Adaptive practical prescribed-time attitude tracking control for quadrotor UAV

Abstract

To achieve attitude tracking control on the entire time interval, an adaptive prescribed-time control (PTC) scheme is proposed for quadrotor unmanned aerial vehicle (QUAV) subject to external disturbances, actuator fault, input saturation and inertia uncertainties. Initially, a novel saturation function is introduced to approximate the actual control input subject to saturation, which eliminates the turning points in traditional saturation functions. Additionally, an adaptive neural network (NN) structure is proposed to approximate the lumped uncertainties. Subsequently, the approximation error of the NN structure and external disturbances are treated as a non-vanishing lumped term, and a novel adaptive prescribed-time control scheme is proposed, ensuring that tracking errors converge to a small neighborhood around zero within any prescribed time. To the best of our knowledge, existing PTC schemes primarily focus on vanishing uncertainties/ disturbances, thus tackling non-vanishing uncertainties/disturbances (NVU/NVD) renders the proposed PTC problem nontrivial. Furthermore, unlike existing PTC approaches, the combination of proposed adaptive PTC and NN approximation schemes results in satisfactory transient and steady-state performance. Rigorous stability analysis confirms the effectiveness of the proposed control strategy. Finally, comparing simulation results under various initial conditions and types of disturbances demonstrate the tracking performance and robustness of the proposed control strategy within prescribed time, which may offer broader application prospects than existing finite-time and fixed-time control schemes.