optimization of fuzzy membership functions via pso and ga with application to quad rotor

quad rotor is a renowned underactuated unmanned aerial vehicle (uav) with widespread military and civilian applications. despite its simple structure, the vehicle suffers from inherent instability. therefore, control designers always face formidable challenge in stabilization and control goal. in this paper fuzzy membership functions of the quad rotor’s fuzzy controllers are optimized using nature-inspired algorithms such as particle swarm optimization (pso) and genetic algorithm (ga). finally, the results of the proposed methods are compared and a trajectory is defined to verify the effectiveness of the designed fuzzy controllers based on the algorithm with better results.