Hybrid adaptive control based on a Hopfield dynamic neural network for nonlinear dynamical systems

I. Hsum Li*, Lian Wang Lee, Wei Yen Wang

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

摘要

In this paper, we propose a hybrid adaptive control scheme based on Hopfield-based dynamic neural network (HACHNN) for SISO nonlinear systems. An auxiliary direct adaptive controller is proposed to ensure the stability in the time-interval of when an indirect adaptive controller is failed because of ĝ(x)→0. The weights of the Hopfield-based dynamic neural network are on-line tuned by the adaptive laws derived in the sense of Lyapunov theorem, so that the stability of the closed-loop system can be guaranteed, and all signals in the closed-loop system are bounded. The designed structure of the Hopfield-based dynamic neural network maintains the tracking performance of the control scheme, and it also makes the practical implementation much easier.

原文英語
主出版物標題2012 International Joint Conference on Neural Networks, IJCNN 2012
DOIs
出版狀態已發佈 - 2012 八月 22
事件2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, 澳大利亚
持續時間: 2012 六月 102012 六月 15

出版系列

名字Proceedings of the International Joint Conference on Neural Networks

其他

其他2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
國家/地區澳大利亚
城市Brisbane, QLD
期間2012/06/102012/06/15

ASJC Scopus subject areas

  • 軟體
  • 人工智慧

指紋

深入研究「Hybrid adaptive control based on a Hopfield dynamic neural network for nonlinear dynamical systems」主題。共同形成了獨特的指紋。

引用此