Fault Detection and Model Identification in Linear Dynamical Systems

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dc.contributor.advisor S.L. Campbell, Chair en_US
dc.contributor.advisor R. Smith, Member en_US
dc.contributor.advisor K. Ito, Member en_US
dc.contributor.advisor H.T. Tran, Member en_US
dc.contributor.advisor E. Chukwu, Member en_US
dc.contributor.author Horton, Kirk Gerritt en_US
dc.date.accessioned 2010-04-02T18:28:40Z
dc.date.available 2010-04-02T18:28:40Z
dc.date.issued 2001-04-05 en_US
dc.identifier.other etd-20010403-112605 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/3288
dc.description.abstract Linear dynamical systems, Ex'+Fx=f(t), in which E is singular, are useful in a wide variety of applications. Because of this wide spread applicability, much research has been done recently to develop theory for the design of linear dynamical systems. A key aspect of system design is fault detection and isolation (FDI). One avenue of FDI is via the multi-model approach, in which the parameters of the nominal, unfailed model of the system are known, as well as the parameters of one or more fault models. The design goal is to obtain an indicator for when a fault has occurred, and, when more than one type is possible, which type of fault it is. A choice that must be made in the system design is how to model noise. One way is as a bounded energy signal. This approach places very few restrictions on the types of noisy systems which can be addressed, requiring no complex modeling requirement. This thesis applies the multi-model approach to FDI in linear dynamical systems, modeling noise as bounded energy signals. A complete algorithm is developed, requiring very little on-line computation, with which nearly perfect fault detection and isolation over a finite horizon is attained. The algorithm applies techniques to convert complex system relationships into necessary and sufficient conditions for the solutions to optimal control problems. The first such problem provides the fault indicator via the minimum energy detection signal, while the second problem provides for fault isolation via the separating hyperplane. The algorithm is implemented and tested on a suite of examples in commercial optimization software. The algorithm is shownto have promise in nonlinear problems, time varying problems, and certain types of linear problems for which existing theory is not suitable. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.title Fault Detection and Model Identification in Linear Dynamical Systems en_US
dc.degree.name PhD en_US
dc.degree.level PhD Dissertation en_US
dc.degree.discipline Operations Research en_US


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