Innovation generation in the presence of unknown inputs : application to robust failure detection

Abstract : The first step in innovations-based failure detection is the construction of an innovations generator, i.e., a filter which, in the absence of failures, from the inputs and the outputs of the system, generates a zero-mean white process with known covariance called innovations. Decision on whether a failure has occurred is then made by monitoring and applying statistical tests to this innovations process. In this paper, we present a method for constructing innovations in the case where the model contains unknown inputs and disturbances. Our solution is complete in the sense that it covers all "singular" cases.
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Rapport
[Research Report] RR-1914, INRIA. 1993
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https://hal.inria.fr/inria-00074759
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Soumis le : mercredi 24 mai 2006 - 16:14:55
Dernière modification le : vendredi 25 mai 2018 - 12:02:05
Document(s) archivé(s) le : mardi 12 avril 2011 - 19:05:42

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Ramine Nikoukhah. Innovation generation in the presence of unknown inputs : application to robust failure detection. [Research Report] RR-1914, INRIA. 1993. 〈inria-00074759〉

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