Distributed Model Predictive Control of an Amine Gas Sweetening Plant

Manjiri Moharir; Davood B. Pourkargar; Ali Almansoori; Prodromos Daoutidis

doi:10.1021/acs.iecr.8b01291

Distributed Model Predictive Control of an Amine Gas Sweetening Plant

Manjiri Moharir, Davood B. Pourkargar, Ali Almansoori, Prodromos Daoutidis

Chemical Engineering and Materials Science

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

This paper addresses the plant-wide control of the amine gas sweetening plant using distributed model predictive control. The plant is fed natural gas containing sour gases (hydrogen sulfide and carbon dioxide), which are removed by absorption in monoethanolamine solution. A plant decomposition algorithm based on modularity maximization for distributed parameter systems is used to obtain the optimal decomposition for distributed model predictive control. Comparisons are drawn among the performance and computational requirements of distributed, decentralized, and centralized model predictive controls.

Original language	English (US)
Pages (from-to)	13103-13115
Number of pages	13
Journal	Industrial and Engineering Chemistry Research
Volume	57
Issue number	39
DOIs	https://doi.org/10.1021/acs.iecr.8b01291
State	Published - Oct 3 2018

Bibliographical note

Funding Information:
Partial financial support from Khalifa University of Science, Technology and Research, Abu Dhabi, UAE, is gratefully acknowledged.

Publisher Copyright:
© 2018 American Chemical Society.

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AU - Almansoori, Ali

AU - Daoutidis, Prodromos

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Distributed Model Predictive Control of an Amine Gas Sweetening Plant

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