Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies

This paper investigates the time-varying formation-tracking (TVFT) problem for multi-UAV systems (MUSs), where the followers need to achieve a predefined time-varying formation configuration while tracking the leader’s state. In order to reduce the consumption of communication resources, an adaptive...

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Main Authors: Chengqing Liang, Lei Liu, Lei Li, Dongmei Yan
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Drones
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Online Access:https://www.mdpi.com/2504-446X/9/4/259
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author Chengqing Liang
Lei Liu
Lei Li
Dongmei Yan
author_facet Chengqing Liang
Lei Liu
Lei Li
Dongmei Yan
author_sort Chengqing Liang
collection DOAJ
description This paper investigates the time-varying formation-tracking (TVFT) problem for multi-UAV systems (MUSs), where the followers need to achieve a predefined time-varying formation configuration while tracking the leader’s state. In order to reduce the consumption of communication resources, an adaptive event-triggered mechanism (AETM) is designed. By combining the advantages of the adaptive technique and the event-triggered mechanism (ETM), UAVs can realize intermittent communication without relying on global information. Secondly, to improve the flexibility of formation-tracking trajectories, the TVFT consensus protocol with non-zero leader inputs is constructed. Meanwhile, the scope of the formation-tracking feasibility condition is extended. Then, the stability of the system is verified by Lyapunov stability theory, and sufficient conditions for MUSs to realize the desired TVFT configuration are obtained. In addition, the designed consensus protocol can be applied to both fixed topologies and switching topologies. Finally, the validity of the designed algorithm is confirmed by numerical examples and software-in-the-loop (SIL) simulation experiments.
format Article
id doaj-art-4f2c4cc7dc2a40b2841a977598a469c3
institution OA Journals
issn 2504-446X
language English
publishDate 2025-03-01
publisher MDPI AG
record_format Article
series Drones
spelling doaj-art-4f2c4cc7dc2a40b2841a977598a469c32025-08-20T02:28:12ZengMDPI AGDrones2504-446X2025-03-019425910.3390/drones9040259Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched TopologiesChengqing Liang0Lei Liu1Lei Li2Dongmei Yan3College of Artificial Intelligence and Automation, Hohai University, Changzhou 213200, ChinaSchool of Mathematics, Hohai University, Nanjing 210098, ChinaSchool of Mathematics, Hohai University, Nanjing 210098, ChinaSchool of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaThis paper investigates the time-varying formation-tracking (TVFT) problem for multi-UAV systems (MUSs), where the followers need to achieve a predefined time-varying formation configuration while tracking the leader’s state. In order to reduce the consumption of communication resources, an adaptive event-triggered mechanism (AETM) is designed. By combining the advantages of the adaptive technique and the event-triggered mechanism (ETM), UAVs can realize intermittent communication without relying on global information. Secondly, to improve the flexibility of formation-tracking trajectories, the TVFT consensus protocol with non-zero leader inputs is constructed. Meanwhile, the scope of the formation-tracking feasibility condition is extended. Then, the stability of the system is verified by Lyapunov stability theory, and sufficient conditions for MUSs to realize the desired TVFT configuration are obtained. In addition, the designed consensus protocol can be applied to both fixed topologies and switching topologies. Finally, the validity of the designed algorithm is confirmed by numerical examples and software-in-the-loop (SIL) simulation experiments.https://www.mdpi.com/2504-446X/9/4/259formation tracking controladaptive event-triggered mechanismUAVsswitching topologysoftware-in-the-loop
spellingShingle Chengqing Liang
Lei Liu
Lei Li
Dongmei Yan
Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies
Drones
formation tracking control
adaptive event-triggered mechanism
UAVs
switching topology
software-in-the-loop
title Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies
title_full Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies
title_fullStr Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies
title_full_unstemmed Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies
title_short Distributed Event-Triggered-Based Adaptive Formation Tracking Control for Multi-UAV Systems Under Fixed and Switched Topologies
title_sort distributed event triggered based adaptive formation tracking control for multi uav systems under fixed and switched topologies
topic formation tracking control
adaptive event-triggered mechanism
UAVs
switching topology
software-in-the-loop
url https://www.mdpi.com/2504-446X/9/4/259
work_keys_str_mv AT chengqingliang distributedeventtriggeredbasedadaptiveformationtrackingcontrolformultiuavsystemsunderfixedandswitchedtopologies
AT leiliu distributedeventtriggeredbasedadaptiveformationtrackingcontrolformultiuavsystemsunderfixedandswitchedtopologies
AT leili distributedeventtriggeredbasedadaptiveformationtrackingcontrolformultiuavsystemsunderfixedandswitchedtopologies
AT dongmeiyan distributedeventtriggeredbasedadaptiveformationtrackingcontrolformultiuavsystemsunderfixedandswitchedtopologies