4.7 Article

Unbiased minimum-variance input and state estimation for linear discrete-time systems

Journal

AUTOMATICA
Volume 43, Issue 1, Pages 111-116

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.automatica.2006.08.002

Keywords

Kalman filtering; recursive state estimation; unknown input estimation; minimum-variance estimation

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This paper addresses the problem of simultaneously estimating the state and the input of a linear discrete-time system. A recursive filter, optimal in the minimum-variance unbiased sense, is developed where the estimation of the state and the input are interconnected. The input estimate is obtained from the innovation by least-squares estimation and the state estimation problem is transformed into a standard Kalman filtering problem. Necessary and sufficient conditions for the existence of the filter are given and relations to earlier results are discussed. (c) 2006 Elsevier Ltd. All rights reserved.

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