Adaptive fuzzy-neural observer for a class of nonlinear systems

Yih Guang Leu, Tsu Tian Lee

研究成果: 雜誌貢獻期刊論文同行評審

2 引文 斯高帕斯(Scopus)

摘要

Based on the H control technique and the strictly positive real Lyapunov (SPR-Lyapunov) design approach, an adaptive fuzzy-neural observer tuned on-line for a class of uncertain (unknown) nonlinear systems is developed. Unlike previous results, the assumption that the uncertain system nonlinearities only are restricted to the system output is not required. Moreover, the adaptive fuzzy-neural observer provides the modeling error (and the external bounded disturbance) attenuation with H performance, obtained by a Riccati-like equation. Finally, simulation results demonstrate that the proposed observer yields satisfactory performance.

原文英語
頁(從 - 到)2130-2135
頁數6
期刊Proceedings-IEEE International Conference on Robotics and Automation
3
DOIs
出版狀態已發佈 - 2000 四月
對外發佈

ASJC Scopus subject areas

  • 軟體
  • 控制與系統工程
  • 人工智慧
  • 電氣與電子工程

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