[1]LIAO Qian-fang,LI Ning,LI Shao-yuan.A TypeⅡ TS fuzzy modeling method for datadriven approaches[J].CAAI Transactions on Intelligent Systems,2009,4(4):303-308.
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A TypeⅡ TS fuzzy modeling method for datadriven approaches

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 4 Number of periods: 2009 4 Page number: 303-308 Column: 学术论文—人工智能基础 Public date: 2009-08-25
Title:
A TypeⅡ TS fuzzy modeling method for datadriven approaches
Author(s):
LIAO Qian-fang;  LI Ning;  LI Shao-yuan
chool of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Keywords:
TypeⅡ fuzzy;  TS fuzzy model;  datadriven;  pH neutralization process
CLC:
TP273
DOI:
-
Abstract:
Data collected from the field inevitably contains uncertainties such as noise or other disturbances; mathematical models established with datadriven approach must possess strong capability to deal with the influence of uncertainties. Following analysis of current methods for typeI TakagiSugeno (TS) fuzzy modeling, a method suitable for typeⅡ TS fuzzy modeling was proposed. In the data driven modeling process, the influence of the degree of uncertainty was determined by analysis of the collected data. On the basis of the typeI fuzzy model, for antecedent parameters, we employed the fuzzy set of the typeⅡ fuzzy model to replace the counterpart from the typeⅠ model . But for consequent parameters, we took typeI fuzzy sets to replace crisp numbers. This produced an improved typeⅡ TS fuzzy model. Finally, a pH neutralization process was taken as an example to verify the proposed mathematical model. Simulation results showed that this method can handle the influence of uncertainties better and achieves higher accuracy.
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