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dc.contributor.authorYin, YanYan
dc.contributor.authorShi, P.
dc.contributor.authorLiu, F.
dc.contributor.authorPan, J.
dc.date.accessioned2017-04-28T13:58:39Z
dc.date.available2017-04-28T13:58:39Z
dc.date.created2017-04-28T09:06:14Z
dc.date.issued2012
dc.identifier.citationYin, Y. and Shi, P. and Liu, F. and Pan, J. 2012. Gain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates. Nonlinear Analysis: Real World Applications. 13 (1): pp. 359-369.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/52409
dc.identifier.doi10.1016/j.nonrwa.2011.07.043
dc.description.abstract

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.

dc.publisherPergamon, Elsevier Ltd
dc.titleGain-scheduled fault detection on stochastic nonlinear systems with partially known transition jump rates
dc.typeJournal Article
dcterms.source.volume13
dcterms.source.number1
dcterms.source.startPage359
dcterms.source.endPage369
dcterms.source.issn1468-1218
dcterms.source.titleNonlinear Analysis: Real World Applications
curtin.departmentDepartment of Mathematics and Statistics
curtin.accessStatusFulltext not available


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