New time-efficient structure for observer-based adaptive fuzzy-neural controllers for nonaffine nonlinear systems

Wei-Yen Wang*, I. Hsum Li, Ming Chang Chen, Shun Feng Su, Yih-Guang Leu

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

6 引文 斯高帕斯(Scopus)

摘要

This paper proposes an observer-based adaptive controller with a merged fuzzy-neural network for nonaffine nonlinear systems under the constraint that only the system output is available for measurement. Using a conventional fuzzy-neural network leads to rule explosion which leads to huge computation time. Our proposed merged-FNN does not have this problem, and can take the place of the conventional fuzzy-neural networks under some assumptions while maintaining the property of stability. Moreover, the adaptive scheme using the merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. Finally, this paper gives examples of the proposed controller for nonaffine nonlinear systems, and is shown to provide good effectiveness.

原文英語
頁(從 - 到)963-978
頁數16
期刊International Journal of Innovative Computing, Information and Control
6
發行號3
出版狀態已發佈 - 2010 三月 1

ASJC Scopus subject areas

  • 軟體
  • 理論電腦科學
  • 資訊系統
  • 計算機理論與數學

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