NDLI: Generalized predictive control for a precise crude oil blending process

Content Provider	IEEE Xplore Digital Library
Author	Aimin An Xiaohong Hao Hongye Su
Copyright Year	2008
Description	Author affiliation: Inst. of Electr. Eng. & Inf. Eng., Lanzhou Univ. of Technol., Lanzhou (Aimin An; Xiaohong Hao)
Abstract	The refinery units frequently need advanced process control (APC) strategies and near smooth real-time feed stream composition of crude oil for increasing economic profit in petroleum refining industry. So crude oil blending is a crucial process for managing crude transitions in logistics. In this paper we model the blending process as multi-input multi-output (MIMO) CARIMA model according to the characteristics that there is no coupling among variables, we control the blending process based on generalized predictive control (GPC) strategy. Meanwhile a nuclear magnetic resonance (NMR) spectroscopy analyzer is used to precisely measure the important crude oil composition of different steam of the blender. Then the real time data is used to adapt the parameters of CARIMA model. Finally, the accurateness and suitability of the proposed method is demonstrated with the case study of a crude oil blender.
Starting Page	7
Ending Page	12
File Size	192655
Page Count	6
File Format	PDF
ISBN	9781424425020
DOI	10.1109/ICAL.2008.4636110
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Nuclear magnetic resonance spectroscopy analyzer Crude oil blending Generalized predictive control Process control CARIMA model Nuclear magnetic resonance Feeds Petroleum Equations Optimization
Content Type	Text
Resource Type	Article

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