Prescribed finite-time adaptive neural trajectory tracking control of quadrotor via output feedback

Abstract

This paper proposes a novel prescribed finite-time output feedback control scheme for quadrotor trajectory tracking control. The proposed control scheme considers the quadrotor modeling containing uncertain nonlinearities and strong coupling. The neural observer is set up to estimate the unknown state variables. The main difficulty caused by the time-vary coefficient matrix to design a state observer is overcame by the convex combination technique. To get a prescribed finite-time tracking performance, Barrier Lyapunov Function (BLF) approach is presented for control design. The constructed controllers guarantee that the tracking errors meet the prescribed accuracy in a pre-specified finite settling time. Finally, a simulation example verifies the effectiveness of the control scheme.