Robust model matching for geometric fault detection filters

Peter Seiler, József Bokor, Balint Vanek, Gary J. Balas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Geometric fault detection and isolation filters are known for having excellent fault isolation properties. However, they are generally assumed to be sensitive to model uncertainty and noise. This paper proposes a robust model matching method to incorporate model uncertainty into the design of geometric fault detection filters. Several existing methods for robust filter synthesis are described to solve the robust model matching problem. It is then shown that the robust model matching problem has an interesting self-optimality property for multiplicative input uncertainty models. Finally, a simple example is presented to study the effect of parametric uncertainty and unmodeled dynamics on the performance of a geometric filter.

Original languageEnglish
Title of host publicationProceedings of the 2011 American Control Conference, ACC 2011
Pages226-231
Number of pages6
Publication statusPublished - Sep 29 2011
Event2011 American Control Conference, ACC 2011 - San Francisco, CA, United States
Duration: Jun 29 2011Jul 1 2011

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2011 American Control Conference, ACC 2011
CountryUnited States
CitySan Francisco, CA
Period6/29/117/1/11

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Seiler, P., Bokor, J., Vanek, B., & Balas, G. J. (2011). Robust model matching for geometric fault detection filters. In Proceedings of the 2011 American Control Conference, ACC 2011 (pp. 226-231). [5991249] (Proceedings of the American Control Conference).