TY - JOUR
T1 - Distributed Estimation and Nonlinear Model Predictive Control Using Community Detection
AU - Pourkargar, Davood B.
AU - Moharir, Manjiri
AU - Almansoori, Ali
AU - Daoutidis, Prodromos
N1 - Publisher Copyright:
© 2019 American Chemical Society.
PY - 2019/7/31
Y1 - 2019/7/31
N2 - A combined distributed moving horizon estimation and distributed model predictive control architecture is proposed to address the distributed output-feedback control problem for nonlinear process systems. Community detection based on modularity maximization is used to generate separate optimal decompositions for the estimation and control problems on the basis of suitable graphs. The process of benzene alkylation with ethylene is used as a case study to illustrate the application and computational advantages of the proposed control strategy.
AB - A combined distributed moving horizon estimation and distributed model predictive control architecture is proposed to address the distributed output-feedback control problem for nonlinear process systems. Community detection based on modularity maximization is used to generate separate optimal decompositions for the estimation and control problems on the basis of suitable graphs. The process of benzene alkylation with ethylene is used as a case study to illustrate the application and computational advantages of the proposed control strategy.
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U2 - 10.1021/acs.iecr.9b00820
DO - 10.1021/acs.iecr.9b00820
M3 - Article
AN - SCOPUS:85068777877
SN - 0888-5885
VL - 58
SP - 13495
EP - 13507
JO - Industrial and Engineering Chemistry Research
JF - Industrial and Engineering Chemistry Research
IS - 30
ER -