A quasi-ARX model incorporating neural network for control of nonlinear systems

Jinglu Hu, Kotaro Hirasawa, Kousuke Kumamaru

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Neural networks have been known as flexible nonlinear black-box models and have attracted much interest in control community. This paper introduces a new neural-network based prediction model for control of nonlinear systems. Distinctive features of the new model to the conventional neural-network based ones are that it has not only meaningful interpretation on part of its parameters but also is linear for the input variables. The former feature makes the parameter estimation easier and the latter allows deriving a nonlinear controller directly from the identified prediction model. The modeling and the parameter estimation are described in detail. The usefulness of the new model is demonstrated by applying it to control of two simulated nonlinear black-box systems.

本文言語English
ホスト出版物のタイトルIFAC Proceedings Volumes (IFAC-PapersOnline)
編集者Gabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
出版社IFAC Secretariat
ページ199-204
ページ数6
1
ISBN(印刷版)9783902661746
DOI
出版ステータスPublished - 2002
外部発表はい
イベント15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
継続期間: 2002 7 212002 7 26

出版物シリーズ

名前IFAC Proceedings Volumes (IFAC-PapersOnline)
番号1
15
ISSN(印刷版)1474-6670

Other

Other15th World Congress of the International Federation of Automatic Control, 2002
国/地域Spain
CityBarcelona
Period02/7/2102/7/26

ASJC Scopus subject areas

  • 制御およびシステム工学

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