Stochastic Theory of Continuous-Time State-Space Identification
(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:
https://lup.lub.lu.se/record/8497068
- author
- Johansson, Rolf LU ; Verhaegen, Michel and Chou, C. T.
- organization
- publishing date
- 1999
- 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}}, }