Iterative Learning Control Based on Relaxed 2D Systems Stability Criteria

This paper develops significant new results on the design of Iterative Learning Control (ILC) schemes based on treating the problem within the framework of the stability/control theory for linear repetitive processes. These processes propagate in two independent directions and arise in the modeling of a number of physical processes. The duration of information propagation in one of the two directions is finite, and this is a key link to ILC which has been developed as a technique for controlling systems which are required to repeat the same operation over a finite duration known as the trial length and information from previous executions is used to update the control input for the next trial and thereby sequentially improve performance. The experimental performance of the new algorithms on a gantry robot is reported, including a comparison with alternative designs