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Title: On existence, optimality and asymptotic stability of the Kalman filter with partially observed inputs
Authors: Su, Jinya
Li, Baibing
Chen, Wen-Hua
Keywords: Asymptotic stability
Existence
Kalman filter
Optimality
Unknown inputs
Issue Date: 2015
Publisher: Elsevier / © The Authors
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.
Abstract: 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.
Description: 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/
Sponsor: This work was jointly funded by UK Engineering and Physical Sciences Research Council (EPSRC) [grant number EP/H501401/1] and BAE Systems.
Version: Published
DOI: 10.1016/j.automatica.2014.12.044
URI: https://dspace.lboro.ac.uk/2134/17019
Publisher Link: http://dx.doi.org/10.1016/j.automatica.2014.12.044
ISSN: 0005-1098
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)

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