Dynamic tuning of parameterized defuzzification methods applied to automatic control and diagnosis

Tuning parameterized defuzzification methods by dynamically adjusting parameters values according to dynamic changes in the environment have proven successful in optimizing fuzzy systems. This paper illustrates the techniques involved by discussing examples of dynamically tuning of one type of parameterized defuzzification method, those based on the basic defuzzification distribution (BADD) method. An application of dynamic tuning of parameterized defuzzification in optimizing automatic control and diagnostic systems which use fuzzy reasoning underline the potential offered by this technique in coping with complex tasks.

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