Event-triggered control for trajectory tracking of quadrotor unmanned aerial vehicle

Abstract

This paper studies the trajectory tracking problem of quadrotor unmanned aerial vehicle (QUAV) with model nonlinearities and external disturbances via event-triggered control technique. Dividing the QUAV system into position subsystem and attitude subsystem, an adaptive fuzzy control algorithm is designed in position subsystem to provide desired pitch and roll angles for the attitude subsystem. Then, by constructing an event-triggered mechanism, an event-triggered adaptive fuzzy control algorithm is presented in the attitude subsystem, where the control law and the fuzzy parameter adaptive law are updated in an aperiodic form. Based on Lyapunov stability theory, it is proved that all signals in the closed-loop system are uniformly ultimately bounded via the impulsive dynamical system tool, and the tracking errors converge to a small neighbourhood of the origin. Besides, it is proved that there is a positive lower bound between the intersample time to avoid Zeno behaviour. Finally, simulation results illustrate that the proposed control scheme can guarantee the trajectory tracking performance of the QUAV system, while it can reduce the update frequency of the controller and improve the resource utilization.