Simultaneous input and state estimation for linear discrete-time stochastic systems with direct feedthrough

Sze Zheng Yong, Minghui Zhu, Emilio Frazzoli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

In this paper, we present an optimal filter for linear discrete-time stochastic systems with direct feedthrough that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense. We argue that the information about the unknown input can be obtained from the current time step as well as the previous one, making it possible to estimate the unknown input in different ways. We then propose one variation of the filter that uses the updated state estimate to compute the best linear unbiased estimate (BLUE) of the unknown input. The comparison of the new filter and the filters in existing literature is discussed in detail and tested in simulation examples.

Original languageEnglish (US)
Title of host publication2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7034-7039
Number of pages6
ISBN (Print)9781467357173
DOIs
StatePublished - Jan 1 2013
Event52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy
Duration: Dec 10 2013Dec 13 2013

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other52nd IEEE Conference on Decision and Control, CDC 2013
CountryItaly
CityFlorence
Period12/10/1312/13/13

Fingerprint

Unknown Inputs
Stochastic systems
State Estimation
State estimation
Discrete-time Systems
Stochastic Systems
Filter
Estimate
Unbiased variance
Optimal Filter
Minimum Variance
Simulation

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Cite this

Yong, S. Z., Zhu, M., & Frazzoli, E. (2013). Simultaneous input and state estimation for linear discrete-time stochastic systems with direct feedthrough. In 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013 (pp. 7034-7039). [6761004] (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2013.6761004
Yong, Sze Zheng ; Zhu, Minghui ; Frazzoli, Emilio. / Simultaneous input and state estimation for linear discrete-time stochastic systems with direct feedthrough. 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013. Institute of Electrical and Electronics Engineers Inc., 2013. pp. 7034-7039 (Proceedings of the IEEE Conference on Decision and Control).
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Yong, SZ, Zhu, M & Frazzoli, E 2013, Simultaneous input and state estimation for linear discrete-time stochastic systems with direct feedthrough. in 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013., 6761004, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 7034-7039, 52nd IEEE Conference on Decision and Control, CDC 2013, Florence, Italy, 12/10/13. https://doi.org/10.1109/CDC.2013.6761004

Simultaneous input and state estimation for linear discrete-time stochastic systems with direct feedthrough. / Yong, Sze Zheng; Zhu, Minghui; Frazzoli, Emilio.

2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013. Institute of Electrical and Electronics Engineers Inc., 2013. p. 7034-7039 6761004 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - In this paper, we present an optimal filter for linear discrete-time stochastic systems with direct feedthrough that simultaneously estimates the states and unknown inputs in an unbiased minimum-variance sense. We argue that the information about the unknown input can be obtained from the current time step as well as the previous one, making it possible to estimate the unknown input in different ways. We then propose one variation of the filter that uses the updated state estimate to compute the best linear unbiased estimate (BLUE) of the unknown input. The comparison of the new filter and the filters in existing literature is discussed in detail and tested in simulation examples.

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Yong SZ, Zhu M, Frazzoli E. Simultaneous input and state estimation for linear discrete-time stochastic systems with direct feedthrough. In 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013. Institute of Electrical and Electronics Engineers Inc. 2013. p. 7034-7039. 6761004. (Proceedings of the IEEE Conference on Decision and Control). https://doi.org/10.1109/CDC.2013.6761004