Norm-optimal control of time-varying discrete repetitive processes

This paper extends the norm-optimal control design methodology of iterative learning control to the case of time-varying discrete repetitive processes. As a first contribution, starting from a lifting-based formulation, we show a novel iteration-domain state-space description for discrete-repetitive processes. We then pose and solve the norm-optimal control problem for this class of systems. We present solutions for three cases: optimal regulation, two-degree-of-freedom optimal tracking, and optimal robust servomechanism-based tracking of iteration-invariant reference signals.