Approximation-based Adaptive Tracking Control for 6-DoF Tailless Flying-Wing UAV with Coefficient Uncertainties

In this paper, we focus on the adaptive tracking control problem for tailless flying-wing unmanned aerial vehicle (UAV) subject to the coefficient uncertainties and external disturbance. It’s worth noting that the six-degree-of-freedom (6-DoF) model of flying-wing UAV is established for the first time. Different from most existing results, both the velocity and attitude control under state coupling are considered simultaneously in this work. With the help of neural network approximators, an adaptive neural controller is developed to handle the coefficient uncertainty and external disturbance problem. It is proved that all the signals in the closed-loop system are semiglobal uniformly ultimately bounded (SGUUB). The simulation results are provided to demonstrate the effectiveness of the designed method.