Intelligent Chaos Synchronization of Fractional Order Systems via Mean-Based Slide Mode Controller

Chi-Hsu Wang*, Chun Yao Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In this paper, a new mean-based adaptive fuzzy neural network sliding mode control is developed to perform the chaos synchronization among the master-slave fractional order uncertain systems. The mean-based expansion is adopted to replace the traditional Taylor expansion to transform a nonlinear function into a partially linear form for the linearization of nonlinear systems. In comparison with the traditional Taylor method, the proposed mean-based method can estimate the first-order derivative term on the identifier model, which will somehow alleviate the computational burden. Based on the learning algorithms, the adaptive laws and control laws can be tuned on-line to synchronize the master-slave fractional order uncertain systems. Furthermore, the stability of the closed-loop system can not only be assured but the synchronization deviation of external perturbation can also be alleviated. Finally, simulation examples are illustrated to demonstrate the feasibility and the synchronization performance of this new approach.

Original languageEnglish
Pages (from-to)144-157
Number of pages14
JournalInternational Journal of Fuzzy Systems
Volume17
Issue number2
DOIs
StatePublished - 29 Jun 2015

Keywords

  • Adaptive fuzzy neural network
  • Chaotic systems
  • Fractional order
  • Mean-based expansion
  • Sliding mode control

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