Predefined Accuracy Control of Autonomous Aerial Vehicles: An Obstacle Avoidance Robust Control

In this paper, we present a controller approach to solve the problem of bearing‐constrained autonomous aerial vehicle (AAV) reaching a target with predefined accuracy, also avoiding multiple obstacles and coping with possible actuator failure in the process. First, to ensure that AAV with weak perception capabilities still maintains high performance, we propose a bearing‐based AAV localization model to accurately locate targets and obstacles while only obtaining angular information, which effectively solves the problem of maintaining high performance of AAV with limited loading capacity and cost. Second, an obstacle avoidance assistance system is designed in combination with the localization model, so that the AAV can avoid obstacles perfectly even with local perception. Third, we also employ an asymmetric time‐varying Lyapunov barrier function (BLF) to enable the AAV to reach the target with a predefined accuracy, and use neural networks (NNs) to approximate unknown functions in the system while being able to cope with actuator failures. Finally, simulation experiments verify that the AAV can perfectly achieve the control goal in various environments.