Journal
ISA TRANSACTIONS
Volume 64, Issue -, Pages 184-192Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2016.06.002
Keywords
KPCA; RKPCA; MW-RKPCA; Nonlinear dynamic process; Fault detection
Ask authors/readers for more resources
This paper proposes an improved Reduced Kernel Principal Component Analysis (RKPCA) for handling nonlinear dynamic systems. The proposed method is entitled Moving Window Reduced Kernel Principal Component Analysis (MW-RKPCA). It consists firstly in approximating the principal components (PCs) of the KPCA model by a reduced data set that approaches properly the system behavior in the order to elaborate an RKPCA model. Secondly, the proposed MW-RKPCA consists on updating the RKPCA model using a moving window. The relevance of the proposed MW-RKPCA technique is illustrated on a Tennessee Eastman process. (C) 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available