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Fuzzy parity equation for fault detection and identification of nonlinear systems

  • Hua Song*
  • , C. W. Chan
  • , Hong Yue Zhang
  • *Corresponding author for this work
  • The University of Hong Kong
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A fault detection and identification method for nonlinear systems based on fuzzy parity equations is presented. The proposed technique involves approximating first the nonlinear system by a T-S model, and then fully-decoupled parity equations are derived for the local linear models. Residuals generated from the fuzzy parity equations in the T-S model are fused by another T-S model. As the residual generated by the fuzzy parity equation is sensitive to a specific actuator or sensor fault, and insensitive to other faults, system states and disturbance inputs, faults can be detected and/or identified. A simulation example involving a nonlinear airplane model is presented to illustrate the performance of the proposed technique.

Original languageEnglish
Title of host publication6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006
Pages390-395
Number of pages6
EditionPART 1
StatePublished - 2006
Event6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006 - Beijing, China
Duration: 29 Aug 20061 Sep 2006

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume6
ISSN (Print)1474-6670

Conference

Conference6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2006
Country/TerritoryChina
CityBeijing
Period29/08/061/09/06

Keywords

  • Fault detection and identification
  • Fault diagnosis
  • Fuzzy model
  • Nonlinear systems
  • Parameter estimation

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