Robust Fault Detection of Linear Systems using a Computationally Efficient Set-membership Method

Seyed Mojtaba Tabatabaeipour, Thomas Bak

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

In this paper, a new computationally efficient
set-membership method for robust fault detection of linear
systems is proposed. The method computes an interval
outer-approximation of the output of the system that is
consistent with the model, the bounds on noise and
disturbance, and the past measurements. If the output of
the system does not belong to this interval, a fault is
detected. To compute the output interval, we propose using
support functions. Only two support functions for each
output must be computed which results in a computationally
efficient algorithm. Moreover, the method is trivially
parallelizable. The method is demonstrated for fault
detection of a hydraulic pitch actuator of a wind turbine.
We show the effectiveness of the proposed method by
comparing our results with two zonotope-based
set-membership methods.
Original languageEnglish
Title of host publicationControl Applications (CCA), 2014 IEEE Conference on
Number of pages6
PublisherIEEE Press
Publication date2014
Pages358-363
ISBN (Print)978-1-4799-7408-5
DOIs
Publication statusPublished - 2014
Event2014 IEEE Conference on Control Applications - Juan Les Antibes, France
Duration: 8 Oct 201410 Oct 2014
Conference number: 35444

Conference

Conference2014 IEEE Conference on Control Applications
Number35444
CountryFrance
CityJuan Les Antibes
Period08/10/201410/10/2014
SeriesI E E E International Conference on Control Applications. Proceedings
ISSN1085-1992

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    Tabatabaeipour, S. M., & Bak, T. (2014). Robust Fault Detection of Linear Systems using a Computationally Efficient Set-membership Method. In Control Applications (CCA), 2014 IEEE Conference on (pp. 358-363). IEEE Press. I E E E International Conference on Control Applications. Proceedings https://doi.org/10.1109/CCA.2014.6981372