Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities

© 2016 ISSN.A robust fault detection observer (RFDO) is designed to solve the robust fault detection problem of the nonlinear Markovian jump systems (NMJSs) with partly unknown transition probabilities. With the method of T-S fuzzy linearization, the original NMJSs are described as a set of local li...

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Main Authors: Shi, J., Yin, YanYan, Liu, F.
Format: Journal Article
Published: ICIC International 2016
Online Access:http://hdl.handle.net/20.500.11937/63111
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author Shi, J.
Yin, YanYan
Liu, F.
author_facet Shi, J.
Yin, YanYan
Liu, F.
author_sort Shi, J.
building Curtin Institutional Repository
collection Online Access
description © 2016 ISSN.A robust fault detection observer (RFDO) is designed to solve the robust fault detection problem of the nonlinear Markovian jump systems (NMJSs) with partly unknown transition probabilities. With the method of T-S fuzzy linearization, the original NMJSs are described as a set of local linear models. On this basis, free-connection weighting matrices are introduced to RFDO. A series of linear matrix inequalities which ensure the stochastic asymptotic stability of the system are obtained by using the constructed Lyapunov function. Furthermore, the design problem is formulated as a two-objective optimization algorithm. A simulation example is given to show that the designed RFDO can not only detect the fault sensitively, but have the robustness to unknown disturbances.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T10:24:40Z
publishDate 2016
publisher ICIC International
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-631112018-02-06T06:15:18Z Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities Shi, J. Yin, YanYan Liu, F. © 2016 ISSN.A robust fault detection observer (RFDO) is designed to solve the robust fault detection problem of the nonlinear Markovian jump systems (NMJSs) with partly unknown transition probabilities. With the method of T-S fuzzy linearization, the original NMJSs are described as a set of local linear models. On this basis, free-connection weighting matrices are introduced to RFDO. A series of linear matrix inequalities which ensure the stochastic asymptotic stability of the system are obtained by using the constructed Lyapunov function. Furthermore, the design problem is formulated as a two-objective optimization algorithm. A simulation example is given to show that the designed RFDO can not only detect the fault sensitively, but have the robustness to unknown disturbances. 2016 Journal Article http://hdl.handle.net/20.500.11937/63111 ICIC International restricted
spellingShingle Shi, J.
Yin, YanYan
Liu, F.
Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
title Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
title_full Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
title_fullStr Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
title_full_unstemmed Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
title_short Robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
title_sort robust fault detection of nonlinear markovian jump systems with partly unknown transition probabilities
url http://hdl.handle.net/20.500.11937/63111