永磁直线同步电机伺服系统的分段变论域模糊迭代学习控制

doi:10.19595/j.cnki.1000-6753.tces.161449

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Abstract For permanent magnet linear synchronous motor (PMLSM)to perform repetitive tasks, in the process of iterative learning, it is vulnerable to the influence of the nonrepetitive disturbances such as the load disturbances, parameter variation and so on. It is difficult to achieve high performance tracking control. The segmented variable universe fuzzy iterative learning control (ILC) is proposedwhich combines ILC with variable universe fuzzy control.In the period of larger error, the variable universe fuzzy control is used to change the learning gain of ILC in real time, and intelligently adjust the domain of fuzzy control, in order to restrain the influence of uncertain factors on the system and improve the control precision. In the period of smaller error, PD type ILC is used to make the learning gain stable and the position error can be reduced further. The experimental results show that the control method can effectively speed up the convergence rate, improve the position tracking accuracy, and enhance the robustness of the system.

Key words： Permanent magnet linear synchronous motor iterative learning control segmented variable universe fuzzy control tracking accuracy

Received: 09 September 2016 Published: 22 December 2017

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TM315

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	ZhaoXimei
	Jin Hongyan

Cite this article:

ZhaoXimei,Jin Hongyan. Segmented Variable Universe Fuzzy Iterative Learning Control for Permanent Magnet Linear Synchronous Motor Servo System[J]. Transactions of China Electrotechnical Society, 2017, 32(23): 9-15.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.161449 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I23/9

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