Robust Iterative Learning Control Design: Application to a Robot Manipulator

Abstract

This paper deals with robust iterative learning control design for uncertain single-input-single-output linear time-invariant systems. The design procedure is based upon solving the robust performance condition using the Youla parameterization and the mu-synthesis approach to obtain a feedback controller. Thereafter, a convergent iterative learning law is obtained by using the performance weighting function involved in the robust performance condition. Experimental results, on a CRS465 robot manipulator, are provided to illustrate the effectiveness of the proposed design method.