A fuzzy knowledge base to support routine engineering design
Fuzzy Sets and Systems
The application of fuzzy logic in automatic modelling of electromechanical systems
Fuzzy Sets and Systems
Fuzzy Modeling for Control
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The extraction of fuzzy information out of raw data is very important and contains saving potential for science and engineering applications. The fuzzy models from this information can be used for different purposes in various applications because of their transparecy. A number of techniques have been introduced to construct fuzzy models from measured data. Relatively little attention has been devoted to the identification of Multi Input Multi Output (MIMO) fuzzy models from input-output data. This paper concentrates on the fuzzy modeling and identification of MIMO systems by TS (Takagi-Sugeno) fuzzy models. In this paper product-space fuzzy clustering with adaptive distance measure named as Gustafson-Kessel (GK) algorithm is used. With this approach, the knowledge of the physical structure can be easily incorporated in the structure of the model. Implementation in the MATALAB is briefly described with simulation examples.