Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation

This paper focuses on determining the limit state exceeding probability of a deteriorating model using optimal and sub-optimal Bayesian algorithms. Specifically the Kalman filter (for a linear system), extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation (for non...

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Main Authors:	Garciano, Lessandro Estelito O., Yoshida, Ikumasa
Format:	text
Published:	Animo Repository 2011
Subjects:	Kalman filtering Monte Carlo method Structural analysis (Engineering) Structural analysis (Engineering)—Approximation methods Civil Engineering Construction Engineering and Management
Online Access:	https://animorepository.dlsu.edu.ph/faculty_research/6033
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Institution:	De La Salle University

id	oai:animorepository.dlsu.edu.ph:faculty_research-6716
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spelling	oai:animorepository.dlsu.edu.ph:faculty_research-67162022-06-02T01:47:27Z Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation Garciano, Lessandro Estelito O. Yoshida, Ikumasa This paper focuses on determining the limit state exceeding probability of a deteriorating model using optimal and sub-optimal Bayesian algorithms. Specifically the Kalman filter (for a linear system), extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation (for non-linear systems) are used to approximate the present state of a deteriorating system given measurements tainted with noise of the system output. In addition to the comprehensive discussion of the theory, numerical implementation and comparison of the results through numerical examples are shown. 2011-09-01T07:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/6033 Faculty Research Work Animo Repository Kalman filtering Monte Carlo method Structural analysis (Engineering) Structural analysis (Engineering)—Approximation methods Civil Engineering Construction Engineering and Management
institution	De La Salle University
building	De La Salle University Library
continent	Asia
country	Philippines Philippines
content_provider	De La Salle University Library
collection	DLSU Institutional Repository
topic	Kalman filtering Monte Carlo method Structural analysis (Engineering) Structural analysis (Engineering)—Approximation methods Civil Engineering Construction Engineering and Management
spellingShingle	Kalman filtering Monte Carlo method Structural analysis (Engineering) Structural analysis (Engineering)—Approximation methods Civil Engineering Construction Engineering and Management Garciano, Lessandro Estelito O. Yoshida, Ikumasa Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
description	This paper focuses on determining the limit state exceeding probability of a deteriorating model using optimal and sub-optimal Bayesian algorithms. Specifically the Kalman filter (for a linear system), extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation (for non-linear systems) are used to approximate the present state of a deteriorating system given measurements tainted with noise of the system output. In addition to the comprehensive discussion of the theory, numerical implementation and comparison of the results through numerical examples are shown.
format	text
author	Garciano, Lessandro Estelito O. Yoshida, Ikumasa
author_facet	Garciano, Lessandro Estelito O. Yoshida, Ikumasa
author_sort	Garciano, Lessandro Estelito O.
title	Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_short	Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_full	Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_fullStr	Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_full_unstemmed	Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation
title_sort	estimating the limit state exceeding probability of a deteriorating structure using the kalman filter, extended kalman filter, unscented kalman filter and the sequential monte carlo simulation
publisher	Animo Repository
publishDate	2011
url	https://animorepository.dlsu.edu.ph/faculty_research/6033
_version_	1767196413270163456

Estimating the limit state exceeding probability of a deteriorating structure using the Kalman filter, extended Kalman filter, unscented Kalman filter and the sequential Monte Carlo simulation

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