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Fuzzy Model Identification & Control of Non-Linear Systems
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This book presents a research work towards the Identification and Control of Non-Linear Systems based on Fuzzy Models approach. A TS fuzzy model has been implemented successfully to a known benchmark problem of the identification of non-linear plant data. FCM Clustering based approach has been used for the classification of input -output data points. After clustering gradient descent method is used for the learning of parameters. It has also been implemented on a real data problem which is a model of an operator's control of a chemical plant and the accuracy was comparable to the results reported in the literature. The entire system has been modeled using MATLAB 7.0/Simulink toolbox.
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