Adaptive asymptotic tracking control of quadrotor UAVs with error constraints and unknown disturbances

Abstract This study focuses on resolving two important issues in quadrotor UAVs tracking control: (i) developing an accurate dynamic model despite unpredictable external disturbances and (ii) ensuring asymptotic convergence of both position and attitude tracking for arbitrary reference trajectories, without violating predefined error bounds. The core challenges involve compensating for unmodeled disturbances and adhering to strict tracking constraints. To address these, a novel adaptive tracking controller is designed by incorporating logarithmic barrier functions and a time‐based exponentially decaying term. Unlike conventional methods, the proposed approach offers not only enhanced robustness against uncertain disturbances, but also a unified control architecture for seamless position and attitude regulation. Numerical simulations confirm the strategy's effectiveness.