Adaptive Dynamic Event-Triggered Formation Control of Multiple Hexarotor UAVs Under Atmospheric Boundary Layer Gusts
Multi-UAV formation control in low-altitude urban environments faces critical challenges from atmospheric boundary layer (ABL) disturbances, including turbulence, wind gusts, and communication inefficiency in resource-constrained swarms. This paper proposes an adaptive dynamic event-triggered formation control (ADETFC) strategy integrated with a finite-time disturbance observer (FTDO) for multi-agent hexarotor UAV formations operating under ABL conditions. The novelty of the proposed ADETFC lies in employing dual adaptive parameters to simultaneously account for tracking error magnitude and inter-agent formation geometry, dynamically adjusting communication frequency. A nonsingular terminal sliding mode manifold ensures rapid transient convergence and robustness against nonlinearities and inter-agent coupling. The FTDO estimates lumped disturbances with finite-time convergence to a bounded residual neighborhood, enabling reduced control gains that mitigate chattering and actuator wear. Lyapunov-based analysis establishes finite-time reachability of the sliding manifold and guarantees that the tracking error converges to a bounded residual set in finite time. The Zeno-free operation is guaranteed by a strictly positive minimum inter-event time analytically derived from system dynamics. Simulations under three ABL scenarios, including Dryden turbulence, wind gusts, and sinusoidal disturbances, demonstrate formation tracking RMSE reductions of up to 29.4%, disturbance estimation RMSE reductions of up to 54.3%, and communication-event reductions of 46.4–63.2% compared with benchmark schemes. These results confirm accurate formation tracking, efficient communication, and robust multi-agent networking under challenging wind conditions, making the framework suitable for networked UAV applications in complex environments.
Authors
- Nihad Ali (ORCID: https://orcid.org/0000-0002-4664-5301)
- Jamshed Iqbal (ORCID: https://orcid.org/0000-0002-0795-0282)
- Muhammad Ilyas
Institutions
- Harbin Engineering University (CN)
- Gulf University for Science & Technology (KW)
- Shanghai Jiao Tong University (CN)
Publication Details
- Journal
- Fractal and Fractional
- Published
- 2026-06-16
- DOI
- https://doi.org/10.3390/fractalfract10060410
- Primary Topic
- Distributed Control Multi-Agent Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00