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On existence, optimality and asymptotic stability of the Kalman filter with partially observed inputs

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posted on 2015-03-16, 16:33 authored by Jinya Su, Baibing LiBaibing Li, Wen-Hua ChenWen-Hua Chen
For linear stochastic time-varying systems, we investigate the properties of the Kalman filter with partially observed inputs. We first establish the existence condition of a general linear filter when the unknown inputs are partially observed. Then we examine the optimality of the Kalman filter with partially observed inputs. Finally, on the basis of the established existence condition and optimality result, we investigate asymptotic stability of the filter for the corresponding time-invariant systems. It is shown that the results on existence and asymptotic stability obtained in this paper provide a unified approach to accommodating a variety of filtering scenarios as its special cases, including the classical Kalman filter and state estimation with unknown inputs.

Funding

This work was jointly funded by UK Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/H501401/1] and BAE Systems.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Automatica

Volume

53

Pages

149 - 154 (6)

Citation

SU, J., LI, B. and CHEN, W.-H., 2015. On existence, optimality and asymptotic stability of the Kalman filter with partially observed inputs. Automatica, 53, pp. 149 - 154.

Publisher

Elsevier / © The Authors

Version

  • VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/ by/4.0/

Acceptance date

2014-12-10

Publication date

2015-01-12

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

ISSN

0005-1098

Language

  • en

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