Abstract
This paper presents a nonlinear model predictive control (NMPC) framework for quadrotor trajectory tracking under nonlinear dynamics and aerodynamic disturbances. Unlike conventional proportional-derivative (PD) controllers that require trajectory-dependent gain retuning, the proposed NMPC employs a single set of weighting matrices to track multiple three-dimensional trajectories. The proposed controller is evaluated on helical and Lissajous trajectories and compared against an optimized PD controller. Simulation results show that the NMPC framework achieves improved tracking accuracy, reduced overshoot, and smoother control effort across varying trajectory complexities. Quantitatively, NMPC reduces the Integral of Squared Error (ISE) by 53-99.6% and the Integral of Time Absolute Error (ITAE) by 82.5-98.5% compared to the optimized PD controller, while maintaining robust performance without retuning. These results demonstrate the suitability of fixed-tuning NMPC for agile quadrotor trajectory tracking.