DocumentCode :
1835819
Title :
T-S Fuzzy Modeling Method Based on C-Means Clustering
Author :
Zhang Li ; Han Liang ; Bao Zengjun
Author_Institution :
Sch. of Mech. Electr. & Inf. Eng., Shandong Univ. at Weihai, Weihai, China
Volume :
2
fYear :
2013
fDate :
26-27 Aug. 2013
Firstpage :
230
Lastpage :
232
Abstract :
As complex industrial process with the characteristics of multi-variables, nonlinear, time-varying and large inertia, it is difficult to obtain the satisfactory model by traditional modeling method. In this paper, T-S model between calcination temperature and gas flow is established by applying the T-S fuzzy modeling method. Antecedent and consequent of T-S model are identified apart. Fuzzy c-means clustering algorithm is used to identify antecedent parameter and structure. Consequent parameter is identified by least square method. At last, the effect modeling method is validated by simulation of rotary kiln.
Keywords :
calcination; fuzzy control; fuzzy set theory; industrial control; kilns; least squares approximations; metallurgical industries; multivariable systems; nonlinear systems; pattern clustering; time-varying systems; T-S fuzzy modeling method; antecedent parameter identification; calcination temperature; complex industrial process; consequent parameter identification; effect modeling method; fuzzy c-means clustering algorithm; gas flow; large inertia system; least square method; multivariable system; nonlinear system; rotary kiln simulation; time-varying system; Atmospheric modeling; Calcination; Clustering algorithms; Data models; Kilns; Least squares methods; Mathematical model; Fuzzy c-means clustering; T-S model; calcination process; least square method;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Human-Machine Systems and Cybernetics (IHMSC), 2013 5th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-0-7695-5011-4
Type :
conf
DOI :
10.1109/IHMSC.2013.203
Filename :
6642731
Link To Document :
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