Fuzzy PD control for a quadrotor with experimental results

Quadrotor is an unmanned aerial vehicle widely used in traffic construction monitoring, volcano monitoring, forest fire, power line inspection, missing person search and disaster relief. The dynamic model of quadrotor becomes complex and non-linear due to four motors with four propellers to control and stabilize the motion. One disadvantage of the traditional PID controller is that its parameters are tuned based on trials and errors, but the fuzzy PID controller will automatically adjust its PID gains based on the IF-THEN rules and the parameters of the fuzzy systems are designed beforehand. For other adaptive fuzzy controllers, their parameters are online updated with large computational load. In this paper, we design an intelligent controller to manage the operating state of quadrotor (UAV) by combining the advantages of traditional PD controller with fuzzy logic inference systems to tune its parameters. These Fuzzy PD controllers performs control of the movement of the quadrotor along three axes to follow the desired trajectory. The proposed Fuzzy PD control system for the quadrotor is simulated and evaluated on Matlab-Simulink, then conducted with real-time experiments on QDrone2 physical system. Simulation and experimental results with comparisons to the PD controller have proven the effectiveness of the proposed control method with small tracking error under the impact of time-varying disturbance and additional load.