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Fault detection under fuzzy model uncertainty

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Abstract

The paper tackles the problem of robust fault detection using Takagi-Sugeno fuzzy models. A model-based strategy is employed to generate residuals in order to make a decision about the state of the process. Unfortunately, such a method is corrupted by model uncertainty due to the fact that in real applications there exists a model-reality mismatch. In order to ensure reliable fault detection the adaptive threshold technique is used to deal with the mentioned problem. The paper focuses also on fuzzy model design procedure. The bounded-error approach is applied to generating the rules for the model using available measurements. The proposed approach is applied to fault detection in the DC laboratory engine.

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Authors and Affiliations

  1. Institute of Control and Computation Engineering, University of Zielona Góra, ul. Podgórna 50, 65-246, Zielona Góra, Poland

    Marek Kowal & Józef Korbicz

Authors
  1. Marek Kowal
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  2. Józef Korbicz
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Correspondence to Marek Kowal.

Additional information

Marek Kowal received his M.Sc. and Ph.D. degrees in electrical engineering from the University of Zielona Góra, Poland, in 2000 and 2004, respectively. In 2001 (3 months) he was with the Technical University of Lisbon, Portugal, as a research fellow. Currently, he is a assistant professor in the Institute of Control and Computation Engineering at the University of Zielona Góra, Poland.

He has published about 20 papers in refereed journal and conference papers. He is an author of one monograph and two book chapters. His current interests include technical and medical diagnostics, fuzzy and neuro-fuzzy modelling, image processing and pattern recognition.

Józef Korbicz received his M.Sc., Ph.D. and D.Sc. (doctor habilitatis) degrees in automatic control from the Kiev University of Technology, Ukraine in 1975, 1980 and 1986, respectively. He obtained his professorial title from the Institute of System Research of the Polish Academy of Sciences, Warsaw, in 1993. In 1991 (5 months) he was with the University of Colorado, USA, as an IREX research fellow, and then in 1994 (2 months) with the Universities of Duisburg and Wuppertal, Germany, as a DAAD research fellow. He has been a full-rank professor of automatic control at the University of Zielona Góra, Poland, since 1994. He currently heads the Institute of Control and Computation Engineering. In 1991 he founded the International Journal of Applied Mathematics and Computer Science (AMCS) and up to now he has been the Editor-in-Chief.

He has published more than 220 technical papers, 90 of them in international journals. He is an author or co-author of 9 monographs and text books and a co-editor of 3 books. His current research interests include computational intelligence, fault detection and isolation (FDI) and control theory.

Prof. Korbicz is a senior member of IEEE, a member of IFAC TC on SAFEPROCESS, as well as a member of the Automatics and Robotics Committee of the Polish Academy of Sciences in Warsaw. He was a chairman of the International Programme Committee of the 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, SAFEPROCESS, in Beijing, 2006.

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Kowal, M., Korbicz, J. Fault detection under fuzzy model uncertainty. Int J Automat Comput 4, 117–124 (2007). https://doi.org/10.1007/s11633-007-0117-1

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  • DOI: https://doi.org/10.1007/s11633-007-0117-1

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