基于DDPG制导的无人帆船路径跟踪控制OA
Unmanned sailboat path following control based on DDPG guidance
针对传统制导算法未考虑无人帆船迎风换舷和顺风换舷操纵特性,无法有效引导无人帆船在实际海洋风场下沿预定路径实现跟踪任务问题,提出了一种基于深度确定性策略梯度(Deep Deterministic Policy Gradient,DDPG)制导的 DDPG-PID 无人帆船路径跟踪控制算法.将无人帆船航行时的运动状态和位置信息作为制导算法的输入,利用 DDPG 算法的策略网络输出无人帆船参考航向角,使用 PID 算法设计航向控制器实现无人帆船的真实航向对参考航向的有效追踪.考虑无人帆船的操纵特性,设计一种奖励函数,经过神经网络的迭代训练最大化每回合的奖励值.最后,通过仿真对比实验,证明了所提出的 DDPG-PID 算法在无人帆船参考路径跟踪任务中的有效性与可靠性.
Aiming at the problem that the traditional guidance approach does not consider the tacking and gybing maneuvering characteristics of the unmanned sailboat,and cannot complete the path following task under actual ocean wind conditions,a DDPG-PID path following approach for the unmanned sailboat based on the Deep Deterministic Policy Gradient(DDPG)guidance is proposed.The motion state and position information of the unmanned sailboat are taken as the inputs of the guidance algorithm,and the policy network of the DDPG algorithm is utilized to output the reference heading angle of the unmanned sailboat.The heading controller is designed by using the PID algorithm to realize the effective tracking of the actual heading of the unmanned sailboat to the reference.Considering the maneuvering characteristics of the unmanned sailboat,a reward function is designed and the neural networks are iteratively trained to maximize the reward value of each round.Finally,through simulation comparison experiments,the effectiveness and reliability of the proposed DDPG-PID algorithm in the reference path tracking task of unmanned sailboats are verified.
刘方成;邓英杰;徐艺菲;徐开明
燕山大学 机械工程学院,河北 秦皇岛 066004燕山大学 机械工程学院,河北 秦皇岛 066004||燕山大学 起重机械关键技术全国重点实验室,河北 秦皇岛 066004燕山大学 机械工程学院,河北 秦皇岛 066004||燕山大学 起重机械关键技术全国重点实验室,河北 秦皇岛 066004燕山大学 机械工程学院,河北 秦皇岛 066004
交通工程
无人帆船DDPG 算法路径跟踪操纵特性
unmanned sailboatsDDPG algorithmpath followingmaneuvering characteristics
《燕山大学学报》 2026 (3)
231-240,249,11
国家自然科学基金资助项目(52101375)河北省自然科学基金资助项目(E2024203179,E2022203088)河北省创新能力提升计划项目(24461901D)
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