海洋环境复杂多变，若无人艇编队不能快速调整航向或速度，易致队形破坏、失控，增加碰撞风险。为提升编队任务效能、规避航行碰撞风险，提出基于电力推进的无人艇编队协同航行控制方法。构建领航与跟随无人艇控制函数，结合人工势场法实现避碰，将控制指令转化为电力推进系统电压信号，再经直流电动机模型及螺旋桨水动力模型，完成从电压信号到推进动力的转换，确保编队能依实时环境动态调整动力，维持航行稳定高效。实验表明，该方法可按领航与跟随无人艇运动需求产生相应螺旋桨推力，维持编队协同航行，助其抵达目标点，航行中保持队形完整，成功避障且避免编队内碰撞。
The marine environment is complex and ever-changing. If unmanned boat formations cannot quickly adjust their heading or speed, it can easily cause formation damage, loss of control, and increase the risk of collisions. To improve the efficiency of formation missions and avoid collision risks during navigation, a coordinated navigation control method for unmanned boat formations based on electric propulsion is proposed. Constructing control functions for navigation and following unmanned boats, combined with artificial potential field method to achieve collision avoidance, converting control instructions into voltage signals of the electric propulsion system, and then completing the conversion from voltage signals to propulsion power through DC motor model and propeller hydrodynamic model, ensuring that the formation can dynamically adjust power according to real-time environment and maintain stable and efficient navigation. Experiments have shown that this method can generate corresponding propeller thrust according to the requirements of navigation and following the motion of unmanned boats, maintain coordinated navigation of the formation, help them reach the target point, maintain the integrity of the formation during navigation, successfully avoid obstacles and avoid collisions within the formation.
2025,47(21): 89-94 收稿日期：2025-6-3
DOI：10.3404/j.issn.1672-7649.2025.21.015
分类号：U675.91
基金项目：武汉交通职业学院校本研究项目（JB2024011）
作者简介：师光飞(1979-),男,硕士,副教授,研究方向为船舶电气与自动化
参考文献：
[1] 王艺凯, 孙俊, 王偲. 欠驱动无人艇集群协同编队路径规划仿真[J]. 计算机仿真, 2023, 40(6): 485-490.
WANG Y K, SUN J, WANG S. Simulation of path planning for under-driven unmanned surface vehicle cluster cooperative formation[J]. Computer Simulation, 2023, 40(6): 485-490.
[2] 丁明, 王磊, 丁英, 等. 一种无需指定船舶位置的新型船舶大规模自主编队方法[J]. 中国舰船研究, 2024, 19(1): 191-199.
DING M, WANG L, DING Y, et al. A novel approach to large-scale autonomous formation of ships without specifying ship positions [J]. Chinese Journal of Ship Research, 2024, 19(1): 191-199.
[3] 任璐, 柯亚男, 柳文章, 等. 基于优势函数输入扰动的多无人艇协同策略优化方法[J]. 自动化学报, 2025, 51(4): 824-834.
REN L, KE Y N, LIU W Z, et al. Multi-USVs cooperative policy optimization method based on disturbed input of advantage function[J]. Acta Automatica Sinica, 2025, 51(4): 824-834.
[4] 陈浩宇, 徐海祥, 魏骁, 等. 基于KFESO的多无人艇分布式协同路径跟踪复合抗扰控制[J]. 中国舰船研究, 2025, 20(1): 191-202.
CHEN H Y, XU H X, WEI X, et al. KFESO-based composite anti-disturbance control for distributed cooperative path following of unmanned surface vehicles[J]. Chinese Journal of Ship Research, 2025, 20(1): 191-202.
[5] 刘昊, 张云飞, 赵继成. 基于局部感知的无人艇集群过复杂障碍场方法[J]. 系统工程与电子技术, 2024, 46(8): 2829-2840.
LIU H, ZHANG Y F, ZHAO J C. Formation control of unmanned surface vehicle swarm in dense environment based on local perception[J]. Systems Engineering and Electronics, 2024, 46(8): 2829-2840.
[6] 王义轩, 李擎, 姚其家, 等. 多无人艇固定时间自适应分布式协同编队控制[J]. 工程科学学报, 2024, 46(10): 1880-1888.
WANG Y X, LI Q, YAO Q J, et al. Fixed-time adaptive distributed cooperative formation control for multiple unmanned surface vessels[J]. Chinese Journal of Engineering, 2024, 46(10): 1880-1888.
[7] 王宁, 王仁慧, 鲁挺. 推进器饱和约束的水面无人艇固定时间精准跟踪控制[J]. 控制理论与应用, 2023, 40(1): 55-64.
WANG N, WANG R H, LU T. Fixed-time precision tracking control of an unmanned surface vehicle constrained by thruster saturations[J]. Control Theory & Applications, 2023, 40(1): 55-64.
[8] 王广旭, 蔡伟, 李永琪, 等. 含不确定动态观测的异构无人舰艇系统固定时间编队控制[J]. 电光与控制, 2025, 32(5): 103-110.
WANG G X, CAI W, LI Y Q, et al. Fixed-time formation control for heterogeneous usvs with uncertain dynamic observations[J]. Electronics Optics & Control, 2025, 32(5): 103-110.
[9] 游旭, 刘佳仑, 马枫, 等. 异构船舶编队航行的研究现状与技术展望[J]. 哈尔滨工程大学学报, 2023, 44(1): 11-22.
YOU X, LIU J L, MA F, et al. Analysis and strategy development for the navigation of heterogeneous ship formations[J]. Journal of Harbin Engineering University, 2023, 44(1): 11-22.
[10] 宁君, 彭周华, 李铁山, 等. 带有输入量化的分布式多无人船舶自适应模糊编队控制[J]. 控制与决策, 2024, 39(8): 2588-2596.
NING J, PENG Z H, LI T S, et al. Fuzzy-adaptive distributed formation control of unmanned surface vehicles with input quantization[J]. Control and Decision, 2024, 39(8): 2588-2596.
