IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/713560.html
   My bibliography  Save this article

Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

Author

Listed:
  • Yun Li
  • Guang He
  • Jie Li

Abstract

A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.

Suggested Citation

  • Yun Li & Guang He & Jie Li, 2013. "Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, May.
  • Handle: RePEc:hin:jnlmpe:713560
    DOI: 10.1155/2013/713560
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2013/713560.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2013/713560.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2013/713560?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:713560. 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.