Using 2D systems theory to design output signal based iterative learning control laws with experimental verification

In this paper we use a 2D systems setting to develop new results on iterative learning control for linear plants, where it is well known in the subject area that a trade-off exists between speed of convergence and the response along the trials. Here we give new results by designing the control scheme using a strong form of stability for repetitive processes/2D linear systems known as stability along the pass (or trial). The resulting design computations are in terms of Linear Matrix Inequalities (LMIs) and they are also experimentally validated on a gantry robot. The control laws only use plant output information and hence the use of a state observer is avoided.