Abstract
This paper considers the problem of designing an iterative learning control law for discrete linear systems using repetitive process stability theory The resulting design produces a stabilizing output feedback controller in the time domain and a feedforward controller that guarantees monotonic convergence in the trial-to-trial domain. An extension to design with limited frequency range specifications for uncertain plants is developed. All design computations required for the new results in this paper can be computed using linear matrix inequalities (LMIs). A simulation example is given to illustrate the theoretical developments.
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