Reference model iterative learning control for linear systems

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.