农业机械学报2026，Vol.57Issue(19)：54-62,202,10.DOI:10.6041/j.issn.1000-1298.2026.19.005
基于数据-物理双驱动的强化学习无人船航迹跟踪控制
Reinforcement Learning-based Trajectory Tracking Control for Unmanned Surface Vessels via Data-Physics Dual-driven Approach
摘要
Abstract
A data-physics dual-driven(DPD)reinforcement learning(RL)-based optimal control method considering input constraints and external environmental disturbances was proposed for unmanned surface vessels(USVs)applied in intelligent marine ranching.Firstly,to address the challenges of modeling USVs'unknown dynamics and insufficient interpretability of traditional data-driven methods,a DPD model was constructed by integrating the physical laws of ship dynamics with the data learning capability of recurrent neural networks(RNN),enabling accurate reconstruction of unknown complex dynamic characteristics and enhancing the model's physical interpretability.Secondly,a control framework was designed via the combination of backstepping and optimal control methods.An RL-based optimal control strategy was proposed to improve the USVs'continuous interaction capability with complex marine environments,achieving a dynamic balance between tracking accuracy and control resource consumption.Meanwhile,the physical constraints imposed by the hull's load-bearing capacity on control inputs were incorporated into the controller design.Thirdly,the uniform ultimate boundedness(UUB)of all signals in the closed-loop system was proved by using Lyapunov stability theory.Finally,comparative simulation results under Level 2 sea conditions demonstrated that the proposed method improved tracking accuracy by 42.6%compared with the physics-principle-driven(PPD)method,and reduced control input cost by 26.9%relative to the PPD method and 9.6%compared with traditional backstepping control,which fully verified the effectiveness and superiority of the proposed method.关键词
无人船/航迹跟踪/输入约束/强化学习/数据-物理双驱动Key words
unmanned surface vessels/trajectory tracking/input constraints/reinforcement learning/data-physics dual-driven分类
信息技术与安全科学引用本文复制引用
白伟伟,雷家虎,林玉芳,李荣辉..基于数据-物理双驱动的强化学习无人船航迹跟踪控制[J].农业机械学报,2026,57(19):54-62,202,10.基金项目
国家自然科学基金项目(52271360、52571405)、兴辽英才计划项目(XLYC2403032)、辽宁省自然科学基金项目(2025-MS-093)和辽宁省科技计划联合计划项目(重点研发计划项目)(2025JH2/101800233) （52271360、52571405）
