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Title: Fault detection and isolation filter design for systems subject to polytopic uncertainties
Authors: Mazars, E.
Jaimoukha, I.M.
Li, Zhenhai
Zolotas, Argyrios C.
Issue Date: 2007
Publisher: © IEEE
Citation: MAZARS, E. ... et al, 2007. Fault detection and isolation filter design for systems subject to polytopic uncertainties. IN: Proceedings, IEEE Mediterranean Conference on Control & Automation. MED '07, 27-29 June 2007, pp. 1-5
Abstract: This paper considers the robust fault detection and isolation (FDI) problem for linear time-invariant dynamic systems subject to faults, disturbances and polytopic uncertainties. We employ an observer-based FDI filter to generate a residual signal. We propose a cost function that penalizes a weighted combination of the deviation of the fault to residual dynamics from a given fault isolation reference model, as well as the effects of disturbances and uncertainties on the residual, using the Hinfin norm as a measure. The proposed cost function thus captures the requirements of fault detection and isolation and disturbance rejection in the presence of polytopic uncertainties. We derive necessary and sufficient conditions for the existence of an FDI filter that achieves the design specifications. This condition takes the form of easily implementable linear matrix inequality (LMI) optimization problem.
Description: This is a conference paper [© IEEE]. It is also available from: http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=4433643. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Version: Published
DOI: 10.1109/MED.2007.4433710
URI: https://dspace.lboro.ac.uk/2134/4300
ISBN: 9781424412815
Appears in Collections:Conference Papers (Control Systems Group)
Conference Papers and Contributions (Mechanical, Electrical and Manufacturing Engineering)

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