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Variance-Reduced Particle Filters for Structural System Identification Problems

Chowdhury, Roy S and Roy, D and Vasu, R M (2013) Variance-Reduced Particle Filters for Structural System Identification Problems. In: JOURNAL OF ENGINEERING MECHANICS-ASCE, 139 (2). pp. 210-218.

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Official URL: http://dx.doi.org/10.1061/(ASCE)EM.1943-7889.00004...


A few variance reduction schemes are proposed within the broad framework of a particle filter as applied to the problem of structural system identification. Whereas the first scheme uses a directional descent step, possibly of the Newton or quasi-Newton type, within the prediction stage of the filter, the second relies on replacing the more conventional Monte Carlo simulation involving pseudorandom sequence with one using quasi-random sequences along with a Brownian bridge discretization while representing the process noise terms. As evidenced through the derivations and subsequent numerical work on the identification of a shear frame, the combined effect of the proposed approaches in yielding variance-reduced estimates of the model parameters appears to be quite noticeable. DOI: 10.1061/(ASCE)EM.1943-7889.0000480. (C) 2013 American Society of Civil Engineers.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the ASCE-AMER SOC CIVIL ENGINEERS, 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400 USA
Keywords: Directed bootstrap filter; Gain-based direction; Quasi-Newton direction; Quasi-Monte Carlo simulations; Structural system identification
Department/Centre: Division of Mechanical Sciences > Civil Engineering
Division of Physical & Mathematical Sciences > Instrumentation Appiled Physics
Date Deposited: 19 Jul 2016 09:52
Last Modified: 19 Jul 2016 09:52
URI: http://eprints.iisc.ac.in/id/eprint/54189

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