Title :
Multivariable generalized predictive control based on receding feedback correction in binary distillation process
Author :
Chaochun, Li ; Lili, Tao ; Hui, Cheng ; Rongbin, Qi ; Feng, Qian
Author_Institution :
Key Lab. of Adv. Control & Optimization for Chem. Processes, East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
An improved generalized predictive control (GPC) algorithm has been proposed in this paper. In order to cut off computation burden and get good performance of disturbance rejection, receding feedback correction mechanism is used to reject the disturbance instead of the traditional online identification mechanism. Furthermore, two factors are presented to tune for good dynamic performance. Simulation has been carried out with a binary distillation process model, named wood& berry model, which is a typical multivariable process. The simulation result proves the efficiency of proposed algorithm.
Keywords :
distillation; feedback; multivariable control systems; predictive control; GPC algorithm; binary distillation process; disturbance rejection; multivariable generalized predictive control; receding feedback correction mechanism; wood and berry model; Computational modeling; Equations; Heuristic algorithms; Prediction algorithms; Predictive control; Predictive models; Correction factor; Soft factor; generalized predictive control; receding feedback correction;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
DOI :
10.1109/WCICA.2012.6358044
