OPTIMUM SYNTHESIS OF FUZZY LOGIC CONTROLLER FOR TRAJECTORY TRACKING BY DIFFERENTIAL EVOLUTION
Abstract Differential Evolution (DE) and Genetic Algorithms (GA) are population based search algorithms that come under the category of evolutionary optimization techniques. In the present study, these evolutionary methods have been utilized to conduct the optimum design of a fuzzy controller for mobile robot trajectory tracking. Comparison between their performances has also been conducted. In this paper, we will present a fuzzy controller to the problem of mobile robot path tracking for a CEDRA rescue robot. After designing the fuzzy tracking controller, the membership functions will be optimized by evolutionary algorithms in order to obtain more acceptable results.
In this paper a study for very high efficiency targeting 99 % range converter is described. We have proposed a new soft switching boost type chopper based on snubber assisted zero voltage and zero current transition (SAZZ) with output diode fabricated “SiC schottky diode”. The output power of 8 kW with the efficiency of 98.96% was obtained. The loss breakdown evaluation of SiC-SAZZ is discussed.