Article
Engineering, Electrical & Electronic
Xinghong Li, Siwei Cheng, Dong Wang, Zhongkun Ji, Yunfei Hu, Yajun Lv
Summary: This article presents a simple and nonintrusive method to identify and compensate for current measurement errors in interior permanent magnet synchronous motor (IPNISM) drives. The method utilizes the distinct steady-state short-circuit current characteristic of each IPMSM and compares the measured currents with the true short-circuit characteristic to correct for current sensor errors.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2022)
Article
Engineering, Electrical & Electronic
Cong Bai, Zhonggang Yin, Yanping Zhang, Jing Liu
Summary: A composite robust current regulation method with good dynamic response and disturbance rejection performance is proposed in this paper to achieve high-performance control of the precise LPMSM control system. It combines continuous time model predictive current control with adaptive disturbance observer to improve system performance.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Automation & Control Systems
Mohammad Moradi Ghahderijani, Behzad Mirzaeian Dehkordi
Summary: This article introduces a new control scheme for Z-source inverter-based permanent magnet synchronous motor drive systems to enhance system robustness and performance. Experimental validation shows that the enhanced configuration excels in reducing torque ripple and settling time.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Review
Engineering, Electrical & Electronic
Anton Dianov, Fabio Tinazzi, Sandro Calligaro, Silverio Bolognani
Summary: This article discusses the MTPA control of synchronous motors, explaining the nature of torque produced by these motors and presenting algorithms for operating at the maximum torque point. The authors classify the MTPA methods based on their features and discuss the modifications required for implementation. They review existing control algorithms, analyze their pros and cons, and provide insights into their potential applications.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Automation & Control Systems
Yupeng Wang, Lin Zhao
Summary: This article investigates the position tracking control problem of permanent magnet synchronous motors (PMSMs) with mismatched disturbances based on adaptive fuzzy gain-varying finite-time command filtered backstepping method. The anti-disturbance ability of the system is improved by constructing gain-varying functions and utilizing command filters. The finite-time control technique and fuzzy logic systems are used to handle the coupling and approximate nonlinear functions of the PMSMs systems.
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
(2023)
Article
Automation & Control Systems
Yanchun Bai, Jian Hu, Jianyong Yao
Summary: This paper focuses on the high-performance tracking control of electromechanical servo systems. A novel neural network state observer is designed to observe the unknown states. The proposed observer has higher observation accuracy and better robustness compared to existing neural network observers. Additionally, a fixed-weight single-node neural network is added to effectively improve the approximation ability of the double-layer neural network.
Article
Computer Science, Information Systems
Hao Yan, Weiduo Zhao, Giampaolo Buticchi, Chris Gerada
Summary: The paper proposes an Active Thermal Control method for improving the lifetime of Permanent Magnet Synchronous Motors (PMSMs) drive system, and uses power routing and Rainflow Counting Algorithm to estimate the lifetime of power converters. The effectiveness of the proposed method is validated through simulation and experiments.
Article
Automation & Control Systems
Majid Moradi Zirkohi
Summary: In this paper, an efficient adaptive control approach is proposed for chaotic PMSMs by using command filtering, Bessel series approximation, and a reduced-order observer to improve control system performance. The asymmetric Lyapunov functions are employed to guarantee the restriction of state variables, and the control design successfully suppresses chaotic behavior while maintaining excellent tracking performance.
Article
Automation & Control Systems
Qianwen Duan, Wei Tian, Qifan Yang, Xiaonan Gao, Yao Mao, Petros Karamanakos, Ralph Kennel, Marcelo Lobo Heldwein
Summary: This article presents two computationally efficient methods for selecting the optimal modulated voltage that can achieve superior dynamic performance for surface-mounted permanent magnet synchronous motors (SPMSMs). The first method is a simple overmodulation method based on common-mode-saturation injection (CMSI), which has very low computational cost and can easily find the voltage vector on the boundary. The second method is a quadratic program (QP) based deadbeat (DB) control, which formulates the control problem as a constrained QP and solves it with an efficient solver based on an active-set method. Simulative and experimental investigations are conducted to demonstrate the effectiveness of both methods for an SPMSM.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Qi Jiang, Jiapeng Liu, Jinpeng Yu, Chong Lin
Summary: An adaptive fuzzy control scheme based on command filtering is proposed for the position tracking control of PMSM stochastic system with full state constraints. Fuzzy logic systems are employed to approximate unknown stochastic nonlinear functions, while barrier Lyapunov functions are constructed to ensure that all states of the system do not violate its constrained boundary. The scheme solves the problem of complexity in traditional design and introduces error compensation mechanism to reduce filtering errors.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Yanlei Yu, Yulong Pei, Feng Chai, Martin Doppelbauer
Summary: This article compares the performance of permanent magnet synchronous motor (PMSM) and permanent magnet Vernier motor (PMVM) for in-wheel direct drive, including air-gap magnetic field harmonic, electromagnetic torque, power factor, etc. The strengths and weaknesses of these two types of motors for in-wheel drive are analyzed, and future prospects are suggested.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Vahid Zamani Faradonbeh, Akbar Rahideh
Summary: A fast hybrid analytical model is proposed to predict the on-load performance of double-layer IPMSMs considering iron bridges saturation and slotting effects. The model utilizes constant flux in the magnetic equivalent circuit method for iron bridges saturation and flux path function and VSCs for slotting effects in 1-D and 2-D analytical methods.
