Delay-dependent robust fault detection for Markovian jump systems with partly unknown transition rates
dc.contributor.author | Chen, F. | |
dc.contributor.author | Yin, YanYan | |
dc.contributor.author | Liu, F. | |
dc.date.accessioned | 2018-01-30T08:03:40Z | |
dc.date.available | 2018-01-30T08:03:40Z | |
dc.date.created | 2018-01-30T05:59:17Z | |
dc.date.issued | 2016 | |
dc.identifier.citation | Chen, F. and Yin, Y. and Liu, F. 2016. Delay-dependent robust fault detection for Markovian jump systems with partly unknown transition rates. Journal of the Franklin Institute. 353 (2): pp. 426-447. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/61111 | |
dc.identifier.doi | 10.1016/j.jfranklin.2015.12.001 | |
dc.description.abstract |
This paper focuses on delay-dependent robust fault detection (RFD) problem for continuous-time Markovian jump systems (MJSs) with partly unknown transition rates and time-varying delay. Free-connection weighting matrices are firstly addressed to robust fault detection filter design, which reduce the conservatism caused by fixed-connection weighting matrices. By considering Lyapunov stability theory, new delay-dependent stochastic stability criteria are eatablished in terms of linear matrix inequalities (LMIs). Based on this, sufficient conditions are given and proved to guarantee the existence of the robust fault detection filter system. Furthermore, an optimization design approach is derived with an improved cone complementarity linearization algorithm. Finally, a simulation example is given to show that the designed robust fault detection filter can detect the faults sensitively, and also respond robustly to unknown disturbances. | |
dc.publisher | Elsevier | |
dc.title | Delay-dependent robust fault detection for Markovian jump systems with partly unknown transition rates | |
dc.type | Journal Article | |
dcterms.source.volume | 353 | |
dcterms.source.number | 2 | |
dcterms.source.startPage | 426 | |
dcterms.source.endPage | 447 | |
dcterms.source.issn | 0016-0032 | |
dcterms.source.title | Journal of the Franklin Institute | |
curtin.department | School of Electrical Engineering, Computing and Mathematical Science (EECMS) | |
curtin.accessStatus | Fulltext not available |
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