Quadcopter UAV attitude control based on DDPG

Abstract

Aiming at the problems of difficult implementation and poor robustness of quadrotor UAV attitude control in unknown environment, an intelligent attitude control method based on deep deterministic strategy (DDPG) algorithm is proposed. Firstly, based on the Euler-Poincare equation, the dynamic model of the quadrotor is established by computer symbolic derivation. Secondly, the attitude controller of the quadcopter is designed based on the DDPG algorithm, and the attitude error, attitude angular velocity error and control law penalty items are introduced into the reward function design. Finally, the performance of the controller is verified by setting different initial state values, changing the structural parameters of the quadcopter, and introducing noise. The simulation results show that the controller can guide the quadrotor to respond quickly to the desired attitude and maintain stability, and also show good generalization ability.

Keywords

• quadcopter|dynamic model|deep reinforcement learning|ddpg|attitude control