Identification of nonlinear systems using Gaussian mixture of local models

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Identification of operating regime based models of nonlinear dynamic systems is addressed. The operating regimes and the parameters of the local linear models are identified directly and simultaneously based on the Expectation Maximization (EM) identification of Gaussian Mixture Model (GMM). The proposed technique is demonstrated by means of the identification of a neutralization reaction in a continuously stirred tank reactor.

Original languageEnglish
Pages (from-to)129-134
Number of pages6
JournalHungarian Journal of Industrial Chemistry
Volume29
Issue number2
Publication statusPublished - 2001

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Nonlinear systems
Identification (control systems)
Dynamical systems

Keywords

  • Expectation maximization
  • Neutralization reaction
  • Nonlinear system
  • Operating regime based model
  • Takagi-Sugeno fuzzy model

ASJC Scopus subject areas

  • Chemistry (miscellaneous)
  • Chemistry(all)
  • Chemical Engineering(all)

Cite this

Identification of nonlinear systems using Gaussian mixture of local models. / Abonyi, J.; Chovan, T.; Szeifert, F.

In: Hungarian Journal of Industrial Chemistry, Vol. 29, No. 2, 2001, p. 129-134.

Research output: Contribution to journalArticle

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