• DocumentCode
    3117210
  • Title

    Fractional order chaotic system tracking design based on adaptive hybrid intelligent control

  • Author

    Lin, Tsung-Chih ; Kuo, Chia-Hao ; Balas, Valentina Emilia

  • Author_Institution
    Dept. of Electron. Eng., Feng-Chia Univ., Taichung, Taiwan
  • fYear
    2011
  • fDate
    27-30 June 2011
  • Firstpage
    2890
  • Lastpage
    2896
  • Abstract
    In this paper, an adaptive hybrid fuzzy neural network (FNN) controller is proposed to achieve prescribed tracking performance of fractional order chaotic systems. Based on the trade-off between plant knowledge and control knowledge, a weighting factor can be adjusted by combining the indirect adaptive FNN control effort and the direct FNN adaptive control effort. Nonlinear fractional order chaotic response system is fully illustrated to track the trajectory generated from fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control scheme is more flexible during the design process.
  • Keywords
    adaptive control; chaos; drives; fuzzy neural nets; neurocontrollers; nonlinear control systems; tracking; adaptive hybrid fuzzy neural network controller; adaptive hybrid intelligent control; direct fuzzy neural network adaptive control effort; fractional order chaotic drive system; fractional order chaotic system tracking design; hybrid intelligent control scheme; indirect adaptive fuzzy neural network control effort; nonlinear fractional order chaotic response system; tracking performance; weighting factor; Adaptive systems; Approximation methods; Chaos; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Trajectory; Fractional order chaotic systems; adaptive hybrid control; fuzzy neural network (FNN);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2011 IEEE International Conference on
  • Conference_Location
    Taipei
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4244-7315-1
  • Electronic_ISBN
    1098-7584
  • Type

    conf

  • DOI
    10.1109/FUZZY.2011.6007356
  • Filename
    6007356