IET ELECTRIC POWER APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Piotr Gnacinski, Adam Muc, Marcin Peplinski
Summary: Research found that voltage containing subharmonics has an extraordinarily harmful influence on LSPMSM motors, causing unacceptable vibration.
Article
Computer Science, Information Systems
Chan Hee Park, Junmin Lee, Hyeongmin Kim, Chaehyun Suh, Myeongbaek Youn, Yongjin Shin, Sung-Hoon Ahn, Byeng D. Youn
Summary: This paper proposes a novel method using stator current signals to detect motor faults under varying speed and load torque conditions, without the need for domain knowledge. The method calculates a drive-tolerant current residual variance as a new health feature, showing the ability to promptly and accurately detect faults in various conditions. Experimental studies confirm the effectiveness of the proposed method compared to conventional methods, which are greatly influenced by operating conditions.
Review
Computer Science, Information Systems
Paolo Mercorelli
Summary: This paper aims to review literature on tracking problems in the control of permanent magnet synchronous motors, including their control and functionality, such as fault detection and performance evaluation. Permanent magnet synchronous motors are widely used in various motion control systems, known for their high efficiency, high power density, excellent dynamic performance, and limited power ripple.
Article
Computer Science, Artificial Intelligence
Lili Zhang, Bing Chen, Chong Lin, Yun Shang
Summary: This article discusses the consensus tracking issue for multiagent systems and proposes a fixed-time consensus proposal by fuzzy adaptive method. The suggested fuzzy adaptive control protocol ensures bounded closed-loop signals for each agent and convergence of consensus tracking error to a small region around the origin in fixed time. The virtual control signals are constructed as piecewise functions to avoid singularity of their derivatives, and numerical simulation validates the effectiveness of the suggested control strategy.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Shuhui Sun, Zhijian Ji, Chong Lin, Yungang Liu
Summary: This paper discusses the structural controllability of leader-follower systems over digraphs. By analyzing the topological characteristics, it provides a sufficient condition for ensuring structural controllability and explores the effects of topologies on strong (or weak) structural controllability.
IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION
(2022)
Article
Automation & Control Systems
Lei Tian, Zhijian Ji, Yungang Liu, Chong Lin
Summary: This paper investigates the influences of negative weights on the consensus problems of multi-agent systems and provides a unified approach to deal with the consensus problem when the connection weight becomes negative.
SYSTEMS & CONTROL LETTERS
(2022)
Article
Mathematics, Applied
Xiuwen Fu, Zhaoliang Sheng, Chong Lin, Bing Chen
Summary: This work investigates the admissibility and dissipativity of descriptor systems with state delay. A novel asymmetric Lyapunov-Krasovskii functional is constructed to obtain delay-dependent conditions. New criteria for admissibility and dissipativity are proposed based on strict linear matrix inequalities. The main advantage of this method is reducing conservatism by removing the positive definiteness requirement of some symmetric matrices. Three numerical examples are provided to verify the effectiveness of the results.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Physics, Multidisciplinary
Zhuang Yao, Ziye Zhang, Zhen Wang, Chong Lin, Jian Chen
Summary: This paper investigates the polynomial synchronization problem of complex-valued inertial neural networks with multi-proportional delays. It analyzes the problem using the non-separation method. Firstly, an exponential transformation is applied and an appropriate controller is designed. Then, a new sufficient criterion for polynomial synchronization is derived using the Lyapunov function approach and inequalities techniques. A numerical example is provided to illustrate the effectiveness of the obtained result.
