Iterative learning control with an optimality criterion

An improved iterative learning control based on optimality criterion is proposed in this paper. The control signal in each trial is calculated as the solution of a minimum norm optimization problem with a reasonable performance index. The convergence of the tracking error sequence and input sequence can be proved by the properties of optimality criterion instantly. The iterative learning control algorithm of linear time-varying system assures that the input sequence will converge to the optimal control of linear quadratic tracking problem. The algorithm achieves an exponential rate of convergence. The theory of the proposed algorithm is verified through the comparison in the simulation studies.