Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/26542
Title: Linguistic Fuzzy Modeling for Industrial Applications
Authors: Singh, Nirmal
Vig, Renu
Sharma, J K
Issue Date: Nov-2001
Publisher: NISCAIR-CSIR, India
Abstract: The extraction of fuzzy information from raw data is important and contains savings potential in industrial applications. A general approach to linguistic modeling based on fuzzy logic has been presented. A fuzzy inference algorithm or mechanism is necessary to use linguistic model. Such a mechanism enables computation of output value, given some input values. The maxmin (Mamdani) inference algorithm for linguistic modeling has been considered, and its implementation is illustrated, using MATLAB package. The linguistic fuzzy models can be used for different purposes because of their transparency and can also be used in industrial applications, which are partly described by first principle model s and partly by experience contained in designers, operators and other workers. An example of linguistic fuzzy modeling for simple industrial application of heating power of a gas burner has been presented to illustrate the proposed model and method of computation.
Page(s): 851-859
URI: http://hdl.handle.net/123456789/26542
ISSN: 0975-1084 (Online); 0022-4456 (Print)
Appears in Collections:JSIR Vol.60(11) [November 2001]

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