Iterative learning control for discrete-time affine nonlinear system with iteration varying lengths

This note proposes ILC for discrete-time affine nonlinear systems with randomly iteration varying lengths. No prior information on the probability of random iteration length is required. The conventional P-type update law is used with a modified tracking error because of random iteration length. The modified supremum norm technique is used to prove the zero convergence of tracking error. Illustrative example show the effectiveness of the proposed algorithm.