Observer-based adaptive fuzzy-neural control for a class of MIMO nonlinear systems

Yih Guang Leu*, Tsu Tian Lee

*此作品的通信作者

研究成果: 會議貢獻類型會議論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this paper, an observer-based adaptive fuzzy-neural controller for a class of multi-input multi-output (MIMO) nonlinear systems is developed based on observers used to estimate the time derivatives of the system outputs. The proposed method has the merit that no differentiation of the system output is required in order to avoid the noise amplification associated with numerical differentiation. The stability of the observer-based adaptive fuzzy-neural controller is proven by using strictly-positive-real (SPR) Lyapunov theory. The overall adaptive scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system asymptotically track the desired output trajectories. Finally, simulation results are provided to demonstrate the robustness and applicability of the proposed method.

原文英語
頁面178-183
頁數6
出版狀態已發佈 - 2000
對外發佈
事件26th Annual Conference of the IEEE Electronics Society IECON 2000 - Nagoya, 日本
持續時間: 2000 10月 222000 10月 28

其他

其他26th Annual Conference of the IEEE Electronics Society IECON 2000
國家/地區日本
城市Nagoya
期間2000/10/222000/10/28

ASJC Scopus subject areas

  • 控制與系統工程
  • 電氣與電子工程

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