Convergence Analysis of 2-D Theory Based Point-to-Point Iterative Learning Control with Constrained Input

Convergence analysis of the tracking error of point-to-point iterative learning control (P2P-ILC) method with constrained input in the batch process is presented based on two-dimensional (2D) theory. In the P2P-ILC, a tracking reference trajectory passing through the desired points is designed and updated from batch to batch, and then the whole system is described as a 2D system model. For the constrained input, its convex set is abstracted and the procedure of calculating the constrained input is presented in detail. By using dynamic response of 2D model, tracking error convergence properties of the P2P-ILC can be analyzed theoretically. The sufficient convergence conditions of output tracking error in the proposed algorithm are derived for a class of linear systems. Simulation results of a numerical model have demonstrated the proposed method.