A Dynamic High-Order Control Barrier Function Based Model Predictive Trajectory Tracking Control for Quadrotor UAVs

With the rapid advancement of unmanned aerial vehicle (UAV) technology, quadrotor UAVs have demonstrated great potential in tasks such as surveillance, inspection, search and rescue, due to their strong maneuverability and simple structure. Trajectory tracking ensures the UAV following a predefined path autonomously in the flight environment, which plays a critical role in autonomous navigation. However, their highly nonlinear, strongly coupled dynamics and susceptibility to external disturbances pose significant challenges for achieving highprecision trajectory tracking. To address these issues, this paper proposes a Model Predictive Control (MPC)-based trajectory tracking control algorithm which involved safety constraints proposed by Dynamic High-order Control Barrier Functions (DHCBF), ensuring that system states remain within predefined safe regions while optimizing performance. Firstly, a dynamic model of the quadrotor UAV with six degrees of freedom is created. Then, the three-order safe set is formulated by the DHCBF to guaranteed the UAV remained within the safe flight region. Finally, the restricted optimal control issue is expressed as a quadratic program by including the DHCBF constraints into the MPC framework. Simulation results demonstrate that the proposed algorithm achieves high tracking accuracy across complex trajectories. Compared with traditional PID control, the method exhibits superior precision guarantees and dynamic responsiveness.