2D systems based iterative learning control revisited

Iterative learning control can be applied to systems that repeat the same task over a finite duration with resetting to the starting point once each one is complete. The idea of iterative learning control is to make use of information from previous executions of the task in order to update the control signal applied during the current execution and thereby sequentially improve performance. This form of control can be treated as a class of 2D systems. In this paper, a critical overview of progress on this application area for 2D systems theory is given, including results from experimental verification on a gantry robot, and discussion of some open research questions.