Reference model iterative learning control for linear systems

Abstract

This paper presents an iterative learning control D-type for linear system to follow a reference model (also called desired system). This desired system doesn't have dependence with the model of the real system. In addition, the initial states of the two systems must not be necessarily equal. The λ -norm is adopted as the topological measure in our proof of the asymptotic stability of this control scheme, over the whole finite time-interval, when the iteration number tends to infinity. Simulation results are presented to illustrate the effectiveness of the proposed control scheme.