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Self-calibrating Bayesian real-time system identification
Ka-Veng Yuen1; Sin-Chi Kuok1,2; Le Dong1
2019-03-06
Source PublicationComputer-Aided Civil and Infrastructure Engineering
ISSN1093-9687
Volume34Issue:9Pages:806-821
Abstract

In this article, a novel Bayesian framework is proposed for real-time system identification with calibratable model classes. This self-calibrating scheme adaptively reconfigures the model classes to achieve reliable real-time estimation for the system state and model parameters. At each time step, the plausibilities of the model classes are computed and they serve as the cue for calibration. Once calibration is triggered, all model classes will be reconfigured. Thereafter, identification will continue to propagate with the calibrated model classes until the next recalibration. Consequently, the model classes will evolve and their deficiencies can be corrected adaptively. This remarkable feature of the proposed framework stimulates the accessibility of reliable real-time system identification. Examples are presented to demonstrate the efficacy of the proposed approach using noisy response measurement of linear and nonlinear time-varying dynamical systems under stationary condition.

DOI10.1111/mice.12441
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Construction & Building Technology ; Engineering ; Transportation
WOS SubjectComputer Science, Interdisciplinary Applications ; Construction & Building Technology ; Engineering, Civil ; Transportation Science & Technology
WOS IDWOS:000478734200006
PublisherWILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ
Scopus ID2-s2.0-85062517791
Fulltext Access
FWCI2.3731065
Citation statistics
Document TypeJournal article
CollectionFaculty of Science and Technology
DEPARTMENT OF CIVIL AND ENVIRONMENTAL ENGINEERING
Corresponding AuthorKa-Veng Yuen
Affiliation1.Department of Civil and Environmental Engineering,University of Macau,Macau,China
2.Department of Engineering Science,University of Oxford,Oxford,United Kingdom
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ka-Veng Yuen,Sin-Chi Kuok,Le Dong. Self-calibrating Bayesian real-time system identification[J]. Computer-Aided Civil and Infrastructure Engineering,2019,34(9):806-821.
APA Ka-Veng Yuen,Sin-Chi Kuok,&Le Dong.(2019).Self-calibrating Bayesian real-time system identification.Computer-Aided Civil and Infrastructure Engineering,34(9),806-821.
MLA Ka-Veng Yuen,et al."Self-calibrating Bayesian real-time system identification".Computer-Aided Civil and Infrastructure Engineering 34.9(2019):806-821.
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