• DocumentCode
    2536039
  • Title

    Application of fractional derivative in control functions

  • Author

    Yahyazadeh, Meisam ; Haeri, Mohammad

  • Author_Institution
    Electr. Eng. Dept., Islamic Azad Univ., Tehran
  • Volume
    1
  • fYear
    2008
  • fDate
    11-13 Dec. 2008
  • Firstpage
    252
  • Lastpage
    257
  • Abstract
    Application of fractional derivative in control problems such as sliding surface design in sliding mode control, training of MLP in neural networks, and parameters updating in model reference adaptive control is studied in this paper. Use of the fractional derivative increases possibility of improving the control performance by reducing the convergence time in the mentioned control problems. This gain is attained due to the higher degree of freedom exist in the fractional dynamical systems. We study such control problems by replacing the integer order derivative with the fractional order derivative. The performance of the proposed methods is illustrated through computer simulations of gyro and ball and beams systems.
  • Keywords
    control system analysis; model reference adaptive control systems; multilayer perceptrons; neurocontrollers; variable structure systems; MLP; ball-beams systems; computer simulations; control functions; fractional dynamical systems; fractional order derivative; gyros; model reference adaptive control; neural networks; sliding mode control; sliding surface design; Adaptive control; Books; Computer simulation; Control system analysis; Control systems; Convergence; Fractional calculus; History; Neural networks; Sliding mode control; Fractional MLP neural networks; Fractional derivative; Fractional order adaptation law; Fractional sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference, 2008. INDICON 2008. Annual IEEE
  • Conference_Location
    Kanpur
  • Print_ISBN
    978-1-4244-3825-9
  • Electronic_ISBN
    978-1-4244-2747-5
  • Type

    conf

  • DOI
    10.1109/INDCON.2008.4768835
  • Filename
    4768835