An Optimal Iterative Learning Control Design Framework for Systems with Varying Trial Lengths

Abstract

This paper proposes an iterative learning control (ILC) design framework for systems with varying trial lengths inspired by existent successive projection method. After reformulating the ILC problem into finding a point between two sets, the framework of successive projection is modified for systems with varying trial lengths in random sense. Therefore, the traditional norm optimal ILC can be employed to solve problems with varying trial lengths, whose convergence is thus proved in mathematical expectation sense. A numerical simulation model is employed to verify the effectiveness of the proposed ILC design.