Due to the importance of autopilot systems in Micro Aerial Vehicles (MAVs), in this paper first, parametric guidance and control systems are designed, and then they are implemented on a simulated nonlinear six-DOF MAV. The control system is fuzzy-supervisory which its gains are optimized using genetic algorithm. For designing the guidance system, first, two-dimensional (constant height) path following algorithms of vector field and carrot-chasing are developed to 3D algorithms. Then, an optimized 3D fuzzy carrot-chasing guidance system is presented using a combination of the carrot-chasing geometric algorithm, fuzzy logic, and genetic algorithm. Augmentation of the fuzzy logic to the carrot-chasing algorithm, improves its performance significantly. In any autonomous flight maneuver, guidance and control systems affect the performance of the aircraft, simultaneously. So, using a similar control system, the performance of the 3D carrot-chasing algorithm, 3D vector field method, and the proposed 3D fuzzy carrot chasing algorithms are compared with and without applying the wind external disturbance. Results have shown significant superiority of the proposed 3D fuzzy carrot-chasing approach in the horizontal plane of motion and the 3D vector field method in the vertical plane of motion.