Iterative learning control for quasi-one-sided Lipschitz non-linear systems

This paper addresses the problem of iterative learning control for non-linear systems in the presence of initial state errors. Here, the non-linear functions in the considered systems satisfy quasi-one-sided Lipschitz condition, which is an assumption weaker than the classical Lipschitz condition. And the P-type learning scheme is proposed for the corresponding quasi-one-sided Lipschitz non-linear systems. When the learning scheme is applied to the systems, the output tracking errors are bounded, and furthermore, the tracking errors can tend to zero along the iteration axis in the absence of initial state errors. The simulation result verifies the effectiveness of the proposed algorithm.