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

Sze Zheng Yong; Minghui Zhu; Emilio Frazzoli

doi:10.1109/CDC.2013.6761004

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 proceeding › Conference contribution

23 Scopus citations

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 language	English (US)
Title of host publication	2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	7034-7039
Number of pages	6
ISBN (Print)	9781467357173
DOIs	https://doi.org/10.1109/CDC.2013.6761004
State	Published - 2013
Externally published	Yes
Event	52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, Italy Duration: Dec 10 2013 → Dec 13 2013

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Other

Other	52nd IEEE Conference on Decision and Control, CDC 2013
Country/Territory	Italy
City	Florence
Period	12/10/13 → 12/13/13

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

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10.1109/CDC.2013.6761004

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). Article 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

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 proceeding › Conference contribution

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

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). doi: 10.1109/CDC.2013.6761004

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

Abstract

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