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Model-Predictive Control Fundamentals

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Springer Handbook of Petroleum Technology

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Abstract

Model-predictive control (GlossaryTerm

MPC

) improves the capability of process units by stabilizing operation, increasing throughput, improving fractionator performance, decreasing product quality giveaway, and reducing utility consumption. MPC provides real-time information to higher-level applications, such as planning models and process optimizers. MPC input comes from the distributed control system (GlossaryTerm

DCS

), advanced regulatory controllers (GlossaryTerm

ARC

s), and laboratory data. A well-implemented MPC controller responds once per minute – or in some cases more frequently – to changes in feedstock, ambient temperature, and so on, by moving several variables simultaneously. For major process units, returns on investment for MPC can exceed $0.50 per barrel, not including collateral benefits, such as improving the efficiency of operators and engineers, and improving process safety.

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Robinson, P.R., Cima, D. (2017). Model-Predictive Control Fundamentals. In: Hsu, C.S., Robinson, P.R. (eds) Springer Handbook of Petroleum Technology. Springer Handbooks. Springer, Cham. https://doi.org/10.1007/978-3-319-49347-3_26

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