Comparison Between The Effects Of Different Types Of Membership Functions On Fuzzy Logic For Hydroxy Dry Cell Performance

In this study, hydroxy (HHO) dry cell performances in terms of voltage, current and temperature were modeled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modeling technique. Input parameters plate combination and time, output parameters voltage, current, temperature were described by RBMTF if-the rules. Current, voltage and temperature were measured for the different membership functions. Numerical parameters of input and output variables were fuzzificated as linguistic variables: very very low (L-1), very low (L-2), low (L-3), negative medium (L-4), medium (L-5), positive medium (L-6), high (L-7), very high (L-8) and very very high (L-9) linguistic classes. With the linguistic variables used, rules were obtained for this system. Membership functions (MFs) are the building blocks of fuzzy set theory, i.e., fuzziness in a fuzzy set is determined by its MF. Accordingly, the shapes of MFs are important for a particular problem since they effect on a fuzzy inference system. They may have different shapes like triangular, trapezoidal, Gaussian, etc. The only condition a MF must really satisfy is that it must vary between 0 and 1. This paper presents the performance comparison of fuzzy logic with three different types of membership function.