Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach

Ian R. Petersen

doi:10.1109/IDC.2007.374518

Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach

Ian R. Petersen^*

^*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

This paper presents a new approach to robust nonlinear state estimation based on the use of Integral Quadratic Constraints and minimax LQG control. The approach involves a class of state estimators which include copies on the system nonlinearities in the state estimator. The nonlinearities being considered are those which satisfy a certain global Lipschitz condition. The linear part of the state estimator is synthesized using minimax LQG control theory which is closely related to H^∞ control theory and this leads to a nonlinear state estimator which gives an upper bound on the estimation error cost.

Original language	English
Title of host publication	Conference Proceedings of 2007 Information, Decision and Control, IDC
Pages	17-22
Number of pages	6
DOIs	https://doi.org/10.1109/IDC.2007.374518
Publication status	Published - 2007
Externally published	Yes
Event	2007 Information, Decision and Control, IDC - Adelaide, Australia Duration: 12 Feb 2007 → 14 Feb 2007

Publication series

Name	Conference Proceedings of 2007 Information, Decision and Control, IDC

Conference

Conference	2007 Information, Decision and Control, IDC
Country/Territory	Australia
City	Adelaide
Period	12/02/07 → 14/02/07

Access to Document

10.1109/IDC.2007.374518

Cite this

@inproceedings{9daeb120299f483498080be4b1f6314f,

title = "Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach",

abstract = "This paper presents a new approach to robust nonlinear state estimation based on the use of Integral Quadratic Constraints and minimax LQG control. The approach involves a class of state estimators which include copies on the system nonlinearities in the state estimator. The nonlinearities being considered are those which satisfy a certain global Lipschitz condition. The linear part of the state estimator is synthesized using minimax LQG control theory which is closely related to H∞ control theory and this leads to a nonlinear state estimator which gives an upper bound on the estimation error cost.",

author = "Petersen, \{Ian R.\}",

year = "2007",

doi = "10.1109/IDC.2007.374518",

language = "English",

isbn = "1424409020",

series = "Conference Proceedings of 2007 Information, Decision and Control, IDC",

pages = "17--22",

booktitle = "Conference Proceedings of 2007 Information, Decision and Control, IDC",

note = "2007 Information, Decision and Control, IDC ; Conference date: 12-02-2007 Through 14-02-2007",

}

Petersen, IR 2007, Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach. in Conference Proceedings of 2007 Information, Decision and Control, IDC., 4252470, Conference Proceedings of 2007 Information, Decision and Control, IDC, pp. 17-22, 2007 Information, Decision and Control, IDC, Adelaide, Australia, 12/02/07. https://doi.org/10.1109/IDC.2007.374518

Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach. / Petersen, Ian R.
Conference Proceedings of 2007 Information, Decision and Control, IDC. 2007. p. 17-22 4252470 (Conference Proceedings of 2007 Information, Decision and Control, IDC).

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

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PY - 2007

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N2 - This paper presents a new approach to robust nonlinear state estimation based on the use of Integral Quadratic Constraints and minimax LQG control. The approach involves a class of state estimators which include copies on the system nonlinearities in the state estimator. The nonlinearities being considered are those which satisfy a certain global Lipschitz condition. The linear part of the state estimator is synthesized using minimax LQG control theory which is closely related to H∞ control theory and this leads to a nonlinear state estimator which gives an upper bound on the estimation error cost.

AB - This paper presents a new approach to robust nonlinear state estimation based on the use of Integral Quadratic Constraints and minimax LQG control. The approach involves a class of state estimators which include copies on the system nonlinearities in the state estimator. The nonlinearities being considered are those which satisfy a certain global Lipschitz condition. The linear part of the state estimator is synthesized using minimax LQG control theory which is closely related to H∞ control theory and this leads to a nonlinear state estimator which gives an upper bound on the estimation error cost.

UR - https://www.scopus.com/pages/publications/34548832236

U2 - 10.1109/IDC.2007.374518

DO - 10.1109/IDC.2007.374518

M3 - Conference Paper

AN - SCOPUS:34548832236

SN - 1424409020

SN - 9781424409020

T3 - Conference Proceedings of 2007 Information, Decision and Control, IDC

SP - 17

EP - 22

BT - Conference Proceedings of 2007 Information, Decision and Control, IDC

T2 - 2007 Information, Decision and Control, IDC

Y2 - 12 February 2007 through 14 February 2007

ER -

Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach

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