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
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;
Conference_Titel :
American Control Conference, 2005. Proceedings of the 2005
Print_ISBN :
0-7803-9098-9
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2005.1470388
