A PSO-based approach to optimize the triangular membership functions in a fuzzy logic controller
Vincenzo Maniscalco, Francesco Paolo Lombardo · AIP conference proceedings · 2017
In this paper a Particle Swarm Optimization (PSO) algorithm is considered in order to optimize the triangular Membership Functions (MF) in a Fuzzy Logic Controller (FLC). PSO algorithm belongs to the class of Swarm Intelligence (SI) techniques and is considered an efficient heuristic technique for optimization problem in a continuous and multidimen-sional search spaces. Performance of a FLC depends on the fuzzy partition of each input/output space considered and the PSO algorithm can be used to obtain the optimal or near optimal parameters of the triangular membership functions in order to achieve the best results in the defuzzification process. Simulation results obtained by this approach to tune the triangular membership functions of a FLC for an application concerning the optimization of the energy consumption in Industrial Wireless Sensor Networks (IWSN) are reported.