DocumentCode :
2269071
Title :
Large-scale system state estimation with sequential measurements
Author :
Arcy, F.D. ; Swidenbank, E. ; Hogg, B.W.
Author_Institution :
Queen´´s Univ., Belfast, UK
fYear :
1998
fDate :
1-4 Sep 1998
Firstpage :
1218
Abstract :
Incremental state estimation algorithms are tested and compared against the traditional discrete extended Kalman filter for the case of large-scale systems with measurements collected sequentially. Five models from a generic library of power plant component models are used as interconnected sub-models in a large-scale hierarchical model. This test model is simulated with integrated noise, measurement noise and discontinuous inputs. The resultant noisy measurements are collected sequentially rather than as a vector of simultaneous measurements. Several alternative state estimation schemes are implemented and the results are presented and compared
Keywords :
large-scale systems; hierarchical model; large-scale systems; measurement noise; power plant component models; sequential measurements; state estimation;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Control '98. UKACC International Conference on (Conf. Publ. No. 455)
Conference_Location :
Swansea
ISSN :
0537-9989
Print_ISBN :
0-85296-708-X
Type :
conf
DOI :
10.1049/cp:19980401
Filename :
726093
Link To Document :
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