TY - JOUR
T1 - Optimization of control performance on CO 2 removal in subang field using model predictive control
AU - Wahid, Abdul
AU - Wiranoto, Yoga
N1 - Publisher Copyright:
© The Authors, published by EDP Sciences, 2018.
PY - 2018/11/26
Y1 - 2018/11/26
N2 - A model predictive control (MPC) is used to optimize the control performance on CO 2 removal in Subang Field. MPC is implemented to control the feed gas pressure (PIC-1101), amine flow rate (FIC-1102), and makeup water flowrate (FIC-1103) to maintain CO 2 concentration in sweet gas. MPC is built using the first-order plus dead time (FOPDT) models. The control performance tests are used set point (SP) tracking and disturbance rejection with the performance indicator is the integral of square error (ISE). The result show that the optimum setting of prediction horizon (P), horizon (M) and Time Sampling (T) in MPC are 9 1, 32 and 1 on PIC-1101; 34, 10 and 5 on FIC-1102 and 40, 10 and 5 on FIC-1103. Based on ISE values, the use of MPC can improve performance for set point tracking by 14.02% in PIC-1101, 76.74% in FIC-1102, and 16.31% in FIC-1103, the use of MPC can improve performance for disturbance rejection by 19.32% in FIC-1102, and 91.57% in FIC-1103, compared with the proportional-integral (PI) controller that used in the field.
AB - A model predictive control (MPC) is used to optimize the control performance on CO 2 removal in Subang Field. MPC is implemented to control the feed gas pressure (PIC-1101), amine flow rate (FIC-1102), and makeup water flowrate (FIC-1103) to maintain CO 2 concentration in sweet gas. MPC is built using the first-order plus dead time (FOPDT) models. The control performance tests are used set point (SP) tracking and disturbance rejection with the performance indicator is the integral of square error (ISE). The result show that the optimum setting of prediction horizon (P), horizon (M) and Time Sampling (T) in MPC are 9 1, 32 and 1 on PIC-1101; 34, 10 and 5 on FIC-1102 and 40, 10 and 5 on FIC-1103. Based on ISE values, the use of MPC can improve performance for set point tracking by 14.02% in PIC-1101, 76.74% in FIC-1102, and 16.31% in FIC-1103, the use of MPC can improve performance for disturbance rejection by 19.32% in FIC-1102, and 91.57% in FIC-1103, compared with the proportional-integral (PI) controller that used in the field.
UR - http://www.scopus.com/inward/record.url?scp=85058713934&partnerID=8YFLogxK
U2 - 10.1051/e3sconf/20186701028
DO - 10.1051/e3sconf/20186701028
M3 - Conference article
AN - SCOPUS:85058713934
SN - 2555-0403
VL - 67
JO - E3S Web of Conferences
JF - E3S Web of Conferences
M1 - 01028
T2 - 3rd International Tropical Renewable Energy Conference "Sustainable Development of Tropical Renewable Energy", i-TREC 2018
Y2 - 6 September 2018 through 8 September 2018
ER -