2D systems based iterative learning control design for multiple-input multiple-output systems

Iterative learning control can be applied to systems that repeat the same task over a finite duration with resetting to the starting location once each one is complete. The novel feature is the use of information from previous executions of the task in order to update the control signal applied during the next one and thereby sequentially improve performance. Linear iterative learning control laws can be designed using 2D systems theory and recently experimental validation of such designs for single-input single-output examples has been reported. This paper gives the first results on extending this approach to systems with more than one input and output.