A design of a strongly stable generalized minimum variance control using a genetic algorithm

Akira Yanou, Mingcong Deng, Akira Inoue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Citations (Scopus)

Abstract

This paper proposes a design scheme of generalized minimum variance control (GMVC) having a new design parameter. The design parameter is introduced by applying coprime factorization approach and Youla-Kucera parameterization of stabilizing compensators to a generalized minimum variance controller. And it is selected by using a genetic algorithm so that the controller is designed to be stable. Therefore the proposed method gives a strongly stable system, that is, not only the closed-loop system is stable, but also the controller itself is stable.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Pages1300-1304
Number of pages5
Publication statusPublished - Dec 1 2009
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: Aug 18 2009Aug 21 2009

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings

Other

OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
CountryJapan
CityFukuoka
Period8/18/098/21/09

Keywords

  • Coprime factorization
  • Generalized minimum variance control
  • Genetic algorithm
  • Strongly stable

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering

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  • Cite this

    Yanou, A., Deng, M., & Inoue, A. (2009). A design of a strongly stable generalized minimum variance control using a genetic algorithm. In ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings (pp. 1300-1304). [5335218] (ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings).