Identification of continuous-time state-space models from non-uniform fast-sampled data

Title: Identification of continuous-time state-space models from non-uniform fast-sampled data
Creator: Yuz, J. I.; Alfaro, J.; Agüero, J. C.; Goodwin, G. C.
Relation: IET Control Theory and Applications Vol. 5, Issue 7, p. 842-855
Publisher Link: http://dx.doi.org/10.1049/iet-cta.2010.0246
Publisher: The Institution of Engineering and Technology
Resource Type: journal article
Date: 2011
Description: In this study, we apply the expectation-maximisation (EM) algorithm to identify continuous-time state-space models from non-uniformly fast-sampled data. The sampling intervals are assumed to be small and uniformly bounded. The authors use a parameterisation of the sampled-data model in incremental form in order to modify the standard formulation of the EM algorithm for discrete-time models. The parameters of the incremental model converge to the parameter of the continuous-time system description as the sampling period goes to zero. The benefits of the proposed algorithm are successfully demonstrated via simulation studies.
Subject: state-space methods; expectation-maximisation algorithm; discrete time systems
Identifier: http://hdl.handle.net/1959.13/1065853
Identifier: uon:17964
Identifier: ISSN:1751-8644
Language: eng
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