Title

Novel Iterative Learning Controls For Linear Discrete-Time Systems Based On A Performance Index Over Iterations

Keywords

Iteration domain; Iterative learning control; Optimality; Quadratic performance index

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. © 2008 Elsevier Ltd. All rights reserved.

Publication Date

5-1-2008

Publication Title

Automatica

Volume

44

Issue

5

Number of Pages

1366-1372

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.automatica.2007.10.024

Socpus ID

41949133038 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/41949133038

This document is currently not available here.

Share

COinS