A General Prescribed Performance Trajectory Tracking Control Policy for Quadrotor UAVs Under Event‐Triggered Sampling

This paper studies the issue of trajectory tracking control of quadrotor unmanned aerial vehicles in the presence of external disturbances. A prescribed performance control method with more general performance functions is proposed to guarantee the predesigned performance, in which Chebyshev neural networks are used to estimate and compensate for external disturbances, and the norm approximation approach is applied to minimize the computational complexity of neural networks. Moreover, an event‐triggered mechanism with general formal threshold functions is introduced to reduce controller update frequency. Finally, simulation results of the proposed methods demonstrate their effectiveness and superiority.