Repetitive process based iterative learning control design using frequency domain analysis

This paper gives new results on the design of iterative learning control laws that enables one step design of a stabilizing feedback controller in the time domain and a feedforward (learning) controller which guarantees convergence in the trial domain. The Kalman-Yakubovich-Popov lemma is central to the analysis and the resulting computations use convex optimization over linear matrix inequalities. An illustrative example is given based on the model of an experimental facility that has been used to compare alternative iterative learning control designs.