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.
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/