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

Yih Guang Leu, Chin Ming Hong, Hong Jian Zhon

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

1 Citation (Scopus)

Abstract

A GA-based adaptive fuzzy-neural controller for a class of multi-input multi-output nonlinear systems, such as robotic systems, is developed for using observers to estimate time derivatives of the system outputs. The weighting parameters of the fuzzy-neural controller are tuned on-line via a genetic algorithm (GA). For the purpose of on-line tuning the weighting parameters of the fuzzy-neural controller, a Lyapunov-based fitness function of the GA is obtained. Besides, stability of the closed-loop system is proven by using strictly-positive-real (SPR) Lyapunov theory. The proposed overall scheme guarantees that all signals involved are bounded and the outputs of the closed-loop system track the desired output trajectories. Finally, simulation results are provided to demonstrate robustness and applicability of the proposed method.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
PublisherSpringer Verlag
Pages45-53
Number of pages9
EditionPART 1
ISBN (Print)9783540723820
DOIs
Publication statusPublished - 2007 Jan 1
Event4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China
Duration: 2007 Jun 32007 Jun 7

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4491 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Symposium on Neural Networks, ISNN 2007
CountryChina
CityNanjing
Period07/6/307/6/7

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'GA-based adaptive fuzzy-neural control for a class of MIMO systems'. Together they form a unique fingerprint.

  • Cite this

    Leu, Y. G., Hong, C. M., & Zhon, H. J. (2007). GA-based adaptive fuzzy-neural control for a class of MIMO systems. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 1 ed., pp. 45-53). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_7