Self-Tuning Iterative Learning Control for Time Variant Systems

Abstract

We consider the iterative learning control problem from an adaptive control viewpoint. The STILCS (self-tuning iterative learning control systems) problem is formulated in a general case, when the underlying repetitive linear process is time-variant and its parameters are all unknown, its initial conditions are not fixed and are not determinable in various iterations. A solution procedure is presented for this problem. The Lyapunov technique is employed to ensure the convergence of the presented STILCS. The computer simulation results are included to illustrate the effectiveness of the proposed STILCS.