• DocumentCode
    572268
  • Title

    Hysteresis Control Method Based on RBF Neural Network

  • Author

    Xi Zi-qiang ; Guo Huiming ; Qi Lei

  • Author_Institution
    Sch. of Electr. & Electron. Eng., HuBei Univ. of Technol., Wuhan, China
  • fYear
    2012
  • fDate
    27-29 March 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The key to the effect of active power filter compensation is compensating current :in order to make it better tracking instruction current,using the RBF neural network of hysteresis controllers,with a "K-means, RLS" algorithm for training is applied.Simulation results show that, neural network control is effective for fast variables, clould improve the performance of hysteresis control, get very strong robustness to the system ,and it also verify the theoretical analysis is correct.
  • Keywords
    hysteresis; neural nets; power filters; radial basis function networks; RBF neural network; active power filter compensation; hysteresis control method; tracking instruction current; Active filters; Algorithm design and analysis; Control systems; Harmonic analysis; Hysteresis; Neural networks; Power harmonic filters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
  • Conference_Location
    Shanghai
  • ISSN
    2157-4839
  • Print_ISBN
    978-1-4577-0545-8
  • Type

    conf

  • DOI
    10.1109/APPEEC.2012.6307488
  • Filename
    6307488
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=572268