基于Smith预估和性能加权函数的永磁直线同步电机鲁棒迭代学习控制

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Abstract In the process of iterative learning control(ILC) for permanent magnet linear synchronous motors(PMLSM),due to the disturbances and time delay,the system might be unstable,the error is difficult to converge,and the tracking precision is reduced.A robust ILC scheme based on the Smith predictor and the performance weighting function is proposed.In the case that the precise mathematical model of PMLSM is unwanted,the combination of the Smith predictor and ILC decreases the influence of time delay on the system tracking performance.Then it can avoid the instability of the system in the iterative process caused by the accumulation of time delay.Due to these uncertain factors of the external disturbance,parameters change,and end effect etc.,the scheme makes full use of the information of the performance weighting function to design the feedback controller.In the case of fulfilling robust convergence condition,it can make the position error converge to the desired value.The experimental results indicate that the proposed control scheme improves the position tracking accuracy of the PMLSM servo system and enhances the robustness of the system.

Key words： Permanent magnet linear synchronous motor iterative learning control performance weighting function time delay

Received: 25 May 2015 Published: 02 November 2016

PACS:

TM359

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	Zhao Ximei
	Ma Zhijun
	Zhu Guoxin

Cite this article:

Zhao Ximei,Ma Zhijun,Zhu Guoxin. Robust Iterative Learning Control for PMLSM Based on Smith Predictor and Performance Weighting Function[J]. Transactions of China Electrotechnical Society, 2016, 31(19): 141-146.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I19/141

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