基于动态规划制导的无人艇自主回收控制方法  

Autonomous recovery control method for USV based on dynamic programming guidance

作　　者：郭文轩 李子豪 唐国元[1] 王泉斌[2] 孙江龙[1] 马杰[3] 乔瑜[4] GUO Wenxuan;LI Zihao;TANG Guoyuan;WANG Quanbin;SUN Jianglong;MA Jie;QIAO Yu(School of Naval Architecture and Ocean Engineering,Huazhong University of Science and Technology,Wuhan 430074,China;China Ship Development and Design Center,Wuhan 430064,China;School of Artificial Intelligence and Automation,Huazhong University of Science and Technology,Wuhan 430074,China;School of Energy and Power Engineering,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]华中科技大学船舶与海洋工程学院,湖北武汉430074 [2]中国舰船研究设计中心,湖北武汉430064 [3]华中科技大学人工智能与自动化学院,湖北武汉430074 [4]华中科技大学能源与动力工程学院,湖北武汉430074

出　　处：《中国舰船研究》2024年第1期264-271,共8页Chinese Journal of Ship Research

基　　金：“慧眼行动”创新成果转化应用资助项目(626020204)。

摘　　要：[目的]针对欠驱动无人艇(USV)自主回收的需求,提出一种基于动态规划制导的跟踪控制方法。[方法]在运动学层面,将平行接近制导(CB)与动态窗口算法(DWA)相结合,引导USV实现目标跟踪与动态避障;在动力学层面,针对模型参数及回收环境的不确定性,采用径向基函数神经网络(RBFNN)设计动力学滑模控制器,实现对制导输出的跟踪控制。随后,采用Lyapunov理论对系统的稳定性进行分析。[结果]仿真结果表明,所提方法使USV具备了稳定跟踪性能,可有效规避回收过程中的动态障碍,并能自适应估计模型中的不确定因素和未知的环境干扰。[结论]所提方法展现出较强的鲁棒性与灵活性,可为USV在动态环境下的回收进行制导与目标跟踪提供参考。[Objective]This paper presents a tracking control method based on dynamic programming guidance to address the challenges presented by the autonomous recovery of underactuated unmanned surface vehicles(USVs).[Methods]At the kinematic level,constant bearing approach(CB)guidance is combined with a dynamic window algorithm(DWA)to guide the USV in achieving target tracking and dynamic obstacle avoidance.At the dynamic level,considering the uncertainties in the model parameters and recovery environment,a radial basis function neural network(RBFNN)is employed to design a dynamic sliding mode controller for the tracking control of the guidance output.Finally,the stability of the system is analyzed using Lyapunov theory.[Results]The simulation results demonstrate that the proposed method enables the USV to exhibit stable tracking performance,effectively avoid dynamic obstacles during the recovery process and adapt to uncertain factors in the estimation model and unknown environmental disturbances.[Conclusion]The proposed method exhibits strong robustness and flexibility,providing valuable references for the guidance and target tracking of USVs during recovery in dynamic environments.

关 键 词：欠驱动无人艇 平行接近制导 动态窗口法 神经网络 滑模控制 

分 类 号：U664.82[交通运输工程—船舶及航道工程]