Practical fixed-time tracking control of quadrotor unmanned aerial vehicles with input saturation

In this article, an adaptive fixed-time sliding mode control method is proposed for the quadrotor unmanned aerial vehicles (UAVs) with external disturbances and input saturation. Firstly, the fixed-time sliding mode surface with a piecewise function enhances convergence speed and avoids singularity problems. The radial basis function neural networks (RBFNNs) are selected to estimate disturbances, and auxiliary systems are designed to address input saturation. Subsequently, an adaptive controller is created to ensure that the error system can converge into the neighborhood of origin within a fixed time. Furthermore, based on the proposed control approach, the stability of the closed-loop system is analyzed with rigorous theoretical proof. Finally, comparative simulations are provided to illustrate the effectiveness and superiority of the proposed methodology.