IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/701671.html
   My bibliography  Save this article

Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates

Author

Listed:
  • Chih-Hong Kao
  • Chun-Fei Hsu
  • Chih-Hu Wang
  • Hon-Son Don

Abstract

This paper addresses the synchronization of chaotic gyros with unknown parameters and external disturbance via an adaptive dynamic neural network control (ADNNC) system. The proposed ADNNC system is composed of a neural controller and a smooth compensator. The neural controller uses a dynamic RBF (DRBF) network to online approximate an ideal controller. The DRBF network can create new hidden neurons online if the input data falls outside the hidden layer and prune the insignificant hidden neurons online if the hidden neuron is inappropriate. The smooth compensator is designed to compensate for the approximation error between the neural controller and the ideal controller. Moreover, the variable learning rates of the parameter adaptation laws are derived based on a discrete-type Lyapunov function to speed up the convergence rate of the tracking error. Finally, the simulation results which verified the chaotic behavior of two nonlinear identical chaotic gyros can be synchronized using the proposed ADNNC scheme.

Suggested Citation

  • Chih-Hong Kao & Chun-Fei Hsu & Chih-Hu Wang & Hon-Son Don, 2011. "Chaos Synchronization Using Adaptive Dynamic Neural Network Controller with Variable Learning Rates," Mathematical Problems in Engineering, Hindawi, vol. 2011, pages 1-20, April.
    • Handle: RePEc:hin:jnlmpe:701671
    DOI: 10.1155/2011/701671
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2011/701671.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2011/701671.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2011/701671?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:jnlmpe:701671. 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.