Institute of Measurement and Control, Ahead of Print.
      Starting from the general observation that a measurement delivered by a sensor is subject to an uncertainty, its use in a decision chain must take into account this imprecise character. It is thus advisable to propagate this imprecision in all the chain of treatment and use of the measurement in question. In what follows, this principle is applied to the diagnostic function, one of the components of system monitoring. More precisely, we propose to analyze the temporal data collected on a system in order to detect and locate possible changes in the behavior of this system.
      Citation: Transactions of the Institute of Measurement and Control
      PubDate: 2022-04-27T11:55:15Z
      DOI: 10.1177/01423312221092527
       
 
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