• DocumentCode
    3693115
  • Title

    Adaptive neural backstepping control strategy of three-phase active power filter

  • Author

    Yunmei Fang;Juntao Fei;Zhe Wang

  • Author_Institution
    College of Mechanical and Electrical Engineering, Hohai University, Changzhou, 213022, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    380
  • Lastpage
    385
  • Abstract
    In this paper, an adaptive neural backstepping controller (ANBC) is proposed for three- phase active power filter (APF). An adaptive neural controller is developed to deal with the nonlinear APF system using backstepping method, improving the current tracking and increasing the power quality. The proposed radial basis function (RBF) neural network (NN) whose weights are adjusted online by the adaptive law is designed to approximate the nonlinear function of APF model. The proposed ANBC can realize the desired dynamic behavior and improve the robustness of the APF system. Simulations using MATLAB /SimPower Systems Toolbox demonstrate the high performance of the proposed adaptive neural backstepping control strategy.
  • Keywords
    "Active filters","Backstepping","Neural networks","Adaptive systems","Power harmonic filters","Lyapunov methods","Harmonic analysis"
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2015 European
  • Type

    conf

  • DOI
    10.1109/ECC.2015.7330573
  • Filename
    7330573