Skip to main content
Kent Academic Repository

Adaptive Sliding-Mode-Observer-Based Fault Reconstruction for Nonlinear Systems With Parametric Uncertainties

Yan, Xinggang, Edwards, Christopher (2008) Adaptive Sliding-Mode-Observer-Based Fault Reconstruction for Nonlinear Systems With Parametric Uncertainties. IEEE Transactions on Industrial Electronics, 55 (11). pp. 4029-4036. ISSN 0278-0046. (doi:10.1109/TIE.2008.2003367) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:27727)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1109/TIE.2008.2003367

Abstract

In this paper, a class of nonlinear systems with uncertain parameters is considered. A novel adaptive law is designed to identify unknown parameters under the assumption that the time derivative of some of the outputs is measurable. Then, a sliding-mode observer is proposed to estimate the system state variables. By using the inherent features of sliding-mode observers, a fault-reconstruction scheme is proposed which can be implemented online. The proposed reconstruction signal can approximate the fault signal to any required accuracy even in the presence of uncertain parameters. A simulation example for a magnetic-levitation system is given to illustrate the feasibility and effectiveness of the proposed scheme.

Item Type: Article
DOI/Identification number: 10.1109/TIE.2008.2003367
Subjects: T Technology > TJ Mechanical engineering and machinery > Control engineering
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: J. Harries
Date Deposited: 26 Apr 2011 09:35 UTC
Last Modified: 16 Nov 2021 10:06 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/27727 (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.