永磁直线同步电机自适应模糊神经网络时变滑模控制

doi:10.19595/j.cnki.1000-6753.tces.210641

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摘要

针对永磁直线同步电机（PMLSM）在跟踪不同参考轨迹运动时,易受参数变化、外部扰动以及摩擦力等不确定因素影响而降低伺服性能的问题,提出一种基于自适应模糊神经网络时变滑模控制器（AFNNTSMC）的精密位置跟踪方法。首先,在PMLSM数学模型的基础上,将时变滑模面引入到传统滑模控制器（SMC）中设计时变滑模控制器（TSMC）。通过调整时变滑模面的斜率,可以在保证鲁棒性的前提下,有效缩短系统状态到达滑动模态的时间,提高系统的响应速度。其次,由于TSMC中斜率值较难获得,因此将其与模糊神经网络相结合设计AFNNTSMC方法。通过采用Lyapounov函数设计自适应律,对时变滑模面的斜率值实时估计并在线调整,保证系统达到最佳伺服性能。最后,在参数变化和外部扰动两种实验条件下,验证所提方法的有效性。实验结果表明,AFNNTSMC可以有效提高系统的响应速度和位置跟踪精度,对不确定性因素具有较强的鲁棒性。

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	魏惠芳
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关键词 ：永磁直线同步电机, 时变滑模控制, 自适应模糊神经网络, 鲁棒性

Abstract：

Aiming at the problem that the servo performance of permanent magnet linear synchronous motor (PMLSM) tracking different reference trajectories is easily affected by parameter changes, external disturbances, friction and other uncertain factors, a precise position tracking method based on adaptive fuzzy neural network time-varying sliding mode controller (AFNNTSMC) is proposed. Firstly, based on the PMLSM mathematical model, the time-varying sliding mode controller (TSMC) is designed by introducing the time-varying sliding surface into the sliding mode controller (SMC). By adjusting the slope of the time-varying sliding surface, the time for the system state to reach the sliding mode can be effectively shortened and the response speed of the system can be improved on the premise of robustness. Besides, because the slope value of TSMC is difficult to obtain, it is combined with the fuzzy neural network to design the AFNNTSMC method. Using the Lyapunov function to design adaptive law, the slope value is estimated in real time and adjusted online to ensure the optimal servo performance of the system. Finally, the effectiveness of the proposed method is verified under two experimental conditions of parameter variation and external disturbance. The experimental results show that AFNNTSMC can effectively improve the response speed and position tracking accuracy of the system, and has strong robustness to uncertainties.

Key words： Permanent magnet linear synchronous motor time-varying sliding mode control adaptive fuzzy neural network robustness

收稿日期: 2021-05-07

PACS:

TM351

基金资助:

国家自然科学基金资助项目（51875366）。

通讯作者: 王丽梅女,1969年生,教授,博士生导师,研究方向为交流伺服驱动技术。E-mail: wanglm@sut.edu.cn

作者简介: 魏惠芳女,1986年生,博士研究生,讲师,研究方向为驱动控制与精密伺服技术。E-mail: weihuifang088@163.com

引用本文:

魏惠芳, 王丽梅. 永磁直线同步电机自适应模糊神经网络时变滑模控制[J]. 电工技术学报, 2022, 37(4): 861-869. Wei Huifang, Wang Limei. Adaptive Fuzzy Neural Network Time-Varying Sliding Mode Control for Permanent Magnet Linear Synchronous Motor. Transactions of China Electrotechnical Society, 2022, 37(4): 861-869.

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