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

被引：512

作者：

Gillijns, Steven ^{[1
]}

De Moor, Bart ^{[1
]}

机构：

[1] Katholieke Univ Leuven, ESAT, SCD, SISTA, B-3001 Louvain, Belgium

来源：

AUTOMATICA | 2007年 / 43卷 / 01期

关键词：

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

D O I：

10.1016/j.automatica.2006.08.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：111 / 116

页数：6

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