Iterative learning control with Smith time delay compensator for batch processes

How to improve the control of batch processes is not an easy task because o f modeling errors and time delays. In this work, novel iterative learning c ontrol (ILC) strategies, which can fully use previous batch control informa tion and are attached to the existing control systems to improve tracking p erformance through repetition, are proposed for SISO processes which have u ncertainties in modeling and time delays. The dynamics of the process are r epresented by transfer function plus pure time delay. The stability propert ies of the proposed strategies for batch processes in the presence of uncer tainties in modeling and/or time delays are analyzed in the frequency domai n. Sufficient conditions guaranteeing convergence of tracking error are sta ted and proven. Simulation and experimental examples demonstrating these me thods are presented. (C) 2001 Elsevier Science Ltd. All rights reserved.