Vision-Based Prescribed Performance Control for UAV Target Tracking Subject to Actuator Saturation

In this article, a vision-based prescribed performance control is proposed for an unmanned aerial vehicle (UAV) subject to actuator saturation to track an uncooperative target. It is supposed that states cannot be measured directly, and are estimated by a on-board camera. The proposed controller is designed within a backstepping framework, where an error transforming function and Barrier Lyapunov Function are applied, and a robust adaptive controller is designed to deal with initial conditions violating the prescribed performance. It is proven that, with the proposed controller, the tracking error converges into the prescribed performance boundary before the finite preset time.