TY - JOUR
T1 - Distributed Model Predictive Control of an Amine Gas Sweetening Plant
AU - Moharir, Manjiri
AU - Pourkargar, Davood B.
AU - Almansoori, Ali
AU - Daoutidis, Prodromos
N1 - 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.
PY - 2018/10/3
Y1 - 2018/10/3
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85054134459&partnerID=8YFLogxK
U2 - 10.1021/acs.iecr.8b01291
DO - 10.1021/acs.iecr.8b01291
M3 - Article
AN - SCOPUS:85054134459
SN - 0888-5885
VL - 57
SP - 13103
EP - 13115
JO - Industrial and Engineering Chemistry Research
JF - Industrial and Engineering Chemistry Research
IS - 39
ER -