Algebraic-Connectivity-Based Multi-USV Distributed Formation Method via Adding a Reverse Edge

Jingchen Wang, Qihe Shan (), Jun Zhu (), Xiaofeng Cheng and Baoze Wei
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Jingchen Wang: School of Navigation, Dalian Maritime University, Dalian 116026, China
Qihe Shan: School of Navigation, Dalian Maritime University, Dalian 116026, China
Jun Zhu: Research Institute of Intelligent Networks, Zhejiang Lab, Hangzhou 311121, China
Xiaofeng Cheng: Research Institute of Intelligent Networks, Zhejiang Lab, Hangzhou 311121, China
Baoze Wei: Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark

Mathematics, 2023, vol. 11, issue 13, 1-22

Abstract: This paper concerns the formation problem in multi-USV cluster formation containment tracking tasks with a special topology. A topology reconstruction method was proposed that enables the followers’ formation to be dispersed while achieving the fastest convergence rate for the system. This topology structure is based on tree topology and DAG (directed acyclic graph) local structure stem as prototypes, using the principle of adding reverse edges on the stem to reduce algebraic connectivity. By adding a reverse edge to obtain a more dispersed formation, a method for selecting appropriate reverse edges was achieved. Through relevant theoretical quantitative and qualitative analysis, it was demonstrated that adding this reverse edge can enable the system to achieve the fastest convergence rate. Finally, through simulation experiments, it was verified that the selected reverse edge can optimize the formation of followers and achieve the fastest convergence rate.

Keywords: formation; stem; DAG; muti-USV cluster; algebraic connectivity (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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