Sensorless Vector Control of Permanent Magnet Synchronous Linear Motor Based on Self-Adaptive Super-Twisting Sliding Mode Controller

控制理论(社会学) 直线电机 计算机科学 国家观察员 滑模控制 控制器(灌溉) 反电动势 同步电动机 病媒控制 观察员(物理) 运动控制 工程类 感应电动机 电压 物理 非线性系统 机器人 电气工程 控制(管理) 人工智能 生物 机械工程 量子力学 农学
作者
Zheng Li,Shuo Zhou,Yu Xiao,Wang Leiyong
出处
期刊:IEEE Access [Institute of Electrical and Electronics Engineers]
卷期号:7: 44998-45011 被引量:107
标识
DOI:10.1109/access.2019.2909308
摘要

Due to its own structural characteristics, permanent magnet synchronous linear motors (PMSLMs) have unstable motor parameters during operation due to the end effect and the inherent magnetic circuit instability. At the same time, linear motors have the characteristics of reciprocating switching motion and high-speed positioning motion in industrial applications, thus placing high demands on the controller. In order to improve the performance of the PMSLM, this paper firstly studies the linear motor structure, the distribution characteristics of its air gap magnetic field are obtained, and the simulation analysis for the back electromotive force (EMF) of PMSLM of its running process is carried out. Then, a state observer based on the sliding mode state observer (SMO) is built to replace the traditional speed sensor and a super-twisting sliding mode controller is designed. The double-closed loop control of the speed and the use of high-order sliding mode control features effectively reduce the chattering of the system and reduce the impact of the observation error brought by the observer on the system. The adaptive sliding mode control strategy is used to effectively suppress the influence of the boundaryless uncertainty interference on the system and reduce the influence of the observation error brought by the observer on the system. This paper also combines the linear motor experimental platform to further verify the control scheme based on the super-twisting sliding mode non-sensing linear motor. The simulation and experimental results show that SMO has accurate speed and position tracking performance, the system's chattering is significantly reduced, the control precision is excellent, and the introduction of adaptive sliding mode controller enhances the robustness of the system.
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