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On Implications and Defuzzification Methods in a Fuzzy Logic C

This paper presents a study on inference in a Fuzzy Logic Controller (FLC). Inference is made up of interpretation, implication, combination and defuzzification. These last two steps can be performed in two sequences. An explanation, through approximate reasoning, on how to implement other than the welìknown Mamdani and Larsen implications is given. (Dis)advantages of several combinations of implication, defuzzification method and sequence are discussed. Differences between FLC’s having either crisp (exact) values or fuzzy sets as nile consequents are studied. To verify this a rotation-translation robot is simulated.