HIGH-ORDER ITERATIVE LEARNING CONTROL FOR DISCRETE-TIME SYSTEM BASED ON MONOTONIC
CONVERGENCE

LI Hongsheng^{1, 2}

(1. Department of Automation, Nanjing Institute of Technology, Nanjing 210013;

2. Deptarment of Automatic Control, Southeast University, Nanjing 210096)

Abstract: Monotonic convergence condition of high-order iterative learning control (ILC) in a suitable norm topology is discussed for a class of discrete-time linear time-invariant system. Optimal parameters design of the ILC scheme is presented and corresponding convergence rate is analyzed. The commonly used algorithms of discrete P, D, PD iterative learning control can be considered examples of the proposed updating law. Simulation results show that better monotonic convergence performance is achieved by using the optimal design.

Key words:Iterative learning control  Monotonic convergence  Discrete-time linear time-invariant system  Optimal design

CLC No: TP13  TP242

Received 20050717, received in revised form 20060206