In this project two Fuzzy control algorithms, which deal with the issue of control from two different perspectives, are utilized to control the attitude of a Quadrotor. In the first algorithm which is known as Parallel Distributed Compensation fuzzy controller (PDC), the process of designing the controller begins with the fuzzy identification of the system and by utilizing the idea of parallel distributed compensation a nonlinear model-based fuzzy controller is provided. The second algorithm which is known as Self Organizing Controller (SOC), a nonlinear adaptive fuzzy controller is initiated with just preliminary knowledge of the system and is trained by assessing its performance over the time. The practical results of the first algorithm imply that it successfully controls the Quadrotor with just eight fuzzy control rules. The second algorithm which has no dependency on the exact dynamic model of the Quadrotor, trains a fuzzy controller in a few minutes with tremendous performance.