Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates

In this paper, the problem of continuous gain-scheduled fault detection (FD) is studied for a class of stochastic nonlinear systems which possesses partially known jump rates. Initially, by using gradient linearization approach, the nonlinear stochastic system is described by a series of linear jump...

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Main Authors: Yin, YanYan, Shi, P., Liu, F., Pan, J.
Format: Journal Article
Published: Pergamon, Elsevier Ltd 2012
Online Access:http://hdl.handle.net/20.500.11937/52409
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author Yin, YanYan
Shi, P.
Liu, F.
Pan, J.
author_facet Yin, YanYan
Shi, P.
Liu, F.
Pan, J.
author_sort Yin, YanYan
building Curtin Institutional Repository
collection Online Access
description In this paper, the problem of continuous gain-scheduled fault detection (FD) is studied for a class of stochastic nonlinear systems which possesses partially known jump rates. Initially, by using gradient linearization approach, the nonlinear stochastic system is described by a series of linear jump models at some selected working points. Subsequently, observer-based residual generator is constructed for each jump linear system. Then, a new observer-design method is proposed for each re-constructed system to design H8 observers that minimize the influences of the disturbances, and to formulate a new performance index that increase the sensitivity to faults. Finally, continuous gain-scheduled approach is employed to design continuous FD observers on the whole nonlinear stochastic system. Simulation example is given to show the effectiveness and potential of the developed techniques. © 2011 Elsevier Ltd. All rights reserved.
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institution Curtin University Malaysia
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publishDate 2012
publisher Pergamon, Elsevier Ltd
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spelling curtin-20.500.11937-524092017-09-13T15:39:22Z Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates Yin, YanYan Shi, P. Liu, F. Pan, J. In this paper, the problem of continuous gain-scheduled fault detection (FD) is studied for a class of stochastic nonlinear systems which possesses partially known jump rates. Initially, by using gradient linearization approach, the nonlinear stochastic system is described by a series of linear jump models at some selected working points. Subsequently, observer-based residual generator is constructed for each jump linear system. Then, a new observer-design method is proposed for each re-constructed system to design H8 observers that minimize the influences of the disturbances, and to formulate a new performance index that increase the sensitivity to faults. Finally, continuous gain-scheduled approach is employed to design continuous FD observers on the whole nonlinear stochastic system. Simulation example is given to show the effectiveness and potential of the developed techniques. © 2011 Elsevier Ltd. All rights reserved. 2012 Journal Article http://hdl.handle.net/20.500.11937/52409 10.1016/j.nonrwa.2011.07.043 Pergamon, Elsevier Ltd restricted
spellingShingle Yin, YanYan
Shi, P.
Liu, F.
Pan, J.
Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
title Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
title_full Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
title_fullStr Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
title_full_unstemmed Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
title_short Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
title_sort gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
url http://hdl.handle.net/20.500.11937/52409