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Effect of model uncertainty on failure detection - The threshold selectorThe performance of all failure detection, isolation, and accomodation (DIA) algorithms is influenced by the presence of model uncertainty. A unique framework is presented to incorporate a knowledge of modeling error in the analysis and design of failure detection systems. The tools being used are very similar to those in robust control theory. A concept is introduced called the threshold selector, which is a nonlinear inequality whose solution defines the set of detectable sensor failure signals. The threshold selector represents an innovative tool for analysis and synthesis of DIA algorithms. It identifies the optimal threshold to be used in innovations-based DIA algorithms. The optimal threshold is shown to be a function of the bound on modeling errors, the noise properties, the speed of DIA filters, and the classes of reference and failure signals. The size of the smallest detectable failure is also determined. The results are applied to a multivariable turbofan jet engine example, which demonstrates improvements compared to previous studies.
Document ID
19890030594
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Emami-Naeini, Abbas
(Systems Control Technology, Inc. Palo Alto, CA, United States)
Akhter, Muhammad M.
(Systems Control Technology, Inc. Palo Alto, CA, United States)
Rock, Stephen M.
(Systems Control Technology, Inc. Palo Alto, CA, United States)
Date Acquired
August 14, 2013
Publication Date
December 1, 1988
Publication Information
Publication: IEEE Transactions on Automatic Control
Volume: 33
ISSN: 0018-9286
Subject Category
Cybernetics
Accession Number
89A17965
Funding Number(s)
CONTRACT_GRANT: NAS3-24079
Distribution Limits
Public
Copyright
Other

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