Robust inferential control using kernel density methods

Authors
Goulding, PR Lennox, B Chen, Q Sandoz, DJ
Citation
Pr. Goulding et al., Robust inferential control using kernel density methods, COMPUT CH E, 24(2-7), 2000, pp. 835-840
Citations number
11
Categorie Soggetti
Chemical Engineering
Journal title
COMPUTERS & CHEMICAL ENGINEERING
ISSN journal
00981354 → ACNP
Volume
24
Issue
2-7
Year of publication
2000
Pages
835 - 840
Database
ISI
SICI code
0098-1354(20000715)24:2-7<835:RICUKD>2.0.ZU;2-L
Abstract
The use of kernel density estimation (KDE) methods to address the issue of control under process uncertainty and unreliability is investigated. It is shown how the KDE-derived joint probability density function of plant opera tional data can be used to assist in this task. It is also shown how the es timated density function can be used to support robust inference of importa nt plant variables in addition to the detection and isolation of faults. (C ) 2000 Elsevier Science Ltd. All rights reserved.