欠驱动多AUV双环指定时间三维编队控制

王则青; 徐海祥; 余文曌; 杜哲; 王红梅

doi:10.12382/bgxb.2025.0046

您当前的位置：

首页 >

文章列表页 >

欠驱动多AUV双环指定时间三维编队控制

更新时间：2025-09-25

- 欠驱动多AUV双环指定时间三维编队控制
- Dual-Loop Prescribed-Time 3D Formation Control of Underactuated Multi-AUVs
- 兵工学报 2025年46卷第8期页码：250046
- 作者机构：
  
  1. 武汉理工大学高性能船舶技术教育部重点实验室, 湖北武汉 430063
  2. 武汉理工大学船海与能源动力工程学院, 湖北武汉 430063
- 作者简介：
  
  *wzyu@whut.edu.cn
- 基金信息：
  
  国家自然科学基金项目(52201373);中国国家留学基金青年骨干教师出国研修项目(202306950131);国家大学生创新创业训练计划资助项目(202410497109)
- DOI：10.12382/bgxb.2025.0046
  中图分类号：
- 收稿：2025-01-13，
  
  网络首发：2025-08-28，
  
  纸质出版：2025-08-31
- 稿件说明：
移动端阅览
王则青, 徐海祥, 余文曌, 等. 欠驱动多AUV双环指定时间三维编队控制[J]. 兵工学报, 2025,46(8):250046.

Zeqing WANG, Haixiang XU, Wenzhao YU, et al. Dual-Loop Prescribed-Time 3D Formation Control of Underactuated Multi-AUVs[J]. Acta Armamentarii, 2025, 46(8): 250046.
王则青, 徐海祥, 余文曌, 等. 欠驱动多AUV双环指定时间三维编队控制[J]. 兵工学报, 2025,46(8):250046. DOI： 10.12382/bgxb.2025.0046.

Zeqing WANG, Haixiang XU, Wenzhao YU, et al. Dual-Loop Prescribed-Time 3D Formation Control of Underactuated Multi-AUVs[J]. Acta Armamentarii, 2025, 46(8): 250046. DOI： 10.12382/bgxb.2025.0046.

摘要

多自主水下航行器(Autonomous Underwater Vehicles

AUV)协同作业在水下作战领域展现出广阔的应用前景。针对具有模型不确定性和未知环境扰动的欠驱动多AUV三维编队控制问题

提出一种双环指定时间编队控制方法。为解决AUV欠驱动问题

建立AUV运动数学模型并引入欠驱动坐标变换。为降低模型不确定性和未知环境扰动对系统的不利影响

设计固定时间扩张状态观测器对其进行估计与补偿。为实现多AUV编队的指定时间收敛

设计由外环控制律与内环控制律组成的双环指定时间控制器。其中

外环控制律调节AUV的期望速度以实现编队目标

而内环控制律则负责跟踪AUV的期望速度。理论分析表明

新方法能够确保系统在指定时间内收敛;仿真结果显示

与有限时间和固定时间控制相比

新方法能够实现系统的指定时间收敛

进一步提高系统的收敛速度

为协同性要求较高任务下的多AUV编队控制提供新思路。

Abstract

The cooperative operation of multiple autonomous underwater vehicles (AUVs) shows broad application prospects in underwater combat scenarios.A dual-loop prescribed-time formation control method is proposed for the control of underactuated multi-AUV three-dimensional formation under model uncertainties and unknown environmental disturbances.A mathematical model of AUV motion is established and an underactuated coordinate transformation is introduced to solve the underactuation problem of AUV.To mitigate the adverse effects of model uncertainty and unknown environmental disturbances on the system

a fixed-time extended state observer is designed to estimate and compensate for model uncertainty and unknown environmental disturbances.In order to achieve the prescribed-time convergence in multi-AUV formation

a dual-loop prescribed-time controller

consisting of an outer-loop control law and an inner-loop control law

is designed.The outer-loop control law is used to adjust the desired velocity of AUV to achieve the formation objective

while the inner-loop control law is responsible for tracking the desired velocity.Theoretical analysis demonstrates that the proposed method enable the system to converge within a prescribed time.+++Simulated results show that

compared to the finite-time and fixed-time control methods

the proposed method can achieve prescribed-time convergence and further enhances the system's convergence speed

providing a new approach for multi-AUV formation control in tasks with high coordination requirements.

