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基于DDPG的四旋翼无人机姿态控制

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针对未知环境下四旋翼无人机姿态控制实现难、鲁棒性差等问题,提出了基于深度确定性策略(DDPG)算法的智能姿态控制方法.首先,基于欧拉-庞卡莱方程,利用计算机符号推导,建立四旋翼的动力学模型;其次,基于DDPG算法设计四旋翼的姿态控制器,并在奖励函数设计中引入姿态误差、姿态角速度误差和控制量惩罚项;最后,通过设置不同初始状态值、改变四旋翼结构参数和引入噪声等仿真试验,分析验证控制器的性能.仿真结果表明,该控制器能够引导四旋翼快速响应到期望姿态并保持稳定,同时展现出较好的泛化能力.
Quadcopter UAV attitude control based on DDPG
Aiming at the problems of difficult implementation and poor robustness of quadrotor UAV attitude control in un-known environment,an intelligent attitude control method based on deep deterministic strategy(DDPG)algorithm is pro-posed.Firstly,based on the Euler-Poincare equation,the dynamic model of the quadrotor is established by computer symbol-ic 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.

quadcopterdynamic modeldeep reinforcement learningDDPGattitude control

黄希杰

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陆军指挥学院, 江苏 南京 210045

四旋翼 动力学模型 深度强化学习 DDPG 姿态控制

2024

指挥控制与仿真
中国船舶重工集团公司 第七一六研究所

指挥控制与仿真

CSTPCD
影响因子:0.309
ISSN:1673-3819
年,卷(期):2024.46(2)
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