Robust feedback error learning method for controller design of nonlinear systems

Hongping Chen, Kotaro Hirasawa, Jinglu Hu

研究成果: Conference contribution

抄録

This paper presents a new robust controller design method for nonlinear system based on feedback error learning (FEL) method and higher order derivatives of Universal Learning Networks (ULNs). Our idea is to make an inverse model robust to signal noise by adding the sensitivity terms to the standard criterion function. Through feedback error learning, the sensitivity term can be minimized as well as usual criterion functions using the higher order derivatives of ULNs. As a result, it is confirmed by using simulation results that NNC robust against signal noise can be obtained.

本文言語English
ホスト出版物のタイトル2004 IEEE International Joint Conference on Neural Networks - Proceedings
ページ1835-1840
ページ数6
DOI
出版ステータスPublished - 2004 12 1
イベント2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest, Hungary
継続期間: 2004 7 252004 7 29

出版物シリーズ

名前IEEE International Conference on Neural Networks - Conference Proceedings
3
ISSN(印刷版)1098-7576

Conference

Conference2004 IEEE International Joint Conference on Neural Networks - Proceedings
国/地域Hungary
CityBudapest
Period04/7/2504/7/29

ASJC Scopus subject areas

  • ソフトウェア

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