Residual Models and Stochastic Realization in State-Space System Identification
(1998) 37th Conference on Decision and Control, 1998- Abstract
- This paper presents theory and algorithms for validation in system identification of state-space models from finite input-output sequences in a subspace model identification framework. Similar to the case of prediction-error identification, it is shown that 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/8516896
- author
- Johansson, Rolf LU ; Chou, C. T. ; Verhaegen, Michel and Robertsson, Anders LU
- organization
- publishing date
- 1998
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- residual models, stochastic realization, state-space system identification, finite input-output sequences, I/O sequences, subspace model identification, model decomposition, stochastic innovations model, Riccati equation, reduced-order stochastic
- host publication
- Proceedings of the 37th IEEE Conference on Decision and Control
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 37th Conference on Decision and Control, 1998
- conference location
- Tampa, Florida, United States
- conference dates
- 1998-12-18 - 1998-12-18
- external identifiers
-
- scopus:0032269936
- DOI
- 10.1109/CDC.1998.758237
- language
- English
- LU publication?
- yes
- id
- 6d5208c5-c4cc-4989-ac1f-e96ea60d57b3 (old id 8516896)
- date added to LUP
- 2016-04-04 12:50:06
- date last changed
- 2022-01-31 18:41:26
@inproceedings{6d5208c5-c4cc-4989-ac1f-e96ea60d57b3, abstract = {{This paper presents theory and algorithms for validation in system identification of state-space models from finite input-output sequences in a subspace model identification framework. Similar to the case of prediction-error identification, it is shown that 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 Chou, C. T. and Verhaegen, Michel and Robertsson, Anders}}, booktitle = {{Proceedings of the 37th IEEE Conference on Decision and Control}}, keywords = {{residual models; stochastic realization; state-space system identification; finite input-output sequences; I/O sequences; subspace model identification; model decomposition; stochastic innovations model; Riccati equation; reduced-order stochastic}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Residual Models and Stochastic Realization in State-Space System Identification}}, url = {{http://dx.doi.org/10.1109/CDC.1998.758237}}, doi = {{10.1109/CDC.1998.758237}}, year = {{1998}}, }