IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v45y2014i3p487-496.html
   My bibliography  Save this article

Actuator fault estimation for a class of nonlinear descriptor systems

Author

Listed:
  • Zhenhua Wang
  • Yi Shen
  • Xiaolei Zhang

Abstract

This article proposes an actuator fault estimation approach for a class of nonlinear descriptor systems. The radial basis function (RBF) neural networks are utilised to model the actuator faults. The adaptive fault estimation observer is designed by exploiting the on-line learning ability of RBF neural networks to approximate the actuator fault. The adaptive algorithm of the RBF networks is established by the Lyapunov theory, and the design of the proposed observer is reformulated as a set of linear matrix inequalities (LMIs), which can be conveniently solved by standard LMI tools. Finally, two simulation examples are used to demonstrate the effectiveness of the proposed fault diagnosis method.

Suggested Citation

  • Zhenhua Wang & Yi Shen & Xiaolei Zhang, 2014. "Actuator fault estimation for a class of nonlinear descriptor systems," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(3), pages 487-496.
    • Handle: RePEc:taf:tsysxx:v:45:y:2014:i:3:p:487-496
    DOI: 10.1080/00207721.2012.724100
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2012.724100
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2012.724100?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Boukhari, Mohamed Riad & Chaibet, Ahmed & Boukhnifer, Moussa & Glaser, Sébastien, 2019. "Two longitudinal fault tolerant control architectures for an autonomous vehicle," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 156(C), pages 236-253.
    2. Ngoc Phi Nguyen & Nguyen Xuan Mung & Le Nhu Ngoc Thanh Ha & Tuan Tu Huynh & Sung Kyung Hong, 2020. "Finite-Time Attitude Fault Tolerant Control of Quadcopter System via Neural Networks," Mathematics, MDPI, vol. 8(9), pages 1-17, September.
    3. Ngoc Phi Nguyen & Sung Kyung Hong, 2019. "Fault Diagnosis and Fault-Tolerant Control Scheme for Quadcopter UAVs with a Total Loss of Actuator," Energies, MDPI, vol. 12(6), pages 1-22, March.
    4. Ngoc Phi Nguyen & Sung Kyung Hong, 2018. "Fault-Tolerant Control of Quadcopter UAVs Using Robust Adaptive Sliding Mode Approach," Energies, MDPI, vol. 12(1), pages 1-15, December.

    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:taf:tsysxx:v:45:y:2014:i:3:p:487-496. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.