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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.