Fixed-Time Formation Control for MAV/UAVs with Switching Threshold Event-Triggered Strategy
The cooperative flight of manned and unmanned aerial vehicles (MAV/UAVs) has recently become a focus in the research of civilian and humanitarian fields, in which formation control is crucial. This paper takes the improvement of convergence performance and resource conservation as the entry point to study control problems of cooperative formation configuration of MAV/UAVs. Following the backstepping recursive design procedures, an event-triggered fixed-time formation control strategy for MAV/UAVs operating under modeling uncertainties and external disturbances is presented. Moreover, a novel switching threshold event-triggered mechanism is introduced, which dynamically adjusts control signal updates based on system states. Compared with periodic sampling control (Controller 1), fixed threshold strategies (Controller 2) and relative threshold strategies (Controller 3), this mechanism enhances resource efficiency and prevents Zeno behavior. On the basis of Lyapunov stability theory, the closed-loop system is shown to be stable in the sense of the fixed-time concept. Numerical simulations are carried out in Simulink to validate the effectiveness of the theoretical findings. The results show that compared with the three comparison methods, the proposed control method saves 86%, 34%, and 43% of control transmission burden respectively, which significantly reduces the number of triggered events.
Authors
- Xueyan Han (ORCID: https://orcid.org/0000-0001-6362-5313)
- Yuyuan Shi (ORCID: https://orcid.org/0009-0004-2090-4928)
- Boyang Zhang (ORCID: https://orcid.org/0000-0002-5174-0549)
- Di Shen (ORCID: https://orcid.org/0000-0002-3534-5311)
- Yu Peng (ORCID: https://orcid.org/0000-0002-0550-9338)
- Maolong Lv (ORCID: https://orcid.org/0000-0001-6406-2399)
Institutions
- Xidian University (CN)
- Air Force Engineering University (CN)
- Xi'an City Planning&Design Institute (China) (CN)
- Beijing Advanced Sciences and Innovation Center (CN)
Publication Details
- Journal
- Drones
- Published
- 2025-10-14
- DOI
- https://doi.org/10.3390/drones9100710
- Primary Topic
- Distributed Control Multi-Agent Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China