Integrated guidance and control for UAV path following in Frenet–Serret frame

Abstract

This paper proposes a high-precision path following method for unmanned aerial vehicles (UAVs) using the Frenet–Serret (FS) coordinate frame combined with the optimal Integrated Guidance and Control (IGC) algorithm. To increase adaptability and reduce tracking error in an uncertain environment, a neural network coupled model predictive controller (NNMPC) is directly integrated into the IGC framework. The stability analysis of the system is performed using the Lyapunov–Krasovskii criterion, providing a sufficient condition for asymptotic stability under bounded time delay and neural network approximation errors. The simulation results for a quadrotor UAV following a sinusoidal trajectory demonstrate that the proposed method outperforms traditional PID control in terms of accuracy and disturbance rejection capability. Furthermore, this study discusses practical implementation constraints, including computational complexity and data availability, thereby bridging the gap between theoretical design and real-time UAV applications.