A design method of extended generalized minimum variance control based on state space approach by using a genetic algorithm

Akira Yanou, Mingcong Deng, Akira Inoue

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

This paper explores a selection method of the design parameter introduced in the extended Generalized Minimum Variance Control (GMVC) based on state space approach by using a genetic algorithm. Its parameter can design the controller poles to be stable without changing the closed-loop poles. That is, a strongly stable system can be obtained. And the genetic algorithm is applied to calculate the design parameter and give the stable controller poles.

Original languageEnglish
Pages (from-to)4183-4194
Number of pages12
JournalInternational Journal of Innovative Computing, Information and Control
Volume7
Issue number7 B
Publication statusPublished - Jul 2011

Fingerprint

Generalized Variance
Minimum Variance
Design Method
Pole
Poles
State Space
Genetic algorithms
Genetic Algorithm
Parameter Design
Controller
Controllers
Closed-loop
Calculate

Keywords

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

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems
  • Software
  • Theoretical Computer Science

Cite this

A design method of extended generalized minimum variance control based on state space approach by using a genetic algorithm. / Yanou, Akira; Deng, Mingcong; Inoue, Akira.

In: International Journal of Innovative Computing, Information and Control, Vol. 7, No. 7 B, 07.2011, p. 4183-4194.

Research output: Contribution to journalArticle

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