• DocumentCode
    3480222
  • Title

    Study on Sliding Mode Control with RBF Network for DSTATCOM

  • Author

    Xu, Yanqing ; Ma, Caoyuan ; Yang, Longyue ; Gong, Zheng ; Pu, Hailin ; Zhang, Zhen

  • Author_Institution
    China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2010
  • fDate
    7-9 Nov. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    For the problems of parameters disturbance, nonlinear and uncertainty of distribution static compensator (DSTATCOM), this paper studies on sliding mode control based on radial basis function (RBF) network. The fast tracking of DSTATCOM reactive current is achieved by using of RBF neural networks and equivalent sliding mode control. The method has a strong adaptability and robustness for load disturbances and system parameters change, and integrates the advantages of neural network and sliding mode control, so it is an ideal intelligent control strategy .The MATLAB simulation results show that the controller has good dynamic and static quality, and provides an effective way for improving the performance of DSTATCOM.
  • Keywords
    neurocontrollers; radial basis function networks; static VAr compensators; variable structure systems; DSTATCOM reactive current; MATLAB simulation; RBF neural networks; distribution static compensator; intelligent control strategy; load disturbances; parameters disturbance; radial basis function network; sliding mode control; system parameters change; Capacitance; Equations; Mathematical model; Radial basis function networks; Robustness; Sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Product E-Service and E-Entertainment (ICEEE), 2010 International Conference on
  • Conference_Location
    Henan
  • Print_ISBN
    978-1-4244-7159-1
  • Type

    conf

  • DOI
    10.1109/ICEEE.2010.5661056
  • Filename
    5661056