DocumentCode :
2736983
Title :
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
Link To Document :
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