DocumentCode :
1694532
Title :
On the combination of fuzzy models
Author :
Kumar, Mohit ; Stoll, Norbert ; Thurow, Kerstin ; Stoll, Regina
Author_Institution :
Center for Life Sci. Autom., Rostock, Germany
fYear :
2011
Firstpage :
322
Lastpage :
326
Abstract :
The combination of fuzzy models could be an effective way to improve system performance. This text proposes a fuzzy approach to the combination of fuzzy models, i.e., the different fuzzy models are combined using a fuzzy rule-based model. The combining fuzzy model is identified using an algorithm that is stable towards disturbances. The combination approach provides simultaneously the benefits of the individual components and thus improves overall performance. The combination scheme could be used to resolve the issue of choice of performance deciding parameters (e.g. learning rate).
Keywords :
fuzzy set theory; fuzzy approach; fuzzy models combination; fuzzy rule based model; Adaptation models; Data models; Indexes; Measurement uncertainty; Nonlinear systems; Robustness; Stability criteria;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation Science and Engineering (CASE), 2011 IEEE Conference on
Conference_Location :
Trieste
ISSN :
2161-8070
Print_ISBN :
978-1-4577-1730-7
Electronic_ISBN :
2161-8070
Type :
conf
DOI :
10.1109/CASE.2011.6042461
Filename :
6042461
Link To Document :
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