Simultaneous state and input estimation with partial information on the inputs

Jinya Su, Baibing Li*, Wen Hua Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This paper investigates the problem of simultaneous state and input estimation (SSIE) 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 inputs. 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 interest, and an extension of the 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.

Original languageEnglish
Pages (from-to)445-452
Number of pages8
JournalSystems Science and Control Engineering
Issue number1
Early online date26 Aug 2015
Publication statusPublished - 11 Sept 2015

Bibliographical note

Funding Information:
This work was jointly funded by UK Engineering and Physical Sciences Research Council (EPSRC) and BAE System (EP/H501401/1).

Publisher Copyright:
© 2015 The Author(s). Published by Taylor & Francis.


  • Bayesian inference
  • partial information
  • state filter
  • unknown input filter


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