Reduced-order Kalman recursive filter for non-square descriptor systems with correlated noise

Author

Tian Hangwei ; Shi Ying

Author_Institution

Dept. Autom., Heilongjiang Univ., Harbin, China

fYear

2011

fDate

22-24 July 2011

Firstpage

1428

Lastpage

1431

Abstract

Using singular value decomposition of matrix and the theory of generalized inverse matrix, the non-square descriptor discrete time stochastic system is decomposed into two subsystems. Based on the classical Kalman filtering theory, the state estimation problem is considered for non-square descriptor discrete time stochastic systems. A Reduced-order Kalman recursive filter for non-square descriptor systems with correlated noise is given. Some numerical examples illustrate the effectiveness of the proposed algorithm.

Keywords

Kalman filters; discrete time systems; matrix algebra; reduced order systems; singular value decomposition; stochastic systems; correlated noise; discrete time stochastic system; filtering theory; generalized inverse matrix theory; nonsquare descriptor systems; reduced order Kalman recursive filter; singular value decomposition; state estimation problem; Electronic mail; Filtering theory; Kalman filters; Matrix decomposition; Noise; Singular value decomposition; Stochastic systems; Generalized inverse matrix; Kalman filter; Non-square descriptor systems; Singular value decomposition;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference (CCC), 2011 30th Chinese

Conference_Location

Yantai

ISSN

1934-1768

Print_ISBN

978-1-4577-0677-6

Electronic_ISBN

1934-1768

Type

conf

Filename

6000399