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
Pages45-53
Number of pages9
EditionPART 1
Publication statusPublished - 2007 Dec 24
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

Fingerprint

Neural Control
MIMO Systems
Fuzzy Control
MIMO systems
Genetic algorithms
Genetic Algorithm
Closed loop systems
Controllers
Output
Controller
Genetic Fitness
Closed-loop System
Weighting
Robotics
Lyapunov Theory
Nonlinear systems
Strictly positive
Tuning
Fitness Function
Trajectories

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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).

GA-based adaptive fuzzy-neural control for a class of MIMO systems. / Leu, Yih-Guang; Hong, Chin-Ming; Zhon, Hong Jian.

Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. 2007. p. 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).

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

Leu, Y-G, Hong, C-M & Zhon, HJ 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 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4491 LNCS, pp. 45-53, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 07/6/3.
Leu Y-G, Hong C-M, Zhon HJ. 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. 2007. p. 45-53. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
Leu, Yih-Guang ; Hong, Chin-Ming ; Zhon, Hong Jian. / GA-based adaptive fuzzy-neural control for a class of MIMO systems. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. 2007. pp. 45-53 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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