In this paper, the robust trajectory tracking control problem of disturbed quadrotor unmanned aerial vehicles (UAVs) with disturbances, uncertainties and unmodeled dynamics is addressed, by devising a novel compound robust tracking control (CRTC) approach via data-driven cascade control technique. By deploying the data-driven philosophy, a data-based sliding-mode surface is proposed, and thereby contributing to strong adaptability to nonlinearity and model-unknown properties of the UAVs. By utilizing the backstepping technique, virtual control strategy and a novel cascaded compound robust PD control structure, the attitude and position subsystems are efficiently cohered such that a data-driven cascaded compound robust controller containing both PD control and sliding-mode control can be developed to conquer the lumped disturbances induced by uncertainties, disturbances and unmodeled dynamics. Eventually, the asymptotic convergence of the tracking errors with respect to both attitude and position subsystems can be guaranteed rigorously. Simulation studies on a prototype quadrotor UAV are performed to evaluate the efficacy and superiority of the devised CRTC method.
Hybrid fuzzy-based sliding-mode control approach, optimized by genetic algorithm for quadrotor unmanned aerial vehicles