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AuthorDaroogheh, Najmeh
AuthorMeskin, Nader
AuthorKhorasani, Khorasani
Available date2016-06-12T10:03:42Z
Publication Date2014
Publication NameProceedings of the 53rd IEEE Conference on Decision and Control
CitationN. Daroogheh, N. Meskin and K. Khorasani, "Robust Hybrid EKF approach for state estimation in multi-scale nonlinear singularly perturbed systems," 53rd IEEE Conference on Decision and Control, Los Angeles, CA, 2014, pp. 1047-1054.
AbstractIn this paper a general framework is developed for state estimation in a class of nonlinear continuous-time singularly perturbed systems. Our approach is based on the hybrid extended Kalman filter in which observations are originated from discrete measurements. The developed framework is also extended to include linearization error in the observation equation as uncertainty in the estimation filter design. The boundedness of both a priori and a posteriori estimation error covariance matrices is considered as a criterion for the algorithm to have bounded estimation errors. As an approximation method for the estimation covariance matrices in the singularly perturbed system, the matched asymptotic series method is utilized to include the effects of initial conditions by approximating the boundary layer solution in order to attain more accurate filter gain approximation. The developed Hybrid Robust EKF (HREKF) strategy can be used as an estimation method for tracking the effects of hidden damage in a nonlinear system.
SponsorNPRP grant No. 4-195-2-065 from the Qatar National Research Fund (a member of Qatar Foundation).
SubjectKalman filters
Subjectapproximation theory
Subjectcontinuous time systems
Subjectcovariance matrices
Subjectnonlinear filters
Subjectnonlinear systems
Subjectsingularly perturbed systems
Subjectstate estimation
TitleRobust Hybrid EKF approach for state estimation in multi-scale nonlinear singularly perturbed systems
TypeConference Paper

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