Vision-based adaptive fixed-time uncooperative target tracking for QUAV with unknown disturbances

Abstract

This article investigates the problem of the vision-based uncooperative target tracking control for a quadrotor unmanned aerial vehicle (QUAV) with unknown external disturbances. Note that the uncooperative target information cannot be obtained directly and need to be measured by a monocular sensor installed on the QUAV. In the light of the monocular sensor, a vision-based adaptive fixed-time control scheme is constructed to deal with the uncooperative target tracking problem. To efficiently observe unknown external disturbances, a fixed-time disturbance observer (FTDO) is designed by using the super-twisting (ST) algorithm. Finally, with the help of the Lyapunov stability theory, which guarantees the boundedness of all closed-loop signals, the QUAV is capable of tracking the uncooperative target in fixed time. The results of the simulation demonstrate the effectiveness of the proposed control strategy.