DocumentCode
3550959
Title
Data-driven Kalman filters for non-uniformly sampled multirate systems with application to fault diagnosis
Author
Li, Weihua ; Shah, Sirish
Author_Institution
Dept. of Chem. & Mater. Eng., Alberta Univ., Edmonton, Alta., Canada
fYear
2005
fDate
8-10 June 2005
Firstpage
2768
Abstract
This paper first develops data-driven Kalman filters for non-uniformly sampled multirate systems. Then a novel methodology of fault detection and isolation for such systems is proposed. The proposed scheme is applied to a pilot scale experimental plant, where a successful case study on FDI is conducted.
Keywords
Kalman filters; fault diagnosis; identification; sampled data systems; state-space methods; data-driven Kalman filters; fault detection; fault diagnosis; fault isolation; nonuniformly sampled multirate systems; state space models; subspace method of identification; Adaptive control; Electrical equipment industry; Fault detection; Fault diagnosis; Kalman filters; Sampling methods; Signal processing algorithms; State estimation; System identification; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2005. Proceedings of the 2005
ISSN
0743-1619
Print_ISBN
0-7803-9098-9
Electronic_ISBN
0743-1619
Type
conf
DOI
10.1109/ACC.2005.1470388
Filename
1470388
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