A Non-fragile Approach to HILC of Linear Discrete-time Systems with Uncertain Learning Gain

Lingchun Li, Guangming Zhang, Meiying Ou, Changlin Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper studies the problem of iterative learning control (ILC) with uncertain learning gain. The ILC controller to be designed with additive gain variations resulting from controller implementations. Resorting to 2D Roesser system manner and Lyapunov method, a new condition is developed to guarantee the desired stability with the prescribed H∞ performance. A sufficient conditions for the ILC controller with additive gain variations design in terms of solutions to a set of linear matrix inequalities (LMIs). To overcome the coupling nonlinearities between system parameters and Lyapunov variable, an effective strategy is employed. A notion of structured vertex separator is utilized to approach the problem of additive gain variations. A numerical example is given to illustrate the effect of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the 40th Chinese Control Conference, CCC 2021
EditorsChen Peng, Jian Sun
PublisherIEEE Computer Society
Pages2196-2201
Number of pages6
ISBN (Electronic)9789881563804
DOIs
StatePublished - 26 Jul 2021
Event40th Chinese Control Conference, CCC 2021 - Shanghai, China
Duration: 26 Jul 202128 Jul 2021

Publication series

NameChinese Control Conference, CCC
Volume2021-July
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference40th Chinese Control Conference, CCC 2021
Country/TerritoryChina
CityShanghai
Period26/07/2128/07/21

Keywords

  • Additive learning gain variations
  • Iterative learning control
  • Linear matrix inequality

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