[1]XIA Guihua,ZHU Wenxu,LIU Haoyan,et al.Research on collaborative self-organizing surrounding control algorithm of USV swarm[J].CAAI Transactions on Intelligent Systems,2025,20(1):162-171.[doi:10.11992/tis.202405025]
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Research on collaborative self-organizing surrounding control algorithm of USV swarm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 20 Number of periods: 2025 1 Page number: 162-171 Column: 学术论文—智能系统 Public date: 2025-01-05
Title:
Research on collaborative self-organizing surrounding control algorithm of USV swarm
Author(s):
XIA Guihua;  ZHU Wenxu;  LIU Haoyan;  LIU Xing;  JIANG Xiangli
College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin 150006, China
Keywords:
unmanned surface vessel; swarm control; cooperative surrounding; multi-agent system; model predictive control; input-to-state stability; state observer; graph theory
CLC:
TP242
DOI:
10.11992/tis.202405025
Abstract:
Unmanned surface vehicle (USV) swarm cooperative surrounding is one of the important application scenarios of USVs. This paper designs a self-organizing control algorithm for USV swarm cooperative surrounding tasks. Considering the unknown acceleration of the target to be encircled and the fact that only some members of the swarm can measure its position and velocity, this paper proposes a distributed target state observer (DTSO) to achieve consistency observation of the target state among swarm members during the surrounding process. Subsequently, a self-organizing surrounding guidance law is designed to address the issue of pre-allocating expected positions for members in the surrounding algorithm. Finally, a distributed nonlinear model predictive control (DNMPC) is designed to resolve the problems of actuator saturation and inter-boat distance constraints, achieving collaborative surrounding control that meets collision avoidance safety. The paper analyzes the input-to-state stability (ISS) of the control system and validates the effectiveness of the surrounding algorithm through simulation experiments with multiple sets of different initial states and varying numbers of members.
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Last Update: 2025-01-05

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