An Optimized Interval Type-2 Fuzzy Logic Control Scheme based on Optimal Defuzzification

In this paper, a new way of optimizing fuzzy logic is introduced. This way is used to optimize the output of Interval Type-2 Fuzzy Logic controller by replacing the Defuzzification stage by the Optimization algorithm. The algorithm chooses the best crisp output variable from the type-reduced set which is the output of the Type-Reduction stage instead of averaging the set extremes which was performed by Defuzzification stage. Artificial Bee Colony optimization algorithm is used to optimize the Interval Type-2 Fuzzy Logic controller to manage the navigation of multiple mobile robots in indoor environments