H-observer-based adaptive fuzzy-neural control for a class of uncertain nonlinear systems

研究成果: 雜誌貢獻Conference article

2 引文 斯高帕斯(Scopus)

摘要

This paper presents a method for designing an H-observer-based adaptive fuzzy-neural output feedback control law with on-line tuning of fuzzy-neural weighting factors for a class of uncertain nonlinear systems based on the H control technique and the strictly positive real Lyapunov (SPR-Lyapunov) design approach. The H-observer-based output feedback control law guarantees all signals involved are bounded, and provides the modeling error (and the external bounded disturbance) attenuation with H performance, obtained by a Riccati-like equation. Besides, the H-observer-based output feedback control law doesn't require the assumptions of the total system states available for measurement and the uncertain system nonlinearities only restricted to the system output. Finally, an example is simulated in order to confirm the effectiveness and applicability of the proposed methods.

原文英語
頁(從 - 到)I-449 - I-454
期刊Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
1
出版狀態已發佈 - 1999 十二月 1
事件1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
持續時間: 1999 十月 121999 十月 15

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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