PID type iterative learning control with optimal variable coefficients

Abstract

Iterative learning control (ILC) is a technique to make use of the repetitiveness of the tasks, a system is commanded to execute in a fixed finite time interval. In this paper, we assume that the system to be controlled is discrete time and described by linear state space equations. We present a proportional, integral, derivative (PID) type ILC updating law with variable coefficients. An optimal procedure is used to determine the coefficients of PID type ILC so that the norm of error between the output of systems and desired trajectory is become minimize. The simulation example is included to illustrate the effectiveness of the proposed method.