Iterative learning control-recent progress and open research problems

The emergence of intelligent control has seen a focus of attention on the ideas of learning control. This paper introduces the current state of the art in the area of iterative learning control (ILC). Together with a general description of the problems that must be addressed, the paper explores the relationship between the performance of learning algorithms and the structure of the system to be controlled. The importance of system's relative degree (pole-zero excess) and the system's zeros are described and the role of prediction in improving performance is stated.