On the optimality of recursive unbiased state estimation with unknown inputs

W. S. Kerwin; J. L. Prince

doi:10.1016/S0005-1098(00)00046-7

On the optimality of recursive unbiased state estimation with unknown inputs

W. S. Kerwin, J. L. Prince

Whiting School of Engineering

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

34 Scopus citations

Abstract

For system models with unknown inputs, state estimates may be obtained using linear minimum-variance unbiased estimation. A proof is presented showing that the optimal solution over the class of all linear unbiased estimates may be written in the form of a linear recursive filter.

Original language	English (US)
Pages (from-to)	1381-1383
Number of pages	3
Journal	Automatica
Volume	36
Issue number	9
DOIs	https://doi.org/10.1016/S0005-1098(00)00046-7
State	Published - Sep 2000

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

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10.1016/S0005-1098(00)00046-7

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title = "On the optimality of recursive unbiased state estimation with unknown inputs",

abstract = "For system models with unknown inputs, state estimates may be obtained using linear minimum-variance unbiased estimation. A proof is presented showing that the optimal solution over the class of all linear unbiased estimates may be written in the form of a linear recursive filter.",

author = "Kerwin, {W. S.} and Prince, {J. L.}",

year = "2000",

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AU - Prince, J. L.

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JO - Automatica

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On the optimality of recursive unbiased state estimation with unknown inputs

Abstract

ASJC Scopus subject areas

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