REDUCED-ORDER STATE ESTIMATION FOR LINEAR TIME-VARYING SYSTEMS

被引：0

作者：

Kim, In Sung ^{[1
]}

Teixeira, Bruno O. S. ^{[2
]}

Chandrasekar, Jaganath ^{[1
]}

Bernstein, Dennis S. ^{[1
]}

机构：

[1] Univ Michigan, Dept Aerosp Engn, Ann Arbor, MI 48109 USA

[2] Univ Fed Minas Gerais, Dept Elect Engn, Belo Horizonte, MG, Brazil

来源：

ASIAN JOURNAL OF CONTROL | 2009年 / 11卷 / 06期

基金：

美国国家科学基金会;

关键词：

Reduced-order Kalman filter; reduced-order state estimation; linear time-varying systems; OPTIMAL PROJECTION EQUATIONS; KALMAN FILTER; DISCRETE;

D O I：

10.1002/asjc.141

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider reduced-order and subspace state estimators for linear discrete-time systems with possibly time-varying dynamics. The reduced-order and subspace estimators are obtained using a finite-horizon minimization approach, and thus do not require the solution of algebraic Lyapunov or Riccati equations.

引用

页码：595 / 609

页数：15

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