Continuous-Time Model Identification and State Estimation Using Non-Uniformly Sampled Data
Johansson, Rolf LU
(2009)
15th IFAC Symposium on System Identification
- Abstract
- This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite non-uniformly sampled input-output sequences. The algorithms developed are methods of model identification and stochastic realization adapted to the continuous-time model context using non-uniformly sampled input-output data. The resulting model can be decomposed into an input-output model and a stochastic innovations model. For state estimation dynamics, we have designed a procedure to provide separate continuous-time temporal update and error-feedback update based on non-uniformly sampled input-output data. Stochastic onvergence analysis is provided.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1454699
- author
- Johansson, Rolf
LU
- organization
- publishing date
- 2009
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proc. 15th IFAC Symposium on System Identification (SYSID2009)
- conference name
- 15th IFAC Symposium on System Identification
- conference location
- Saint-Malo, France
- conference dates
- 2009-06-06 - 2009-06-08
- external identifiers
-
- scopus:80051615555
- language
- English
- LU publication?
- yes
- id
- 43ea6156-036c-47ca-adb4-818582f888aa (old id 1454699)
- date added to LUP
- 2016-04-04 13:05:51
- date last changed
- 2022-02-15 18:04:23
@inproceedings{43ea6156-036c-47ca-adb4-818582f888aa,
abstract = {{This paper presents theory, algorithms and validation results for system identification of continuous-time state-space models from finite non-uniformly sampled input-output sequences. The algorithms developed are methods of model identification and stochastic realization adapted to the continuous-time model context using non-uniformly sampled input-output data. The resulting model can be decomposed into an input-output model and a stochastic innovations model. For state estimation dynamics, we have designed a procedure to provide separate continuous-time temporal update and error-feedback update based on non-uniformly sampled input-output data. Stochastic onvergence analysis is provided.}},
author = {{Johansson, Rolf}},
booktitle = {{Proc. 15th IFAC Symposium on System Identification (SYSID2009)}},
language = {{eng}},
title = {{Continuous-Time Model Identification and State Estimation Using Non-Uniformly Sampled Data}},
url = {{https://lup.lub.lu.se/search/files/62894316/8146063.pdf}},
year = {{2009}},
}