Clustering based fuzzy controller for speed control of DC motor
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Fuzzy c-means (FCM) Clustering has been used to partition the input-output data and to determine the number of rules. By assuming Gaussian membership function for the premise parts, hybrid learning algorithm is used to update its parameters. This book presents a research work towards the development of a T-S fuzzy model for the speed control of dc motors. To be specific, an attempt is made to design a clustering based fuzzy logic controller for speed control of dc motors. The proposed approach provides a mechanism to obtain the reduced rule-set covering the whole input/output space as well as ...
Fuzzy c-means (FCM) Clustering has been used to partition the input-output data and to determine the number of rules. By assuming Gaussian membership function for the premise parts, hybrid learning algorithm is used to update its parameters. This book presents a research work towards the development of a T-S fuzzy model for the speed control of dc motors. To be specific, an attempt is made to design a clustering based fuzzy logic controller for speed control of dc motors. The proposed approach provides a mechanism to obtain the reduced rule-set covering the whole input/output space as well as the parameters of membership functions for each input variable. The entire system has been modeled using MATLAB 7.0/Simulink toolbox.
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