Sampled-data iterative learning control for nonlinear systems with iteration varying lengths

Abstract

This note addresses the problem of sampled-data iterative learning control (SDILC) for continuous-time nonlinear systems with randomly iteration varying lengths. To deal with the iteration varying trial lengths, a P-type ILC scheme with a modified tracking error is proposed. Sufficient conditions are derived to ensure the convergence of the nonlinear system at each sampling instant. An illustrative example is carried out to verify the effectiveness of the proposed ILC algorithm.