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Data Driven Fault Detection with Robustness to Uncertain Parameters Identified in Closed Loop
Delft University of Technology, The Netherlands.
Delft University of Technology, The Netherlands.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2010 (English)In: Proceedings of the 49th IEEE Conference on Decision and Control, 2010, 750-755 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a new robustified data-driven fault detection approach, connected to closed-loop subspace identification. Although data-driven detection methods have recently been reported in the literature, attention has not yet been given to a robust solution coping with identification errors. The key idea of this paper is to analytically quantify the effect of the identification errors on the residual generator of a new data-driven detection approach, namely FICSI. The comparisons of the proposed robust FICSI detection scheme with both its nominal counterpart and the nominal data-driven PSA solutions have verified the effectiveness of accounting the identification errors in improving the performance of the data-driven detection scheme.

Place, publisher, year, edition, pages
2010. 750-755 p.
Keyword [en]
Closed loop systems, Fault diagnosis, Identification
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-95580DOI: 10.1109/CDC.2010.5718040ISBN: 978-1-4244-7745-6 (print)OAI: oai:DiVA.org:liu-95580DiVA: diva2:636214
Conference
49th IEEE Conference on Decision and Control, Atlanta, GA, USA, 15-17 December, 2010
Available from: 2013-07-09 Created: 2013-07-09 Last updated: 2013-07-09

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Gustafsson, Fredrik

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Citation style
  • apa
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  • modern-language-association-8th-edition
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Language
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • asciidoc
  • rtf