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Distributed Model Predictive Formation Control for UAVs and Cooperative Capability Evaluation of Swarm

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

This paper utilizes the distributed model predictive control (DMPC) method to investigate the formation control problem of unmanned aerial vehicles (UAVs) in the obstacle environment and establishes cooperative capability evaluation metrics of the swarm. Based on the DMPC approach, the formation cost function is constructed to adjust the relative positions and velocities of UAVs, ensuring the desired formation. Additionally, to address the obstacle avoidance problem in the formation, the obstacle avoidance function is designed to provide safe formation control in the obstacle environment. To evaluate the cooperative capability of UAVs, we design evaluation metrics from multiple dimensions to reflect the swarm’s cooperative capability. Finally, the simulation results show the effectiveness of the formation control method with obstacle avoidance and the applicability of the swarm’s cooperative capability evaluation metrics.

Original languageEnglish
Article number366
Pages (from-to)1-19
Number of pages19
JournalDrones
Volume9
Issue number5
DOIs
Publication statusPublished - May 2025

Keywords

  • cooperative capability evaluation
  • distributed model predictive control (DMPC)
  • formation control
  • unmanned aerial vehicles (UAVs)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Aerospace Engineering
  • Computer Science Applications
  • Artificial Intelligence

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