Evolutionary Autopilot Design Approach for UAV Quadrotor by Using GA

This paper presents an off-line design strategy of an intelligent 3D autopilot of Micro-UAV Quadrotor. It consists of hybridization between two fuzzy controllers for the x and y motions and four PID classical controllers for the attitude/altitude motions. Genetic algorithms are used to adapt and optimize the value of the six controllers' parameters to achieve the best performance and decrease the consumed energy. Also, in order to ensure the global optimum control parameters, genetic algorithm named Bi-GA is used to automatically configure the two GAs using for the tuning process. This design strategy can be used to different types of Quadrotor (with cross or X configuration). Initially, in order to get the controller parameters, simulation tests are made on a commercial Quadrotor named AR.Drone V2. Finally, these parameters values are tested in an experiment using the robot operating system. The results of these experimentations confirm the effectiveness of using genetic algorithms in the design of intelligent PID autopilot.