• DocumentCode
    2979872
  • Title

    The Research of Nonlinear Control Based on Fuzzy Neural Network

  • Author

    Fan Yuan-yuan ; Sang Ying-jun

  • Author_Institution
    Fac. of Math. & Phys., Huaiyin Inst. of Technol., Huaian, China
  • fYear
    2010
  • fDate
    25-27 June 2010
  • Firstpage
    2417
  • Lastpage
    2420
  • Abstract
    This paper discussed and researched the structure and algorithm of fuzzy neural network controller based on the character of fuzzy logic and neural network theory. For the nonlinear system characteristics of uncertainty, high order and hysteresis, this paper used the fuzzy neural network technology to control nonlinear system and improved the control quality obviously. Take the single inverted pendulum for example, the paper constructed the nonlinear mathematic model, realized the control with the method of the adaptive fuzzy neural network, and compared with control method of liner quadratic regulator, the simulation results indicate that the method of adaptive fuzzy neural network can realize the stabilization of control better without the linear model of system, and has a higher robustness.
  • Keywords
    adaptive control; fuzzy control; fuzzy logic; linear quadratic control; neurocontrollers; nonlinear control systems; pendulums; robust control; adaptive fuzzy neural network; control quality; fuzzy logic; fuzzy neural network controller; fuzzy neural network technology; linear quadratic regulator; neural network theory; nonlinear control system; nonlinear mathematic model; nonlinear system characteristics; robustness; single inverted pendulum; stabilization; Adaptation model; Adaptive systems; Artificial neural networks; Control systems; Data models; Fuzzy control; Fuzzy neural networks; ANFIS; LQR control; nonlinear; robustness; stabilization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Control Engineering (ICECE), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6880-5
  • Type

    conf

  • DOI
    10.1109/iCECE.2010.597
  • Filename
    5629884