COMMUNICATIONS IN THEORETICAL PHYSICS
(2022)
Article
Automation & Control Systems
Xu Yuan, Bing Chen, Chong Lin
Summary: A new and efficient output-feedback adaptive backstepping control strategy is developed to achieve finite-time output tracking control for nonlinear output-constrained systems. The strategy constructs an asymmetric barrier Lyapunov function based on performance functions and error variable for finite-time tracking control. A fuzzy state observer is set up to reconstruct the unknown system states, and an observer-based fuzzy adaptive output-feedback controller is presented. The proposed control strategy ensures that the output tracking error meets the preassigned precision level within a given time period, while the output variable complies with time-varying restrictions and other closed-loop signals are bounded. Numerical simulation research with two examples validates the feasibility and availability of the developed control strategy.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Xu Yuan, Bing Chen, Chong Lin
Summary: This article presents a novel backstepping-based adaptive neural tracking control design procedure for nonlinear systems with time-varying state constraints. The designed controller ensures that the output tracking error converges to a small neighborhood of the origin with the prescribed finite time and accuracy level. The proposed control scheme is further validated through simulation examples.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Mathematics, Applied
Peng Su, Zhaoliang Sheng, Chong Lin, Bing Chen
Summary: This paper investigates the stochastic admissibility of time-delay singular Markovian jump systems (SMJSs) and proposes a new Lyapunov-Krasovskii functional (LKF) to obtain new sufficient conditions for ensuring stochastic admissibility. The proposed method reduces conservativeness by removing the positive definite constraint of some matrix variables. A numerical example is provided to verify the less conservativeness of the proposed approach.
APPLIED MATHEMATICS LETTERS
(2023)
Article
Automation & Control Systems
Yusheng Jia, Chong Lin, Bing Chen
Summary: In this work, the finite-time stability for singular time-delay systems is studied. The effects of the exponential weighted function e eta(t-s) are analyzed, and a new weighted integral inequality in the form of infinite series is derived for solving finite-time stability problems. Based on that, sufficient conditions are obtained to guarantee the finite-time stability of the underlying system. A numerical example is provided to demonstrate the efficiency of the methods.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Xu Yuan, Bing Chen, Chong Lin
Summary: This article addresses the issue of adaptive neural tracking control for state-constrained systems with a novel approach that ensures system states do not violate their constraints and tracking errors converge. The proposed fixed-time stability criterion and adaptive neural control algorithm contribute to this successful outcome, as supported by simulation examples.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Jinpeng Yu, Shuai Cheng, Peng Shi, Chong Lin
Summary: This article proposes an adaptive neural-network command-filtered output-feedback control strategy for stochastic nonlinear systems with actuator constraints. The problem of "explosion of complexity" in conventional backstepping design is successfully solved using the command filter technique, and an error compensation mechanism is introduced to effectively remove the influence of filtered error. A neural network-based state observer is designed to estimate the unmeasurable states of the system by identifying the unknown nonlinear functions using neural networks. The stability of the stochastic closed-loop systems is analyzed using a quartic Lyapunov function. It is proven that all signals of the closed-loop systems are bounded in probability, and the tracking error approaches a small neighborhood of the origin in probability. The effectiveness of the developed control algorithm is verified through a comparison example.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Lili Zhang, Wei-Wei Che, Bing Chen, Chong Lin
Summary: This article presents a solution to the finite-time consensus tracking control problem for nonlinear multiagent systems with unmeasured state variables and unknown nonlinear functions. By designing an observer to estimate the state variables and employing fuzzy logic systems to approximate nonlinearities, an observer-based adaptive fuzzy consensus tracking controller is developed. The control protocol guarantees bounded signals in the closed-loop system and convergence of the consensus tracking error to a prespecified region within a finite time. Compared to existing control protocols, the settling time and convergence region can be predetermined by the designer and are not affected by unknown constants.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Letter
Automation & Control Systems
Zhaoliang Sheng, Chong Lin, Shengyuan Xu
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2023)
Article
Automation & Control Systems
Mengmeng Su, Zhijian Ji, Yungang Liu, Chong Lin
Summary: In this paper, the controllability of multi-agent systems is studied using equitable partition and automorphism. Necessary conditions for controllability are presented from the perspective of the rank of connection matrix when cells are incompletely connected outside but completely connected inside. Sufficient and necessary conditions for controllability are given based on the eigenvalues and eigenvectors of L and L & pi; when multiple cells are completely connected outside and incompletely connected inside. The paper also explores the gap between the necessary condition and the sufficient condition for controllability from the aspect of equitable partition.
Article
Automation & Control Systems
Huihui Yu, Jinpeng Yu, Qing-Guo Wang, Chong Lin
Summary: This article investigates the problem of adaptive neural network finite-time command-filtered tracking control for a certain class of nonlinear systems with time-varying full-state constraints. The issue of time-varying full-state constraints is resolved using asymmetric time-varying barrier Lyapunov functions. The adaptive neural network control method eliminates the influence of unknown items in the system. Additionally, an improved finite-time command filter is introduced to relax the restrictions on the input signal and solve the explosion of complexity problem. Meanwhile, a finite-time error compensation mechanism is developed to eliminate the influence of filtering error. It is demonstrated that the proposed strategy guarantees the boundedness and convergence of signals in the closed-loop system, and the effectiveness of the control method is verified through an example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
