Distributed sensor fault detection and isolation for nonlinear uncertain systems

Vasso Reppa*, Marios M. Polycarpou, Christos G. Panayiotou

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

7 Citations (Scopus)

Abstract

This paper presents a design methodology and some analytical results for distributed sensor fault detection and isolation (SFDI) of a class of nonlinear uncertain systems. The proposed architecture is based on the design of local SFDI modules, which monitor the healthy operation of a set of sensors and aim to detect the faults in this set, using a dedicated nonlinear observer scheme. The multiple sensor fault isolation procedure is further enhanced by deriving a combinatorial decision logic that processes information from local SFDI modules. The performance of the proposed diagnostic scheme is analyzed in terms of its robustness with respect to the modeling uncertainties and conditions for ensuring fault detectability and isolability.

Original languageEnglish
Title of host publication8th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2012
PublisherIFAC Secretariat
Pages1077-1082
Number of pages6
EditionPART 1
ISBN (Print)9783902823090
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event8th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2012 - Mexico City, Mexico
Duration: 29 Aug 201231 Aug 2012

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume8
ISSN (Print)1474-6670

Conference

Conference8th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS 2012
Country/TerritoryMexico
CityMexico City
Period29/08/1231/08/12

Keywords

  • Fault detection
  • Fault isolation
  • Nonlinear systems
  • Sensor faults
  • Uncertain dynamic systems

Fingerprint

Dive into the research topics of 'Distributed sensor fault detection and isolation for nonlinear uncertain systems'. Together they form a unique fingerprint.

Cite this