Open AccessOptimization of back pressure control of direct air-cooling unit based on GPC
Author(s) -
Jianyun Bai,
Ru Shao,
Qi Ren
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/675/1/012101
Subject(s) - pid controller , robustness (evolution) , control theory (sociology) , model predictive control , pressure control , fuzzy control system , computer science , back pressure , control system , fuzzy logic , control engineering , engineering , control (management) , temperature control , artificial intelligence , mechanical engineering , biochemistry , chemistry , electrical engineering , gene
In view of the fact that the actual back pressure is difficult to track the set value quickly and stably, this paper applies the predictive control algorithm (GPC) which can respond quickly, has good robustness and is easy to realize in the industrial production site to optimize the back pressure control. The control performance of the back pressure control system with PID, fuzzy PID and GPC is compared and analyzed through the simulation test. The simulation results show that the GPC algorithm has better dynamic performance than PID and fuzzy PID control in the case of set point disturbance and internal disturbance, and has stronger robustness in the face of model mismatch. To sum up, GPC algorithm is more suitable for the back pressure control system under complex working conditions, and the optimization control method has a certain guiding significance for the actual production site back pressure control strategy improvement.