Event-Triggered Prescribed-Time Tracking Control for UAVs Using Polynomial Error Trajectories

In this paper, we propose a novel event-triggered prescribed-time tracking (PTT) control method for an underactuated unmanned aerial vehicle (UAV). Unlike existing PTT control methods, where the transient behavior of the system depends solely on the controller gains, we design a novel reference error trajectory (RET) using a polynomial to guide the convergence of the tracking error, particularly during the transient phase. Based on this RET and within the backstepping framework, we design a thrust reference. Additionally, we introduce a novel event-triggered mechanism based on the tracking error to update the torque applied to the UAV. To streamline intricate mathematical expressions and improve robustness to external disturbances, a second-order linear system is used as a low-pass filter within the backstepping design. Finally, simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the accuracy of the theoretical predictions. Note to Practitioners—This paper introduces a novel prescribed-time control method for an underactuated UAV, incorporating an event-triggered technique. This approach aims to enhance tracking accuracy while reducing control signal updates, thereby lowering communication overhead and increasing system efficiency. A reference error trajectory is designed for the position error, guiding the UAV to converge quickly to the reference trajectory within a prescribed time. This ensures precise tracking even in dynamic and uncertain environments, making it suitable for real-world applications. Additionally, a second-order filter is introduced to reduce the computational burden from repeated differentiation of the virtual controller in the backstepping design. Our overall approach provides an effective solution for critical tasks such as autonomous navigation, search-and-rescue, and surveillance, making it a promising technology for UAV applications in dynamic, high-stakes environments.