Linear unbiased state estimation under randomly varying bounded sensor delay

E. Yaz; A. Ray

doi:10.1016/S0893-9659(98)00051-2

Linear unbiased state estimation under randomly varying bounded sensor delay

E. Yaz
, A. Ray

Mechanical Engineering

Research output: Contribution to journal › Article › peer-review

98 Scopus citations

Abstract

The motivation for the work reported in this paper accrues from the necessity of finding stabilizing control laws for systems with randomly varying bounded sensor delay. It reports the development of reduced-order linear unbiased estimators for discrete-time stochastic parameter systems and shows how to parametrize the estimator gains to achieve a certain estimation error covariance. Both finite-time and steady-state estimators are considered. The results are potentially applicable to state estimation for stabilizing output feedback control systems.

Original language	English (US)
Pages (from-to)	27-32
Number of pages	6
Journal	Applied Mathematics Letters
Volume	11
Issue number	4
DOIs	https://doi.org/10.1016/S0893-9659(98)00051-2
State	Published - Jul 1998

All Science Journal Classification (ASJC) codes

Applied Mathematics

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10.1016/S0893-9659(98)00051-2

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title = "Linear unbiased state estimation under randomly varying bounded sensor delay",

abstract = "The motivation for the work reported in this paper accrues from the necessity of finding stabilizing control laws for systems with randomly varying bounded sensor delay. It reports the development of reduced-order linear unbiased estimators for discrete-time stochastic parameter systems and shows how to parametrize the estimator gains to achieve a certain estimation error covariance. Both finite-time and steady-state estimators are considered. The results are potentially applicable to state estimation for stabilizing output feedback control systems.",

author = "E. Yaz and A. Ray",

note = "Funding Information: Since, in this work, the state estimation problem for a model involving randomly varying bounded sensor delays is reformulated as a stochastic parameter estimation, the analysis is based on the previous work in the latter area. Special cases of such models have been considered for minimum variance estimation by Nahi \textbackslash{}[3\textbackslash{}] in an uncertain measurement context where the The work reported in this paper was supported in part by the National Science Foundation under Grants ECS-9322798 and CMS-9531835.",

year = "1998",

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doi = "10.1016/S0893-9659(98)00051-2",

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AU - Yaz, E.

AU - Ray, A.

N1 - Funding Information: Since, in this work, the state estimation problem for a model involving randomly varying bounded sensor delays is reformulated as a stochastic parameter estimation, the analysis is based on the previous work in the latter area. Special cases of such models have been considered for minimum variance estimation by Nahi \[3\] in an uncertain measurement context where the The work reported in this paper was supported in part by the National Science Foundation under Grants ECS-9322798 and CMS-9531835.

PY - 1998/7

Y1 - 1998/7

N2 - The motivation for the work reported in this paper accrues from the necessity of finding stabilizing control laws for systems with randomly varying bounded sensor delay. It reports the development of reduced-order linear unbiased estimators for discrete-time stochastic parameter systems and shows how to parametrize the estimator gains to achieve a certain estimation error covariance. Both finite-time and steady-state estimators are considered. The results are potentially applicable to state estimation for stabilizing output feedback control systems.

AB - The motivation for the work reported in this paper accrues from the necessity of finding stabilizing control laws for systems with randomly varying bounded sensor delay. It reports the development of reduced-order linear unbiased estimators for discrete-time stochastic parameter systems and shows how to parametrize the estimator gains to achieve a certain estimation error covariance. Both finite-time and steady-state estimators are considered. The results are potentially applicable to state estimation for stabilizing output feedback control systems.

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ER -

Linear unbiased state estimation under randomly varying bounded sensor delay

Abstract

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