Improved Active Disturbance Rejection Control and Model Predictive Control for Quadrotor UAV Trajectory Tracking

In the field of unmanned aerial vehicle (UAV) control theory and applications, quadrotor UAVs are often severely affected by unknown disturbances when performing precise trajectory tracking tasks. This study proposes an innovative trajectory tracking control algorithm for quadrotor UAVs, which integrates Linear Active Disturbance Rejection Control (LADRC) and Model Predictive Control (MPC). In the position channel, an Extended State Observer (ESO) is employed to detect and compensate for uncertain disturbances, thereby reducing the reliance of MPC on precise models. In the attitude channel, LADRC with fast response and strong anti-disturbance capabilities is adopted, which not only improves computational efficiency but also ensures the stability of the UAV system. Experimental results demonstrate that the proposed trajectory tracking control algorithm significantly enhances the robustness of the UAV system in complex environments while maintaining high system accuracy.