A merged fuzzy-neural network and its application in fuzzy-neural control

I. Hsum Li*, Wei Yen Wang, Shun Feng Su, Ming Chang Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes an observer-based adaptive fuzzy-neural controller, structured by a merged fuzzy-neural network (merged-FNN) to reduce the number of adjustable parameters. In this paper, the merged-FNN is proved to take the place of the traditional fuzzy-neural networks under some assumptions. Moreover, the overall adaptive schemes using the proposed merged-FNN guarantees that all signals involved are bounded and the output of the closed-loop system asymptotically tracks the desired output trajectory. From experimental examples, the proposed merged-FNN has far fewer parameters than the traditional FNN, and the computation time is significantly reduced. To demonstrate the effectiveness of the proposed methods, simulation results are illustrated in this paper.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4529-4534
Number of pages6
ISBN (Print)1424401003, 9781424401000
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Systems, Man and Cybernetics - Taipei, Taiwan
Duration: 2006 Oct 82006 Oct 11

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume6
ISSN (Print)1062-922X

Other

Other2006 IEEE International Conference on Systems, Man and Cybernetics
Country/TerritoryTaiwan
CityTaipei
Period2006/10/082006/10/11

Keywords

  • Direct adaptive control
  • Fuzzy-neural control
  • Merged fuzzy-neural network
  • Nonaffine nonlinear systems

ASJC Scopus subject areas

  • General Engineering

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