Document Type : Research Articles


1 Center for Process Integration and Control (CPIC), Department of Chemical Engineering, University of Sistan and Baluchestan, Zahedan, Iran

2 Center for Process Integration and Control (CPIC) Department of Chemical Engineering University of Sistan and Baluchestan

3 Center of Process Integration and Control (CPIC) Department of Chemical Engineering University of Sistan and Baluchestan Zahedan, PoBox: 98135-987 Iran

4 Center of Process Integration and Control (CPIC), Department of Chemical Engineering, University of Sistan and Baluchestan, Zahedan, PoBox: 98135-987 Iran


The changes in the crude oil flow rate to an atmospheric distillation unit can influence the quality of the products. This paper presents a modification method for soft sensing model including an update term, which makes it compatible with industrial variations. A modified soft sensing structure is adopted using lookup table (LUT) method where steady-state soft sensing models are performed. The steady-state soft sensing models is proposed based on local instrumental variable (LIV) technique for an industrial atmospheric distillation unit (ADU) at Shiraz refinery, Iran. The LIV-based soft sensors are utilized tray temperature measurements to monitor ASTM-D86 index of side products for nominal flow rate (60,000bbl/day). Lookup tables have been developed based on the difference between the predicted values of ASTM-D86 index and corresponding simulation values to make update terms in different feed flow rates. The results present improvement in the predictions of LIV-based soft sensors as well as acceptable control performance in feed flow rate variations. The comparison of soft sensing results with/without lookup tables demonstrates that the proposed update term helps to predict product quality more precisely and is suitable for advanced monitoring scheme due to no complexity and low computational time.


Main Subjects

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