Robust Adaptive Sliding Mode Control Based on Iterative Learning for Quadrotor UAV

Abstract

In order to improve the anti-disturbance ability and reduce the sensitivity to faults for the quadrotor UAV, the robust sliding mode adaptive control strategy based on iterative learning is designed in this paper. Firstly, the dynamic model of the quadrotor UAV is established. Secondly, the iterative learning observer is designed to track the states of the UAV system, and the convergence analysis of the observer is given. Thirdly, for the attitude system of the quadrotor UAV, a robust adaptive sliding mode control strategy based on iterative learning is proposed, and the stability is proved by the Lyapunov theory. Finally, by the simulation for the UAV attitude system, the validity of the iterative learning observer and robust adaptive sliding mode control strategy based on iterative learning is verified.