Global adaptive sliding mode control for PMLSM based on third-order super-twisting disturbance observer

被引:0
作者
Zhang, Yan [1 ]
Wang, Limei [1 ]
Fang, Xin [1 ]
机构
[1] School of Electric and Engineering, Shenyang University of Technology, Shenyang
来源
Dianji yu Kongzhi Xuebao/Electric Machines and Control | 2024年 / 28卷 / 06期
关键词
adaptive reaching law; anti-interference; chattering; disturbance observer; global sliding mode control; permanent magnet linear synchronous motor; tracking accuracy;
D O I
10.15938/j.emc.2024.06.008
中图分类号
学科分类号
摘要
Aiming at the problem that the position tracking accuracy of permanent magnet linear synchronous motor is easily affected by uncertain factors such as external disturbance and parameter change, a compound control strategy combining global adaptive sliding mode controller and three-order super-twisting disturbance observer was proposed. Firstly, in order to solve the chattering problem of global sliding mode control, the global adaptive sliding mode controller was designed according to the adaptive reaching law. The adaptive approach law can adjust the switching gain in real time according to the changing process of the system state variables, so as to improve the response speed of the system and reduce chattering. Then, in order to improve the tracking accuracy and anti-interference ability of the system, a three-order super-twisting disturbance observer was designed to observe the disturbance and uncertainty that cannot be accurately measured in the system and realize the feedforward compensation of the system. Finally, simulation and experimental verification were carried out. The simulation and experimental results show that compared with global sliding mode control, the proposed method can effectively improve the response speed and tracking accuracy of the system, and make the system have good steady-state and dynamic performance. © 2024 Editorial Department of Electric Machines and Control. All rights reserved.
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页码:76 / 86
页数:10
相关论文
共 25 条
[1]  
WANG Lijun, ZHAO Jiwen, DONG Fei, High-bandwidth and strong robust predictive current control strategy research for permanent magnet synchronous linear motor based on adaptive internal model observer [ J ], Proceedings of the CSEE, 39, 10, (2019)
[2]  
ZHAO Xinyu, WANG Limei, Adaptive fractional-order terminal sliding mode control for permanent magnet linear synchronous motor, Transactions of China Electrotechnical Society, 38, 20, (2023)
[3]  
CAO Rongmin, ZHENG Xinxin, HOU Zhongsheng, Aniterative learning control based on improved multiple input and multiple output model free adaptive control for two-dimensional linear motor [J], Transactions of China Electrotechnical Society, 36, 19, (2021)
[4]  
ZHU Jinquan, GE Qiongxuan, ZHANG Bo, Traction control strategy of high-speed maglev considering the influence of suspension System, Transactions of China Electrotechnical Society, 37, 12, (2022)
[5]  
JIN Hongyan, ZHAO Ximei, WANG Tianhe, Adaptive backstepping complementary sliding mode control based on disturbance observer for permanent magnet linear synchronous motor[ J], Proceedings of the CSEE, 42, 6, (2022)
[6]  
FU Dongxue, ZHAO Ximei, Backstepping terminal sliding mode control based on radial basis function neural network for permanent magnet linear synchronous motor, Transactions of China Electrotechnical Society, 35, 12, (2020)
[7]  
(2019)
[8]  
ZHANG Yanqing, YIN Zhonggang, ZHANG Yanping, Et al., A novel sliding mode observer with optimized constant rate reaching law for sensorless control of induction motor[J], IEEE Transactions on Industrial Electronics, 67, 7, (2020)
[9]  
ZHANG Dongdong, ZHANG Hanquan, LI Xiang, Et al., A PMSM control system for electric vehicle using improved exponential reaching law and proportional resonance theory, IEEE Transactions on Vehicular Technology, 72, 7, (2023)
[10]  
WANG Hai, SHI Liheng, MAN Zhihong, Et al., Continuous fast nonsingular terminal sliding mode control of automotive electronic throttle systems using finite-time exact observer, IEEE Transactions on Industrial Electronics, 65, 9, (2018)