Title :
A fuzzy identification algorithm for NARMAX model and its application to the estimation of oxygen concentration
Author :
Sun, Dazhong ; Ye, Fangjun ; Gu, Xingsheng
Author_Institution :
Res. Inst. of Autom., East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
The continuous catalytic reforming system is an important process in petroleum refineries, and the estimation of oxygen concentration plays an important role in refinery enterprises. In this paper, based on the Takagi-Sugeno fuzzy inference system, a NARMAX model is built for a multi-input single-output system of oxygen concentration in a catalytic reformer. 21 variables are chosen as secondary variables related to oxygen concentration for the continuous catalytic reforming system, and PCA is used to treat the sample data to build the fuzzy model in order to reduce some redundant information. The practical operational data is used to build the estimation model of oxygen concentration, and the simulation results are very satisfactory.
Keywords :
catalysis; chemical variables measurement; fuzzy control; identification; inference mechanisms; multivariable control systems; oil refining; oxygen; principal component analysis; NARMAX model; PCA; Takagi-Sugeno fuzzy inference system; catalytic reforming system; fuzzy identification algorithm; multiinput single-output system; oxygen concentration estimation; petroleum refineries; Autoregressive processes; Equations; Function approximation; Fuzzy sets; Fuzzy systems; Nonlinear dynamical systems; Nonlinear systems; Oxygen; Refining; Takagi-Sugeno model;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343186
