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