Type-2 Fuzzy Basis Functions for Adaptive Control


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Abstract


It has been proven that fuzzy systems called type-1 fuzzy systems can approximate any nonlinear function to any desired accuracy because of the universal approximation theorem. The principal problem encountered with type-1 fuzzy systems is that they can deliver a non satisfactory performance in face of uncertainty and imprecision. In this paper, a type-2 fuzzy membership functions were automatically determined in order to use them in fuzzy systems based on type-2 fuzzy basis functions.
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Keywords


Type-2 Fuzzy Logic; Clustering Algorithm; GKCA Algorithm; Fuzzy Basis Functions; Fuzzy Estimation; Adaptive Control

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