Original scientific paper
SOFT SENSORS APPLICATION FOR CRUDE DISTILLATION UNIT PRODUCT QUALITY ESTIMATION
Željka Ujević Andrijić
orcid.org/0000-0003-2290-9664
; Faculty of Chemical Engineering and Technology, University of Zagreb
Nenad Bolf
; Faculty of Chemical Engineering and Technology, University of Zagreb
Abstract
Fractionation product properties of the crude distillation unit (CDU) need to be monitored and controlled through feedback mechanism. Due to the inability of on-line measurement, soft sensors for product quality estimation are developed. Soft sensors for kerosene 95% distillation point are developed using linear and nonlinear identification methods. Experimental data are acquired from the refinery distributed control system (DCS) and include on-line available continuously measured variables and laboratory assays. In present work development of AutoRegressive Moving Average with eXogenous inputs (ARMAX), Nonlinear AutoRegressive model with eXogenous inputs (NARX) and Hammerstein-Wiener (HW) model are presented. To overcome the problem of selecting the best model parameters by trial and error procedure, genetic algorithms were used for determining the best model parameters. Based on developed soft sensors it is possible to estimate fuel properties continuously by embedding model in DCS on site as well as applying the methods of inferential control.
Keywords
topping; optimal process control and regulation; software sensors for process modeling system selection
Hrčak ID:
72468
URI
Publication date:
3.10.2011.
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