A New Soft Sensing Model of C3Concentration of FCCU Based on Chaos-RBF Neural Network

Author

Shang, Yuqing ; Wang, Xuewu ; Gu, Xingsheng

Author_Institution

Dept. of Electr. Eng., Shanghai Dian-Ji Univ.

Volume

1

fYear

0

fDate

0-0 0

Firstpage

4913

Lastpage

4917

Abstract

Real-time measuring the C₃ concentration is important for the process of fluid catalytic cracking unit (FCCU), but it´s difficult to measure it directly, so soft-sensing method is applied to solve this question. The neural network model based on PCA-RBF and chaos-RBF neural network model are established, and the simulation results are analyzed and compared. The results show that soft sensing model based on chaos-RBF neural network has good precision and quality, and it can meet the demands of process in chemical plant

Keywords

catalysis; chaos; chemical industry; neurocontrollers; oil refining; principal component analysis; radial basis function networks; C₃ concentration; chaos-RBF neural network; chemical plant; fluid catalytic cracking unit; principal component analysis; real-time measurment; soft sensing model; Analytical models; Automation; Chaos; Chemical processes; Distributed control; Electric variables measurement; Intelligent control; Neural networks; Principal component analysis; C; Chaos-RBF; FCCU; Neural network; soft-sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1713319

Filename

1713319