A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems

A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems

The work presented in this paper focuses on the design of robust Fault Detection and Isolation (FDI) filters for dynamic systems characterized by LPV (Linear Parameter Varying) polytopic models. A sufficient condition is established to guarantee sensitivity performance of the residual signal vector...

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Main Authors: Sylvain Grenaille, David Henry, Ali Zolghadri
Format: Article
Language:English
Published: Hindawi Limited 2008-01-01
Series:Journal of Control Science and Engineering
Online Access:http://dx.doi.org/10.1155/2008/231697
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spelling doaj-d2f5b9461624450bbbb67080818f4d712020-11-25T02:15:34ZengHindawi LimitedJournal of Control Science and Engineering1687-52491687-52572008-01-01200810.1155/2008/231697231697A Method for Designing Fault Diagnosis Filters for LPV Polytopic SystemsSylvain Grenaille0David Henry1Ali Zolghadri2Université Bordeaux 1, Approche Robuste et Intégrée de l'Automatique, Laboratory IMS, 351 Cours de la Libération, Talence Cedex 33405, FranceUniversité Bordeaux 1, Approche Robuste et Intégrée de l'Automatique, Laboratory IMS, 351 Cours de la Libération, Talence Cedex 33405, FranceUniversité Bordeaux 1, Approche Robuste et Intégrée de l'Automatique, Laboratory IMS, 351 Cours de la Libération, Talence Cedex 33405, FranceThe work presented in this paper focuses on the design of robust Fault Detection and Isolation (FDI) filters for dynamic systems characterized by LPV (Linear Parameter Varying) polytopic models. A sufficient condition is established to guarantee sensitivity performance of the residual signal vector to faults. Robustness constraints against model perturbations and disturbances are also taken into account in the design method. A key feature of the proposed method is that the residual structuring matrices are optimized as an integral part of the design, together with the dynamic part (i.e. the filter). The design problem is formulated as a convex optimization problem and solved using LMI (Linear Matrix Inequalities) techniques. The proposed method is illustrated on the secondary circuit of a Nuclear Power Plant.http://dx.doi.org/10.1155/2008/231697
collection DOAJ
language English
format Article
sources DOAJ
author Sylvain Grenaille
David Henry
Ali Zolghadri
spellingShingle Sylvain Grenaille
David Henry
Ali Zolghadri
A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems
Journal of Control Science and Engineering
author_facet Sylvain Grenaille
David Henry
Ali Zolghadri
author_sort Sylvain Grenaille
title A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems
title_short A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems
title_full A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems
title_fullStr A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems
title_full_unstemmed A Method for Designing Fault Diagnosis Filters for LPV Polytopic Systems
title_sort method for designing fault diagnosis filters for lpv polytopic systems
publisher Hindawi Limited
series Journal of Control Science and Engineering
issn 1687-5249
1687-5257
publishDate 2008-01-01
description The work presented in this paper focuses on the design of robust Fault Detection and Isolation (FDI) filters for dynamic systems characterized by LPV (Linear Parameter Varying) polytopic models. A sufficient condition is established to guarantee sensitivity performance of the residual signal vector to faults. Robustness constraints against model perturbations and disturbances are also taken into account in the design method. A key feature of the proposed method is that the residual structuring matrices are optimized as an integral part of the design, together with the dynamic part (i.e. the filter). The design problem is formulated as a convex optimization problem and solved using LMI (Linear Matrix Inequalities) techniques. The proposed method is illustrated on the secondary circuit of a Nuclear Power Plant.
url http://dx.doi.org/10.1155/2008/231697
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