P-type Iterative Learning Control with Initial State Learning for One-sided Lipschitz Nonlinear Systems

Abstract

In this paper, the problem of iterative learning control is considered for a class of one-sided Lipschitz nonlinear systems. For such nonlinear systems, open-loop and closed-loop P-type learning algorithms with initial state learning are adopted, respectively. Furthermore, the convergence conditions of the P-type learning algorithms are established. It is shown that both algorithms can guarantee the system output converges to the desired one on the whole time interval. A numerical example is constructed to illustrate the effectiveness of the proposed learning algorithms.