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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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

Received: 07 May 2021

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TM351

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	Wei Huifang
	Wang Limei

Cite this article:

Wei Huifang,Wang Limei. Adaptive Fuzzy Neural Network Time-Varying Sliding Mode Control for Permanent Magnet Linear Synchronous Motor[J]. Transactions of China Electrotechnical Society, 2022, 37(4): 861-869.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.210641 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I4/861

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