Attitude-Constrained Flight Control for Unmanned Aerial Vehicles with Thrust-Vectoring Maneuverability Enhancement

This work addresses the path angle tracking control problem for the thrust-vectoring unmanned aerial vehicle (UAV) simultaneously considering the attitude limitations and the maneuverability enhancement. An attitude-constrained flight control scheme is developed under the framework of the backstepping technology. Particularly, the thrust vector is used as the feedforward control to provide accelerations for the UAV, and it is able to eliminate the maneuverability loss due to the attitude limitations. Then, by providing a specified formula of the performance functions, the prescribed performance control method is applied to accomplish the attitude tracking and the constraint satisfaction, simultaneously. Furthermore, the adaptive neural network is utilized to approximate the uncertainties caused by the thrust vector. The Lyapunov function method will be applied to guarantee the boundedness of closed-loop system signals. Finally, the simulation result is presented to illustrate the effectiveness of the proposed flight control scheme.