A New Minimax Control Method for Nonlinear Systems Using Universal Learning Networks

• CHEN Hongping

  Kyushu University

• HIRASAWA Kotaro

  Kyushu University

• HU Jinglu

  Kyushu University

• MURATA Junichi

  Kyushu University

書誌事項

タイトル別名

• New Minimax Control Method for Nonlinear Systems Using Universal Learning Networks

抄録

In neural network based control systems, if system environments, that is, system parameters and distur-bances at training stage, are much different from those at control stage, performances of control systems may become worse. To solve this problem, robust control design is needed. In this paper, we propose a new minimax control method using Universal Learning Networks, in which the criterion function is evaluated at several specific operating points, and at each training step the worst criterion function among the operating points is optimized. Moreover, a sensitivity term calculated on the operating point is included in the crite-rion function in order to improve the performance of the control system between two operating points. The minimax control method including sensitivity term is shown to have better robustness against the changes of system parameters.

収録刊行物

• 電気学会論文誌Ｃ（電子・情報・システム部門誌）

  電気学会論文誌Ｃ（電子・情報・システム部門誌） 121 (9), 1471-1478, 2001

  一般社団法人 電気学会

キーワード

• Universal Learning Networks
• Neural networks
• Minimax control
• Robust control
• Neural network con-trol
• Sensitivity

詳細情報

• CRID: 1390282679587765120
• NII論文ID: 130006845812
• NII論文ID: 10006760111
• NII書誌ID: AN10065950
• DOI: 10.1541/ieejeiss1987.121.9_1471
• ISSN: 13488155
• ISSN: 03854221
• NDL書誌ID: 5894377
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I5894377
• Web Site: https://www.jstage.jst.go.jp/article/ieejeiss1987/121/9/121_9_1471/_pdf
• 本文言語コード: en
• データソース種別:
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  • NDL
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