ILC for Discrete Linear Switched Systems with Varying Trial Lengths

This paper proposes an iterative learning control (ILC) method for discrete linear switched systems with varying trial lengths. By using the contraction mapping method with lambda-norm, the convergence of the proposed iteration-average operator based ILC law is theoretically analyzed. As the terminal time point of the output trajectory fluctuates around the switching time point, the ILC tracking errors of the discrete linear switched system can be driven to zero in mathematical expectation sense. Numerical simulations are presented to verify the effectiveness of the proposed ILC scheme.