Convex optimization based iterative learning control for iteration-varying systems under output constraints

In this work, we discuss a class of linear iterative learning control (ILC) systems which are iteration-varying with system output constraints. It can be shown that the objective of ensuring convergence of system output tracking error and satisfying system output constraints can be converted to a convex optimization problem, in which the objective function is quadratic and the constraints are convex. Under the proposed algorithm, tracking error convergence can be guaranteed over the iteration domain. A simulation study based on a wafer stage system is presented to demonstrate the efficacy of our approach.