Variance-Reduced Particle Filters for Structural System Identification Problems
Publication: Journal of Engineering Mechanics
Volume 139, Issue 2
Abstract
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.
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Published In
Journal of Engineering Mechanics
Volume 139 • Issue 2 • February 2013
Pages: 210 - 218
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Jan 22, 2012
Accepted: May 24, 2012
Published online: May 28, 2012
Published in print: Feb 1, 2013
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