Robust fault-tolerant iterative learning control for discrete systems via linear repetitive processes theory

Abstract

This paper addresses the problem of robust iterative learning control design for a class of uncertain multiple-input multiple-output discrete linear systems with actuator faults. The stability theory for linear repetitive processes is used to develop formulas for gain matrices design, together with convergent conditions in terms of linear matrix inequalities. An extension to deal with model uncertainty of the polytopic or norm bounded form is also developed and an illustrative example is given.