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Title: Simultaneous state and input estimation with partial information on the inputs
Authors: Su, Jinya
Li, Baibing
Chen, Wen-Hua
Keywords: Bayesian inference
Partial information
State filter
Unknown input filter
Issue Date: 2015
Publisher: © The Authors. Published by Taylor and Francis
Citation: SU, J., LI, B. and CHEN, W-H., 2015. Simultaneous state and input estimation with partial information on the inputs. Systems Science & Control Engineering, 3(1), pp. 445-452.
Abstract: This paper investigates the problem of simultaneous state and input estimation for discrete-time linear stochastic systems when the information on the inputs is partially available. To incorporate the partial information on the inputs, matrix manipulation is used to obtain an equivalent system with reduced-order in puts. Then Bayesian inference is drawn to obtain a recursive filter for both state and input variables. The proposed filter is an extension of the recently developed state filter with partially observed inputs to the case where the input filter is also of in terest, and an extension of the Simultaneous State and Input Estimation (SSIE) to the case where the information on the inputs is partially available. A numerical example is given to illustrate the proposed method. It is shown that, due to the additional information on the inputs being incorporated in the filter design, the performances of both state and input estimation are substantially improved in comparison with the conventional SSIE without partial input information.
Description: This is an Open Access Article. It is published by Taylor and Francis 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/
Version: Published
DOI: 10.1080/21642583.2015.1082512
URI: https://dspace.lboro.ac.uk/2134/21205
Publisher Link: http://dx.doi.org/10.1080/21642583.2015.1082512
Appears in Collections:Published Articles (Aeronautical and Automotive Engineering)
Published Articles (Business School)

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