An Iterative Learning Control Based on Improved Multiple Input and Multiple Output Model Free Adaptive Control for Two-Dimensional Linear Motor
Cao Rongmin1, Zheng Xinxin1, Hou Zhongsheng2
1. School of Automation Beijing Information Science and Technology University Beijing 100192 China; 2. School of Automation Qingdao University Qingdao 266071 China
Abstract In actual operation for two-dimensional linear motor, there are some unmodeled dynamic control problems, such as strong coupling, unknown nonlinearity, and easy to be affected by exogenous disturbances. Based on the fact that the model free adaptive control (MFAC) does not depend on the system precise mathematical model and iterative learning control (ILC) is a progressive learning rule, an improved model free adaptive control with multiple input and multiple output (MIMO)-MFAC iterative learning control (ILC) compound scheme was proposed for two-dimensional linear motor. The first order difference element was added to the input criterion function of MFAC, which makes the improved MIMO-MFAC feedback controller have strong robustness. The ILC feedforward controller can reject exogenous disturbances and compensate system nonlinearity, feedforward and feedback are complementary to each other to achieve the accuracy compensation for the desired output, and further reduce the position tracking error. Finally, the two-dimensional linear motor motion platform is combined with LINKS-RT hardware in the loop simulation system, the effectiveness of the proposed scheme is proved by practical experiments.
Cao Rongmin,Zheng Xinxin,Hou Zhongsheng. An Iterative Learning Control Based on Improved Multiple Input and Multiple Output Model Free Adaptive Control for Two-Dimensional Linear Motor[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4025-4034.
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2021, Vol. 36 
