Adaptive Iterative Learning Control for Nonlinear Systems with Time-Iteration-Varying Parametric Uncertainties and Nonparametric Uncertainties

Abstract

This work studies the adaptive iterative learning control algorithm for nonlinear systems with nonparametric uncer-tainty and time-iteration-varying parametric uncertainty generated from a high-order internal model(HOIM) under nonzero initial errors condition. We apply time-varying boundary layer technique to deal with the initial position problem of ILC, adopt robust learning control approach to compensate nonparametric uncertainty, and take advantage of adaptive learning strategy to handle the time-iteration-varying parametric uncertainty generated from HOIM. Lyapunov synthesis is adopted for design the iterative learning controller and analyzing control performance. As the iteration number increases, the filtering error can converge to a tunable residual set. In the end, numerical simulation is given to show the effectiveness of propose adaptive learning control algorithm.