IDEAS home Printed from https://ideas.repec.org/a/hin/complx/8086088.html
   My bibliography  Save this article

Fuzzy Wavelet Neural Network with the Improved Levenberg–Marquardt Algorithm for the AC Servo System

Author

Listed:
  • Run-Min Hou
  • Di-Fen Shi
  • Qiang Gao
  • Yuan-Long Hou
  • Long Wang

Abstract

In this study, a fuzzy wavelet neural network with the improved Levenberg–Marquardt algorithm (FWNN-LM) is proposed to conquer nonlinearity and uncertain disturbance problems in the AC servo system. First of all, use the particle swarm optimization algorithm based on Levenberg–Marquardt (LM) to optimize parameters in the FWNN controller. Second, the potentiality of fuzzy rules (PFR) method is developed to optimize the structure of the FWNN by error reduction ratio (ERR). Furthermore, stability of FWNN-LM is proved by the Lyapunov method. Finally, simulation and prototype test results show that this method can improve the accuracy and robustness of the system in presence of load disturbances and parameter perturbations.

Suggested Citation

  • Run-Min Hou & Di-Fen Shi & Qiang Gao & Yuan-Long Hou & Long Wang, 2021. "Fuzzy Wavelet Neural Network with the Improved Levenberg–Marquardt Algorithm for the AC Servo System," Complexity, Hindawi, vol. 2021, pages 1-12, October.
    • Handle: RePEc:hin:complx:8086088
    DOI: 10.1155/2021/8086088
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2021/8086088.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2021/8086088.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/8086088?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:8086088. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.