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

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

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 Jan 1
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
CountryTaiwan
CityTaipei
Period06/10/806/10/11

Fingerprint

Fuzzy neural networks
Closed loop systems
Trajectories
Controllers

Keywords

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

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Li, I. H., Wang, W-Y., Su, S. F., & Chen, M. C. (2006). A merged fuzzy-neural network and its application in fuzzy-neural control. In 2006 IEEE International Conference on Systems, Man and Cybernetics (pp. 4529-4534). [4274625] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSMC.2006.384859

A merged fuzzy-neural network and its application in fuzzy-neural control. / Li, I. Hsum; Wang, Wei-Yen; Su, Shun Feng; Chen, Ming Chang.

2006 IEEE International Conference on Systems, Man and Cybernetics. Institute of Electrical and Electronics Engineers Inc., 2006. p. 4529-4534 4274625 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 6).

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

Li, IH, Wang, W-Y, Su, SF & Chen, MC 2006, A merged fuzzy-neural network and its application in fuzzy-neural control. in 2006 IEEE International Conference on Systems, Man and Cybernetics., 4274625, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, vol. 6, Institute of Electrical and Electronics Engineers Inc., pp. 4529-4534, 2006 IEEE International Conference on Systems, Man and Cybernetics, Taipei, Taiwan, 06/10/8. https://doi.org/10.1109/ICSMC.2006.384859
Li IH, Wang W-Y, Su SF, Chen MC. A merged fuzzy-neural network and its application in fuzzy-neural control. In 2006 IEEE International Conference on Systems, Man and Cybernetics. Institute of Electrical and Electronics Engineers Inc. 2006. p. 4529-4534. 4274625. (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2006.384859
Li, I. Hsum ; Wang, Wei-Yen ; Su, Shun Feng ; Chen, Ming Chang. / A merged fuzzy-neural network and its application in fuzzy-neural control. 2006 IEEE International Conference on Systems, Man and Cybernetics. Institute of Electrical and Electronics Engineers Inc., 2006. pp. 4529-4534 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics).
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