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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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| 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 |