Robust state estimation for discrete time-varying uncertain systems with a known deterministic input

Huabo Liu; Haisheng Yu; Yang Liu

doi:10.1109/CAC.2017.8242843

Robust state estimation for discrete time-varying uncertain systems with a known deterministic input

Huabo Liu, Haisheng Yu, Yang Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Robust state estimation of a discrete time-varying uncertain system is investigated in this paper when there are not only process and measurement noise, but also parameter uncertainties which affect a state-space model arbitrarily. The expectation minimization based robust state estimation is generalized to uncertain linear systems with a known deterministic input signal. The derived robust estimator has similar forms to the standard Kalman filter with a comparable computational complexity. Several numerical simulations show that the obtained robust state estimator has nice estimation performances.

Original language	English
Title of host publication	Proceedings - 2017 Chinese Automation Congress
Subtitle of host publication	CAC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	624-627
Number of pages	4
ISBN (Electronic)	9781538635247, 9781538635230
ISBN (Print)	9781538635254
DOIs	https://doi.org/10.1109/CAC.2017.8242843
Publication status	Published - 1 Jan 2018
Externally published	Yes
Event	2017 Chinese Automation Congress - Jinan, China Duration: 20 Oct 2017 → 22 Oct 2017

Conference

Conference	2017 Chinese Automation Congress
Abbreviated title	CAC 2017
Country/Territory	China
City	Jinan
Period	20/10/17 → 22/10/17

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10.1109/CAC.2017.8242843Licence: Unspecified

Cite this

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title = "Robust state estimation for discrete time-varying uncertain systems with a known deterministic input",

abstract = "Robust state estimation of a discrete time-varying uncertain system is investigated in this paper when there are not only process and measurement noise, but also parameter uncertainties which affect a state-space model arbitrarily. The expectation minimization based robust state estimation is generalized to uncertain linear systems with a known deterministic input signal. The derived robust estimator has similar forms to the standard Kalman filter with a comparable computational complexity. Several numerical simulations show that the obtained robust state estimator has nice estimation performances.",

keywords = "Robustness, Uncertainty, Kalman filters, State estimation, Uncertain systems, Computational modeling",

author = "Huabo Liu and Haisheng Yu and Yang Liu",

note = "Funding Information: ACKNOWLEDGMENT. This work was supported by National Natural Science Foundation of China (Grant Nos. 61573203 and 61573204), China Postdoctoral Science Foundation (Grant Nos. 20l7M612190 and 2016M600546) and Qingdao Postdoctoral Applied Research Projects (Grant No. 2016112). Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 Chinese Automation Congress, CAC 2017 ; Conference date: 20-10-2017 Through 22-10-2017",

year = "2018",

month = jan,

day = "1",

doi = "10.1109/CAC.2017.8242843",

language = "English",

isbn = "9781538635254",

pages = "624--627",

booktitle = "Proceedings - 2017 Chinese Automation Congress",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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}

Robust state estimation for discrete time-varying uncertain systems with a known deterministic input. / Liu, Huabo; Yu, Haisheng; Liu, Yang.

Proceedings - 2017 Chinese Automation Congress: CAC 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 624-627 8242843.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Robust state estimation for discrete time-varying uncertain systems with a known deterministic input

AU - Liu, Huabo

AU - Yu, Haisheng

AU - Liu, Yang

N1 - Funding Information: ACKNOWLEDGMENT. This work was supported by National Natural Science Foundation of China (Grant Nos. 61573203 and 61573204), China Postdoctoral Science Foundation (Grant Nos. 20l7M612190 and 2016M600546) and Qingdao Postdoctoral Applied Research Projects (Grant No. 2016112). Publisher Copyright: © 2017 IEEE.

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Robust state estimation of a discrete time-varying uncertain system is investigated in this paper when there are not only process and measurement noise, but also parameter uncertainties which affect a state-space model arbitrarily. The expectation minimization based robust state estimation is generalized to uncertain linear systems with a known deterministic input signal. The derived robust estimator has similar forms to the standard Kalman filter with a comparable computational complexity. Several numerical simulations show that the obtained robust state estimator has nice estimation performances.

AB - Robust state estimation of a discrete time-varying uncertain system is investigated in this paper when there are not only process and measurement noise, but also parameter uncertainties which affect a state-space model arbitrarily. The expectation minimization based robust state estimation is generalized to uncertain linear systems with a known deterministic input signal. The derived robust estimator has similar forms to the standard Kalman filter with a comparable computational complexity. Several numerical simulations show that the obtained robust state estimator has nice estimation performances.

KW - Robustness

KW - Uncertainty

KW - Kalman filters

KW - State estimation

KW - Uncertain systems

KW - Computational modeling

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U2 - 10.1109/CAC.2017.8242843

DO - 10.1109/CAC.2017.8242843

M3 - Conference contribution

AN - SCOPUS:85050350221

SN - 9781538635254

SP - 624

EP - 627

BT - Proceedings - 2017 Chinese Automation Congress

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 Chinese Automation Congress

Y2 - 20 October 2017 through 22 October 2017

ER -

Robust state estimation for discrete time-varying uncertain systems with a known deterministic input

Abstract

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