Comparative Study of Fuzzy Controller Optimization with Dynamic Parameter Adjustment Based on Type 1 and Type 2 Fuzzy Logic

Abstract

This paper presents a comparison of fuzzy controller optimization results using dynamic parameter adjustment Type 1 (T1) and Interval Type 2 (T2) fuzzy logic to the Firefly Algorithm (FA). The FA is used for optimizations parameters of the membership functions in the fuzzy controllers. The dynamic adjustment is applied to the randomness parameter of the search space, which represents the exploration of the method, avoiding stagnation or premature convergence. The FA generates the values that the parameters of the membership functions take for optimization use in the fuzzy systems for control. The control plants have one or more input variables that are processed and result in one or more output variables, it would be very difficult to model the human reasoning in equations to achieve a machine acquires the knowledge acquired by humans. For that reason the fuzzy logic that generates that insertion is used as if it were human reasoning.