By Topic

2-D analysis for iterative learning controller for discrete-time systems with variable initial conditions

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yong Fang ; Hong Kong Univ., Kowloon, China ; Chow, T.W.S.

In this work, an iterative learning controller applying to linear discrete-time multivariable systems with variable initial conditions is investigated based on two-dimensional (2-D) system theory. The work first introduces a 2-D tracking error system and shows the effect of tracking errors against variable initial conditions. The sufficient conditions for the convergence of the learning control rules are derived and discussed. Based on the proposed iterative learning control (ILC) rule, we have shown that the convergence of the learning rule is guaranteed with less restriction. An improved ILC rule is proposed. As a result, the convergence is robust with respect to small perturbations of the system parameters. Two numerical simulation examples are used to validate the effectiveness of the proposed methodologies.

Published in:

Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on  (Volume:50 ,  Issue: 5 )