Human-in-the-Loop Time-Varying Formation Tracking of Networked UAV Systems with Compound Actuator Faults
Jiaqi Lu, Kaiyu Qin, Mengji Shi · Drones · 2026
Time-varying formation tracking of networked unmanned aerial vehicle (UAV) systems plays a crucial role in cooperative missions such as encirclement, cooperative surveillance, and search-and-rescue operations, where human operators are often involved and system reliability is challenged by actuator faults and external disturbances. Motivated by these practical considerations, this paper investigates a human-in-the-loop time-varying formation tracking problem for networked UAV systems subject to compound actuator faults and external disturbances. To address this problem, a novel two-layer control architecture is developed, comprising a distributed observer and a fault-tolerant controller. The distributed observer enables each UAV to estimate the states of the human-in-the-loop leader using only local information exchange, while the fault-tolerant controller is designed to preserve formation tracking performance in the presence of compound actuator faults. By incorporating dynamic iteration regulation and adaptive laws, the proposed control scheme ensures that the formation tracking errors converge to a bounded neighborhood of the origin. Rigorous Lyapunov-based analysis is conducted to establish the stability, convergence, and robustness of the resulting closed-loop system. Numerical simulations further demonstrate the effectiveness of the proposed method in achieving practical time-varying formation tracking under complex fault scenarios.