Quadcopter Unmanned Aerial Vehicle Formation Trajectory Tracking based on Extended State Observer with Model Predictive Control

To address the formation trajectory tracking of Quadcopter Unmanned Aerial Vehicle (QUAV) in the complex environment, this paper integrates a Model Predictive Control (MPC) method with an Extended State Observer (ESO), which effectively solves instability of flight coordination resulting from external disturbances and internal uncertainties. The prediction model of the MPC controller is obtained based on Taylor series expansion and Euler transform. ESO estimates external disturbances and internal uncertainties in real-time, adjusts the desired speed via proportional compensation, thereby achieving precise control of formation trajectories. Simulation results demonstrate that the proposed method efficiently suppress external disturbances and internal uncertainties, thereby enabling precise tracking of the trajectory for the formation.