Adaptive Prescribed‐Time Trajectory Tracking Control for a Quadrotor With Non‐Vanishing Uncertainties

This paper investigates a global prescribed‐time trajectory tracking control problem for a quadrotor unmanned aerial vehicle (QUAV) subject to non‐vanishing uncertainties. To overcome the limitations of traditional prescribed‐time control (PTC) methods that rely on switching mechanisms or are sensitive to initial conditions, a novel prescribed‐time controller is constructed based on reference convergence differential functions (RCDF), avoiding any state transition and reducing computational burden. To the authors' best knowledge, while many existing PTC methods can handle non‐vanishing uncertainties (NVU), effectively addressing NVU in under‐actuated systems remains a challenging issue. Then, a prescribed‐time unknown input observer (PTUIO) is designed to estimate translational disturbances, and an adaptive law is introduced into the attitude subsystem to compensate for NVU. Moreover, this control strategy guarantees the system convergence over the entire time interval with a user‐defined settling time, regardless of initial conditions. Simulation results under various conditions demonstrate the effectiveness, robustness, and practical feasibility of the proposed scheme compared to related methods.