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Guo et al. Intell Robot 2023;3(4):596-613 Intelligence & Robotics
DOI: 10.20517/ir.2023.32

Research Article Open Access

Event-triggered consensus control method with com-

munication faults for multi-UAV

1
1
1
Zilong Guo , Chen Wei , Yankai Shen , Wanmai Yuan 2
1 School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.
2 China Academic of Electronics and Information Technology, China Electronics Technology Group Corporation, Beijing 100041,
China.
Correspondence to: Prof. Chen Wei, School of Automation Science and Electrical Engineering, Beihang University, Xueyuan Road
No.37, Haidian District, Beijing 100191, China. E-mail: weichen@buaa.edu.cn

How to cite this article: Guo Z, Wei C, Shen Y, Yuan W. Event-triggered consensus control method with communication faults for
multi-UAV. Intell Robot 2023;3(4):596-613. http://dx.doi.org/10.20517/ir.2023.32
Received: 30 Aug 2023 First Decision: 12 Sep 2023 Revised: 25 Sep 2023 Accepted: 17 Oct 2023 Published: 23 Nov
2023

Academic Editor: Jinguo Liu, Simon X. Yang Copy Editor: Dan Zhang Production Editor: Dan Zhang

Abstract

This paper investigates the event-triggered consensus for a group of unmanned aerial vehicles (UAVs) with commu-
nication faults under the assumption that the position sensors of some individuals are damaged. The objective is to
make the UAV group reach consensus in urgent tasks such as obstacle avoidance or evasion. Using the Lyapunov
stability theory, sufficient conditions to achieve system consensus are given based on different velocity and position
interaction topologies. Considering the limited capabilities of sensors and processors, an event-triggered consensus
protocol is adopted to reduce the sampling frequency. Finally, simulation results illustrate the effectiveness of our
approach.

Keywords: Unmanned aerial vehicle, communication faults, consensus, event-triggered control, interaction topology

1. INTRODUCTION
The multi-agent systems (MAS) abstracted from complex systems, such as unmanned aerial vehicle (UAV)
[1]
groups, are regarded as significant research objects for studying group intelligent behavior in recent years .
With excellent performance in simplifying the analysis process, it is applied to various fields of UAVs, such
[2]
[3]
as formation control , collaborative investigations , and many other fields. Through the consensus control

© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, shar-
ing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you
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