A novel prescribed performance control model with ESO to optimize trajectory tracking for quadrotor UAV

Abstract

In the study of trajectory tracking of the quadrotor UAV, there exists two major problems: external interference and tracking estimation error. Based on the extended state observer (ESO), a unilateral no-overshoot fast convergence model with Novel Prescribed Performance Control (NPPC) mechanism is proposed in this paper. Firstly, the quadrotor UAV is transformed into an external loop position and an inner loop attitude control system. A novel error transform function is proposed for the limitation that the former prescribed performance control scheme cannot achieve rapid convergence of the system state. Secondly, the controllers are designed by the position subsystem and the attitude subsystem, according to the backstepping method and the ESO are designed to estimate external interference. Finally, it is combined with dynamic surface control to realize the trajectory tracking of the UAV under the external interference. Several simulations based on this proposed model have been performed and the results show that the designed controllers can make the quadrotor from any initial state reach the steady one according to the specified convergence time and have better convergence than Traditional Prescribed Performance Control (TPPC).