Flocking Control Algorithm of Multiple Agents Based on Layered Pinning Control Theory

Xiaolong Pang, Zhen Yang, Shiyuan Chai, Xingyu Wang, De Yun Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper starts from the concept of multi-Agent pinning control algorithm applied to UAV flocking control. Layered pinning control algorithm is proposed to optimize the tracking results for the problem of target tracking loss that may occur when the UAV clusters are large and there is external interference. According to the idea of breadth-first search, the speed and position feedback of its parent node is added to the control input of ordinary agents, and the speed matching term of the control input is improved by proposing a speed correction factor, which determines the degree of being affected by the neighborhood by judging the state of each other, so as to realize layer-by-layer transfer feedback and strengthen the tracking ability of the child nodes, which enables the whole network to avoid splitting and reach flocking. The simulation results show that the algorithm can strengthen the tracking ability of the agent and can track the target faster than the traditional pinning flocking control algorithm, which is suitable for large-scale UAV cluster flocking control.

Original languageEnglish
Title of host publication2023 8th International Conference on Robotics and Automation Engineering, ICRAE 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages211-215
Number of pages5
ISBN (Electronic)9798350327656
DOIs
StatePublished - 2023
Event8th International Conference on Robotics and Automation Engineering, ICRAE 2023 - Singapore, Singapore
Duration: 17 Nov 202319 Nov 2023

Publication series

Name2023 8th International Conference on Robotics and Automation Engineering, ICRAE 2023

Conference

Conference8th International Conference on Robotics and Automation Engineering, ICRAE 2023
Country/TerritorySingapore
CitySingapore
Period17/11/2319/11/23

Keywords

  • layered pinning control
  • multi-agent
  • neighborhood optimization

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