关键词

Keywords

references

黄琰 , 李岩 , 俞建成 , 等 . AUV智能化现状与发展趋势 [J ] . 机器人 , 2020 , 42 ( 2 ): 215 - 231 . DOI: 10.13973/j.cnki.robot.190392 http://doi.org/10.13973/j.cnki.robot.190392 归纳总结了国内外AUV单体平台与人工智能方法相结合的主要成果．从探测感知、航行控制决策、路径规划、故障诊断等核心技术环节进行深入剖析，探讨了人工智能方法在AUV典型作业场景下的应用．最后，指出了AUV的智能化发展趋势．

HUANG Y , LI Y , YU J C , et al . State-of-the-art and development trends of AUV intelligence [J ] . Robot , 2020 , 42 ( 2 ): 215 - 231 . (in Chinese) DOI: 10.13973/j.cnki.robot.190392 http://doi.org/10.13973/j.cnki.robot.190392 The state-of-the-art of the AUV (autonomous underwater vehicle) incorporating the artificial intelligence methods at home and abroad are summarized. A number of core technologies are analyzed, including detection and perception, control decision in navigation, path planning and fault diagnosis, and the applications of the artificial intelligence methods in AUV typical application scenarios are investigated. Finally, the intelligence development trends of AUV are pointed out.

智达 . 国外海军无人潜航器发展综述 [J ] . 船舶工程 , 2022 , 44 ( 8 ): 170 - 172 .

ZHI D . Review of the development of foreign naval unmanned underwater vehicles [J ] . Ship Engineering , 2022 , 44 ( 8 ): 170 - 172 . (in Chinese)

王童豪 , 彭星光 , 胡浩 , 等 . 海上有人/无人协同系统及其关键技术综述 [J ] . 兵工学报 , 2024 , 45 ( 10 ): 3317 - 3340 . DOI: 10.12382/bgxb.2024.0327 http://doi.org/10.12382/bgxb.2024.0327 海上有人/无人协同系统对进一步提升海军作战效能有重要作用,是现代海军装备发展的重要方向。立足未来海上作战,以海上有人/无人协同系统的实际应用为牵引,综述国外相关项目发展现状,厘清海上有人/无人协同系统的主要特点,凝练并分析其中科学问题与关键技术,总结海上有人/无人协同系统的发展方向、矛盾与挑战。未来,智能化、模块化和稀疏化将成为海上有人/无人协同系统的重要发展方向,但由于系统自主性与可控性间、智能化发展与海上约束间、海上有人/无人协同特点与现有协同任务体系间存在一定的发展矛盾,故系统还将面临系统规模、平台多样性、系统安全性及信息化与智能化等方面的发展挑战。

WANG T H , PENG X G , HU H , et al . Maritime manned/unmanned collaborative systems and key technologies:a survey [J ] . Acta Armamentarii , 2024 , 45 ( 10 ): 3317 - 3340 . (in Chinese)

张鑫明 , 韩明磊 , 余益锐 , 等 . 潜艇与UUV协同作战发展现状及关键技术 [J ] . 水下无人系统学报 , 2021 , 29 ( 5 ): 497 - 508 .

ZHANG X M , HAN M L , YU Y R , et al . Development and key technologies of submarine-UUV cooperative operation [J ] . Journal of Unmanned Undersea Systems , 2021 , 29 ( 5 ): 497 - 508 . (in Chinese)

崔云菲 . 多无人水下航行器自抗扰编队包含控制方法研究 [D ] . 哈尔滨 : 哈尔滨工程大学 , 2024 : 3 - 4 .

CUI Y F . Research on Anti-disturbance formation containment control for multiple unmanned underwater vehicles [D ] . Harbin : Harbin Engineering University , 2024 : 3 - 4 . (in Chinese)

ER M J , GONG H B , LIU Y , et al . Intelligent trajectory tracking and formation control of underactuated autonomous underwater vehicles:a critical review [J ] . IEEE Transactions on Systems Man Cybernetics-Systems , 2024 , 54 ( 1 ): 543 - 555 .

DU H B , WEN G H , WU D , et al . Distributed fixed-time consensus for nonlinear heterogeneous multi-agent systems [J ] . Automatica , 2020 , 113 : 108797 .

NGO A T , PHAM N N T , HO P H A . Adaptive finite-time leader-follower formation control for multiple AUVs regarding uncertain dynamics and disturbances [J ] . Ocean Engineering , 2023 , 269 : 113503 .

