Closed-loop iterative learning control for non-linear systems with initial shifts

This paper is concerned with the problem of the iterative learning control with current cycle feedback for a class of non-linear systems with well-defined relative degree. The tracking error caused by a non-zero initial shift is detected as extended D-type learning algorithm is applied. The defect is overcome by adding terms including the output error, its derivatives as well as integrals. Asymptotic tracking of the final output to the desired trajectory is guaranteed. As an alternative approach, an initial rectifying action is introduced in the extended D-type learning algorithm and shown effective to achieve the desired trajectory jointed smoothly with a transitional trajectory from the starting position. Also these algorithms with adjustable tracking interval ensure better robustness performance in the presence of initial shifts. Numerical simulation is conducted to demonstrate the theoretical results. Copyright # 2002 John Wiley & Sons, Ltd.