Interval type-2 recurrent fuzzy neural system desing via stable simultaneous perturbation stochastic approximation algorithm

Feng Yu Chang*, Ching Hung Lee

*Corresponding author for this work

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

2 Scopus citations

Abstract

This paper proposes a new type fuzzy neural systems, denotes IT2RFNS-A (interval type-2 recurrent fuzzy neural system with asymmetric membership function), for nonlinear systems control. To enhance the performance and approximation ability, the TSK-type consequent part is adopted for IT2RFNS-A. The gradient information of the IT2RFNS-A is not easy to obtain due to the asymmetric membership functions and interval valued sets. The corresponding stable learning is derived by simultaneous perturbation stochastic approximation (SPSA) algorithm which guarantees the convergence and stability of the closed-loop systems. Simulation and comparison on the control of Chua's chaotic circuit is done to show the feasibility and effectiveness of proposed method.

Original languageEnglish
Title of host publicationFUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings
Pages2155-2162
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011 - Taipei, Taiwan
Duration: 27 Jun 201130 Jun 2011

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2011 IEEE International Conference on Fuzzy Systems, FUZZ 2011
CountryTaiwan
CityTaipei
Period27/06/1130/06/11

Keywords

  • fuzzy neural system
  • Lyapunov theorem
  • Nonlinear systems
  • SPSA algorithm
  • type-2 fuzzy system

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    Chang, F. Y., & Lee, C. H. (2011). Interval type-2 recurrent fuzzy neural system desing via stable simultaneous perturbation stochastic approximation algorithm. In FUZZ 2011 - 2011 IEEE International Conference on Fuzzy Systems - Proceedings (pp. 2155-2162). [6007489] (IEEE International Conference on Fuzzy Systems). https://doi.org/10.1109/FUZZY.2011.6007489