Controlling a quadrotor UAV flight using a fractional Caputo–Fabrizio backstepping control for trajectory tracking tasks

• Published in: International journal of dynamics and control Vol. 13; no. 8
• Main Authors: Lavín-Delgado, J. E., Soto-Mendiola, R. M., Gómez-Aguilar, J. F., Gallardo-Bernal, I., Hernández-Castillo, E., Pérez-Careta, Eduardo
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer Nature B.V 01.08.2025
• Subjects: Control theory; Controllers; Differential equations; Dynamic models; Integers; Nonlinear control; Operators (mathematics); Robotics; Robust control; Root-mean-square errors; Search algorithms; Systems stability; Tracking; Trajectories; Unmanned aerial vehicles
• ISSN: 2195-268X; 2195-2698
• DOI: 10.1007/s40435-025-01794-4

This research presents a novel fractional backstepping control strategy for quadrotor trajectory tracking, formulated using the Caputo–Fabrizio derivative. The dynamic model of the system is derived via the Newton–Euler formalism and generalized to a fractional order using the Caputo–Fabrizio differential operator. The proposed control strategy integrates a fractional PD controller within the structure of a backstepping control law, enabling improved control of the nonlinear, underactuated system. For benchmarking purposes, an integer-order counterpart of the controller is also designed. Both control schemes are optimized through the Cuckoo Search algorithm, employing the root mean square error (RMSE) as the objective function. The effectiveness and robustness of the proposed approach are assessed through numerical simulation involving multiple reference trajectories and external disturbances. Results demonstrate that the fractional controller yields superior tracking accuracy, reduced overshoot, and enhanced system stability compared to its integer-order counterpart. This work constitutes the first reported implementation of a Caputo–Fabrizio-based backstepping control scheme for quadrotor UAV systems, offering a promising foundation for the advancement of robust fractional control strategies in aerial robotics.