Proceedings of the 2015 International Conference on Test, Measurement and Computational Methods

Steady-State Kalman Estimator for Descriptor Systems with Colored Noise

Authors
Yan Xu, Guosheng Zhang
Corresponding Author
Yan Xu
Available Online November 2015.
DOI
https://doi.org/10.2991/tmcm-15.2015.22How to use a DOI?
Keywords
escriptor systems; colored noise; steady-state Kalman estimator; global asymptoticstability
Abstract
Using the modern time series analysis method in the time domain, based on the ARMAinnovation model, a steady-state Kalman estimator for descriptor systems with colored noise is introduced,and employing the state observer principle, the pole-assignment descriptor steady-state Kalman estimator is also presented. They have global asymptotic stability and can handle the filtering, smoothing and prediction problems in unified frameworks, thus avoiding the solution of the Riccatiequations.
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Proceedings
2015 International Conference on Test, Measurement and Computational Methods
Part of series
Advances in Computer Science Research
Publication Date
November 2015
ISBN
978-94-6252-132-2
ISSN
2352-538X
DOI
https://doi.org/10.2991/tmcm-15.2015.22How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yan Xu
AU  - Guosheng Zhang
PY  - 2015/11
DA  - 2015/11
TI  - Steady-State Kalman Estimator for Descriptor Systems with Colored Noise
BT  - 2015 International Conference on Test, Measurement and Computational Methods
PB  - Atlantis Press
SP  - 87
EP  - 90
SN  - 2352-538X
UR  - https://doi.org/10.2991/tmcm-15.2015.22
DO  - https://doi.org/10.2991/tmcm-15.2015.22
ID  - Xu2015/11
ER  -