Iterative learning control (ILC) in manufacturing systems: Design of ILC algorithms and overview of model inversion techniques for ILC synthesis

Abstract

This paper presents a comprehensive overview of Iterative Learning Control (ILC) and its application in manufacturing systems, focusing on the design of ILC algorithms and the use of model inversion techniques for ILC synthesis. General principles of the standard approach to ILC algorithm design are discussed, and various model inversion techniques are compared. The analysis is supported by an illustrative example involving a general mechatronic subsystem, demonstrating the advantages of ILC over conventional control methods. The results highlight the potential of ILC to significantly enhance the performance of manufacturing systems.