Iterative Learning Control for Constrained Linear Systems Using Successive Projection
نویسندگان
چکیده
This paper considers iterative learning control for linear systems with convex control input constraints. First, the constrained ILC problem is formulated in a novel successive projection framework. Then, based on this projection method, a constrained ILC algorithm is proposed to solve this constrained ILC problem. The results show that, when perfect tracking is possible, the proposed algorithm can achieve perfect tracking. When perfect tracking is not possible, the algorithm can exhibit a form of practical convergence to a ”best approximation”. The effect of weighting matrices on the performance of the algorithm is also discussed and finally, numerical simulations are given to demonstrate the effectiveness of the proposed method.
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