Internal model-based robust iterative learning control for uncertain LTI systems

Investigates the combination of an iterative learning control (ILC) with an internal model control (IMC) for uncertain linear time-invariant (LTI) systems. The convergence of the iterative process is investigated and reformulated as a general robust control problem. For a certain choice of the IMC and ILC filters, we prove that the condition of convergence to zero of the iterative process is nothing but the robust performance condition of the IMC structure. Using the general robust control formulation, we propose a design procedure for the ILC-IMC filters using the /spl mu/-synthesis approach.