Tracking Control Strategy of PMSLM with A Novel Observer-based Compensator and A RBFNN-based Controller

Zhentian Liu, Guangsen Wang, Zhiwei Wang
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引用次数: 3

Abstract

This paper is devoted to a high-precision tracking control strategy of permanent magnet synchronous linear motor (PMSLM). Firstly, the field-oriented control model of the PMSLM is established to calculate the electromagnetic thrust. To reconstruct the system states and reject the lump disturbance, a novel observer-based compensator is proposed, by taking the basic ideas of the frequency-domain disturbance observer and the time-domain one (the extended state observer in active disturbance rejection control, ADRC). A radial-basis-function neural network (RBFNN) controller with accurate approximation capability is utilized to tracking the desired motion trajectory. Contrasted to the RBFNN’s parameters self-evolved, a simple and unique parameters tuning method is derived to guarantee the compensator performance. All the proposed algorithms are implemented in a rapid control prototype (RCP) real-time simulation platform and the simulation and experiment results validate the rightness of theoretical analysis and the feasibility of the proposed methods.
基于观测器补偿器和rbfnn控制器的PMSLM跟踪控制策略
研究了永磁同步直线电机的高精度跟踪控制策略。首先,建立了PMSLM的磁场定向控制模型,计算了电磁推力;为了重构系统状态并抑制块扰动,利用频域扰动观测器和时域扰动观测器(自抗扰控制中的扩展状态观测器)的基本思想,提出了一种基于观测器的补偿器。利用具有精确逼近能力的径向基函数神经网络(RBFNN)控制器对目标运动轨迹进行跟踪。对比RBFNN参数自进化的特点,提出了一种简单、独特的参数整定方法来保证补偿器的性能。在快速控制原型(RCP)实时仿真平台上实现了所提算法,仿真和实验结果验证了理论分析的正确性和所提方法的可行性。
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