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Simultaneous state and input estimation with partial information on the inputs
journal contributionposted on 2016-05-12, 13:26 authored by Jinya Su, Baibing LiBaibing Li, Wen-Hua ChenWen-Hua Chen
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.
- Business and Economics
Published inSystems Science & Control Engineering
Pages445 - 452
CitationSU, 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.
Publisher© The Authors. Published by Taylor and Francis
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Publisher statementThis 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/
NotesThis 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/