A study of PDC fuzzy control of structural systems using LMI approach

Cheng Wu Chen, Wei Ling Chiang, Feng Hsia Hsiao

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

1 Scopus citations

Abstract

This paper proposes a design method of H∞ control performance for structural systems using Tagagi-Sugeno (T-S) fuzzy model. The structural system with tuned mass damper is modeled by T-S type fuzzy model. By using parallel distributed compensation (PDC) scheme, we design a nonlinear fuzzy controller for the tuned mass damper system. This control problem will be reformulated into linear matrix inequalities (LMI) problem. Furthermore, the tuned mass damper will be designed according to the first mode of frequency of the control system and then the fuzzy controller will be found via Matlab LMI toolbox to stabilize the structural system. A simulation example is given to show the feasibility of the proposed fuzzy controller design method.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics)
EditorsM.H. Hamza
Pages40-43
Number of pages4
StatePublished - 2004
EventProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics - Innsbruck, Austria
Duration: 16 Feb 200418 Feb 2004

Publication series

NameProceedings of the IASTED International Conference. Applied Informatics

Conference

ConferenceProceedings of the IASTED International Conference on Artificial Intelligence and Applications (as part of the 22nd IASTED International Multi-Conference on Applied Informatics
Country/TerritoryAustria
CityInnsbruck
Period16/02/0418/02/04

Keywords

  • H∞ control
  • Linear matrix inequality
  • Parallel distributed compensation

Fingerprint

Dive into the research topics of 'A study of PDC fuzzy control of structural systems using LMI approach'. Together they form a unique fingerprint.

Cite this