Non-linear iterative learning by an adaptive Lyapunov technique

Abstract

We consider the iterative learning control problem from an adaptive control viewpoint. It is shown that some standard Lyapunov adaptive designs can be modified in a straightforward manner to give a solution to either the feedback or feedforward ILC problem. Some of the common assumptions of non-linear iterative learning control are relaxed: e.g. we relax the common linear growth asssumption on the non-linearities and handle systems of arbitrary relative degree. It is shown that generally a linear rate of convergence of the MSE can be achieved, and a simple robustness analysis is given. For linear plants we show that a linear rate of MSE convergence can be achieved for non-minimum phase plants.