LI J , TIAN Z Y , ZHANG H H , et al . Robust finite-time control of a multi-AUV formation based on prescribed performance [J ] . Journal of Marine Science and Engineering , 2023 , 11 ( 5 ): 897 .

LI L N , LIU Z X , GUO S F , et al . Adaptive practical predefined-time control for uncertain teleoperation systems with input saturation and output error constraints [J ] . IEEE Transactions on Industrial Electronics , 2024 , 71 ( 2 ): 1842 - 1852 .

POLYAKOV A . Nonlinear feedback design for fixed-time stabilization of linear control systems [J ] . IEEE Transactions on Automatic Control , 2012 , 57 ( 8 ): 2106 - 2110 .

LI X J , QIN H D , LI L Y . Fixed-time formation control for AUVs with unknown actuator faults based on lumped disturbance observer [J ] . Ocean Engineering , 2023 , 269 : 113495 .

王静耀 , 杜佳璐 . 欠驱动AUV分布式事件触发固定时间三维编队控制 [J ] . 控制与决策 , 2025 , 40 ( 1 ): 231 - 241 .

WANG J Y , DU J L . Distributed event-triggered fixed-time 3-D formation control of underactuated AUVs [J ] . Control and Decision , 2025 , 40 ( 1 ): 231 - 241 . (in Chinese)

HOLLOWAY J , KRSTIC M . Prescribed-time output feedback for linear systems in controllable canonical form [J ] . Automatica , 2019 , 107 : 77 - 85 .

黄秀颖 , 刘海涛 , 田雪虹 . 基于输入饱和的欠驱动水面舰艇预定义时间跟踪控制 [J ] . 中国舰船研究 , 2024 , 19 ( 1 ): 98 - 110 .

HUANG X Y , LIU H T , TIAN X H . Predefined time tracking control of underactuated surface vessel with input saturation [J ] . Chinese Journal of Ship Research , 2024 , 19 ( 1 ): 98 - 110 . (in Chinese)

YANG T T , ZHANG P F , CHEN H Y . Distributed prescribed-time leader-follower formation control of surface vehicles with unknowns and input saturation [J ] . ISA Transactions , 2023 , 124 : 16 - 27 .

YAN Z P , GONG P , ZHANG W , et al . Model predictive control of autonomous underwater vehicles for trajectory tracking with external disturbances [J ] . Ocean Engineering , 2020 , 217 : 107884 .

XIA G Q , ZHANG Y , ZHANG W , et al . Dual closed-loop robust adaptive fast integral terminal sliding mode formation finite-time control for multi-underactuated AUV system in three dimensional space [J ] . Ocean Engineering , 2021 , 233 : 108903 .

CHEN H X , TANG G Y , WANG S F , et al . Adaptive fixed-time backstepping control for three-dimensional trajectory tracking of underactuated autonomous underwater vehicles [J ] . Ocean Engineering , 2023 , 275 : 114109 .

HUA C C , NING P J , LI K . Adaptive prescribed-time control for a class of uncertain nonlinear systems [J ] . IEEE Transactions on Automatic Control , 2022 , 67 ( 11 ): 6159 - 6166 .

YANG Y N , LIU X S , ZENG X D . Dynamic event-triggered prescribed-time zero-error tracking control for non-strict feedback nonlinear systems [J ] . Nonlinear Dynamics , 2025 , 113 ( 1 ): 567 - 581 .

WANG T Q , LIU Y T , ZHANG X F . Extended state observer-based fixed-time trajectory tracking control of autonomous surface vessels with uncertainties and output constraints [J ] . ISA Transactions , 2022 , 128 : 174 - 183 .

LI J H . 3D trajectory tracking of underactuated non-minimum phase underwater vehicles [J ] . Automatica , 2023 , 155 : 111149 .

SHOJAEI K . Neural network formation control of underactuated autonomous underwater vehicles with saturating actuators [J ] . Neurocomputing , 2016 , 194 ( 19 ): 372 - 384 .

KHAC D D , JIE P . Control of ships and underwater vehicles:design for underactuated and nonlinear marine systems [M ] . Berlin,Germany : Springer , 2009 .

浏览量

257

下载量

CNKI被引量

文章被引用时，请邮件提醒。

提交

工具集

关联资源

基于预设时间一致性理论的无人机编队控制

拒绝服务攻击下欠驱动无人艇事件触发编队控制

基于ESO的模糊LQR双尾舵高速飞行器姿态控制方法

基于扩张状态观测器的机载光电转台控制系统

电液比例伺服阀自适应自抗扰控制