TY - JOUR
T1 - Distributed model predictive control of process networks
T2 - Impact of control architecture
AU - Pourkargar, Davood Babaei
AU - Almansoori, Ali
AU - Daoutidis, Prodromos
N1 - Publisher Copyright:
© 2017
PY - 2017/7
Y1 - 2017/7
N2 - This paper investigates the impact of control architecture design on the distributed model predictive control (MPC) of nonlinear complex process networks. A sequential distributed MPC structure is synthesized to regulate a nonlinear system whose dynamics are decomposed into multiple subsystems by community detection methods. The closed-loop performance and computational effort of employing centralized and sequential distributed MPC structures is analyzed for a reactor-separator integrated process.
AB - This paper investigates the impact of control architecture design on the distributed model predictive control (MPC) of nonlinear complex process networks. A sequential distributed MPC structure is synthesized to regulate a nonlinear system whose dynamics are decomposed into multiple subsystems by community detection methods. The closed-loop performance and computational effort of employing centralized and sequential distributed MPC structures is analyzed for a reactor-separator integrated process.
KW - control architecture
KW - Distributed process control
KW - integrated process systems
KW - model predictive control
KW - network decomposition
UR - http://www.scopus.com/inward/record.url?scp=85044258454&partnerID=8YFLogxK
U2 - 10.1016/j.ifacol.2017.08.1920
DO - 10.1016/j.ifacol.2017.08.1920
M3 - Article
AN - SCOPUS:85044258454
SN - 2405-8963
VL - 50
SP - 12452
EP - 12457
JO - 20th IFAC World Congress
JF - 20th IFAC World Congress
IS - 1
ER -