Title

Novel iterative learning controls for linear discrete-time systems based on a performance index over iterations

Authors

Authors

S. Y. Yang; Z. H. Qu; X. P. Fan;X. H. Nian

Comments

Authors: contact us about adding a copy of your work at STARS@ucf.edu

Abbreviated Journal Title

Automatica

Keywords

iterative learning control; quadratic performance index; iteration; domain; optimality; CONTROL ALGORITHM; QUADRATIC CRITERION; NONLINEAR-SYSTEMS; FEEDBACK; UNCERTAINTY; DESIGN; Automation & Control Systems; Engineering, Electrical & Electronic

Abstract

An optimal iterative learning control (ILC) is proposed to optimize an accumulative quadratic performance index in the iteration domain for the nominal dynamics of linear discrete-time systems. Properties of stability, convergence, robustness, and optimality are investigated and demonstrated. In the case that the system under consideration contains uncertain dynamics, the proposed ILC design can be applied to yield a guaranteed-cost ILC whose solution can be found using the linear matrix inequality (LMI) technique. Simulation examples are included to demonstrate feasibility and effectiveness of the proposed learning controls. (c) 2008 Elsevier Ltd. All rights reserved.

Journal Title

Automatica

Volume

44

Issue/Number

5

Publication Date

1-1-2008

Document Type

Article

Language

English

First Page

1366

Last Page

1372

WOS Identifier

WOS:000256113400022

ISSN

0005-1098

Share

COinS