Human-in-the-Loop Prescribed Performance Distributed Formation Tracking Control of Networked Quadrotor UAVs

Timeliness and accuracy are critical performance metrics for evaluating the effectiveness of control strategies, particularly in high-maneuverability systems such as quadrotor unmanned aerial vehicle (UAV) swarms that demand precise and coordinated control. However, most existing control methods for quadrotor UAV swarms primarily focus on ensuring system stability, often overlooking the stringent requirements on transient response and steady-state accuracy. To this end, this paper proposes a novel prescribed performance formation tracking control scheme for quadrotor UAVs, enhanced by a human-in-the-loop control mechanism. The proposed framework integrates a distributed prescribed-time observer and a prescribed performance controller, enabling the estimation of the human operator's dynamic influence even when the control input is inaccessible to the UAVs. This facilitates accurate formation tracking for the networked UAV system. The framework guarantees that both the estimation error of the human-in-the-loop system and the formation tracking error converge within predefined performance envelopes, with convergence achieved strictly within preset time bounds. Theoretical analysis based on Lyapunov stability theory is provided to ensure rigorous performance guarantees, and simulation results further validate the effectiveness of the proposed scheme, demonstrating its superior capability in achieving rapid convergence and maintaining high-precision tracking under performance constraints.