A new robust neural network controller designing method for nonlinear systems

H. Chen, K. Hirasawa, J. Hu, J. Murata

研究成果: Paper査読

抄録

A new designing method of a robust neural network controller against system environment changes using Universal Learning Network (ULN) is considered in this paper. With the introduced method, the worst values of system parameters can be searched as well as the optimization of controller parameters through a dual learning algorithm, which includes maximization and minimization procedures. Therefore, the robust controller can be obtained by minimizing the criterion function regarding the worst values of system parameters. Simulation results demonstrate that the system performance has been improved compared with the conventional method by using the proposed method.

本文言語English
ページ497-502
ページ数6
出版ステータスPublished - 2001 1 1
外部発表はい
イベントInternational Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States
継続期間: 2001 7 152001 7 19

Conference

ConferenceInternational Joint Conference on Neural Networks (IJCNN'01)
国/地域United States
CityWashington, DC
Period01/7/1501/7/19

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

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