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Stochastic Theory of Continuous-Time State-Space Identification

Johansson, Rolf LU orcid ; Verhaegen, Michel and Chou, C. T. (1999) In IEEE Transactions on Signal Processing 47(1). p.41-51
Abstract
This paper presents theory, algorithms, and validation results for system identification of continuous-time state-space models from finite input-output sequences. The algorithms developed are methods of subspace model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output model and a stochastic innovations model. Using the Riccati equation, we have designed a procedure to provide a reduced-order stochastic model that is minimal with respect to system order as well as the number of stochastic inputs, thereby avoiding several problems appearing in standard application of stochastic realization to the model validation problem.
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
IEEE Transactions on Signal Processing
volume
47
issue
1
pages
41 - 51
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:0032733686
ISSN
1053-587X
DOI
10.1109/78.738238
language
English
LU publication?
yes
id
cb7bcf0b-33e1-45c3-824a-e6a7bce3dbd0 (old id 8497068)
date added to LUP
2016-04-04 13:31:07
date last changed
2022-04-24 03:10:36
@article{cb7bcf0b-33e1-45c3-824a-e6a7bce3dbd0,
  abstract     = {{This paper presents theory, algorithms, and validation results for system identification of continuous-time state-space models from finite input-output sequences. The algorithms developed are methods of subspace model identification and stochastic realization adapted to the continuous-time context. The resulting model can be decomposed into an input-output model and a stochastic innovations model. Using the Riccati equation, we have designed a procedure to provide a reduced-order stochastic model that is minimal with respect to system order as well as the number of stochastic inputs, thereby avoiding several problems appearing in standard application of stochastic realization to the model validation problem.}},
  author       = {{Johansson, Rolf and Verhaegen, Michel and Chou, C. T.}},
  issn         = {{1053-587X}},
  language     = {{eng}},
  number       = {{1}},
  pages        = {{41--51}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Signal Processing}},
  title        = {{Stochastic Theory of Continuous-Time State-Space Identification}},
  url          = {{https://lup.lub.lu.se/search/files/6139652/8498195.pdf}},
  doi          = {{10.1109/78.738238}},
  volume       = {{47}},
  year         = {{1999}},
}