Observer-based adaptive fuzzy finite-time attitude control for quadrotor UAVs

This study presents an observer-based adaptive fuzzy finite-time attitude control strategy for quadrotor unmanned aerial vehicles (UAVs). To estimate the information of angular velocity with the finite-time property, an adaptive neural network observer is first developed. Subsequently, an adaptive fuzzy logic system (FLS)-based nonsingular fast terminal sliding mode controller is proposed to compensate for the lumped disturbance and adjust the control gain online. To cope with the input saturation, an auxiliary system without the boundedness of the saturation difference is constructed. The theoretical analysis proves that all the system signals are bounded and the tracking errors can converge to small neighbourhoods in finite time. Finally, comparative simulations and experiments are performed to manifest the feasibility and superiority of the proposed control strategy, in terms of strong robustness, singularity avoidance, free-chattering, fault tolerance, and saturation attenuation.