Abstract:

A non-causal robust iterative learning control method for uncertain systems is presented. Feedback controller and iterative learning controller are designed independently, and robust analysis is then implemented together in order to ensure the feedback and learning performance of the system. Firstly, an  H_∞ controller is designed to guarantee the robust stability of the feedback part. Secondly, learning efficiency is improved by using a quadratic optimized iterative learning control law. Finally, the robustness of the iterative learning control system is verified by μ-analysis, and the design parameters of the optimal iterative learning control law are modified then. The proposed method not only takes the advantage of good learning performance of the non-causal iterative learning control law, but also utilizes the property of small conservation of μ-analysis to improve the performance. An example is given to testify the effectiveness of the proposed method.