DocumentCode
1983420
Title
Application of RBF Neural Network PID Controller in the Rectification Column Temperature Control System
Author
Yan Zhang ; Chaoying Liu ; Xueling Song ; Zhifei Yan
Author_Institution
Inst. of Electr. Eng., Hebei Univ. of Sci. & Technol., Shijiazhuang, China
Volume
2
fYear
2013
fDate
28-29 Oct. 2013
Firstpage
72
Lastpage
75
Abstract
The temperature control of the rectification column is an important part of distillation process control system. For the time-delay and parameter time-varying characteristics in rectification column temperature control system, it puts forward neural network self-tuning PID controller method which combines the advantages of traditional PID control and neural network radial basis function (RBF). From the simulation experiment results it shows that RBF neural network PID controller gets much better control effect, and it verifies the effectiveness of the proposed method.
Keywords
adaptive control; delay systems; distillation; distillation equipment; neurocontrollers; process control; radial basis function networks; rectification; self-adjusting systems; temperature control; three-term control; time-varying systems; RBF neural network PID controller; control effect; distillation process control system; forward neural network self-tuning PID controller method; neural network radial basis function; parameter time-varying characteristics; rectification column temperature control system; simulation experiment; time-delay; Artificial neural networks; Biological neural networks; Educational institutions; Object recognition; PD control; Temperature control; Neural network PID controller; RBF neural network; Rectification column; Simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Design (ISCID), 2013 Sixth International Symposium on
Conference_Location
Hangzhou
Type
conf
DOI
10.1109/ISCID.2013.132
Filename
6804831
Link To Document