Comparative Analysis of Geometric Path Following and Nonlinear Control Strategies for UAV

Abstract

This research presents a comparative study of three geometric path-following guidance algorithms: Carrot Chasing (CC), Pure Pursuit Line of Sight (PLOS), and Nonlinear Guidance Law (NLGL) implemented within a hierarchical UAV autopilot framework using a Backstepping (BKS) control approach. The study aims to evaluate and enhance the path-following performance of fixed-wing Unmanned Aerial Vehicles (UAVs) under realistic operating conditions. The overall Guidance, Navigation, and Control (GNC) architecture adopted separates the outer guidance loop, responsible for generating attitude commands, from the inner BKS-based control loop, which tracks these commands to stabilize the UAV’s attitude Numerical simulations are conducted to assess each guidance method in terms of convergence speed, path accuracy, and cross-track error performance across straight-line and combined 3D waypoint trajectories. The results demonstrate that while all three geometric guidance laws achieve satisfactory steady-state tracking, notable differences arise in transient response. Among the evaluated methods, the NLGL exhibits superior dynamic performance when integrated with the BKS controller. These findings contribute to the development of guidance strategies that enhance the reliability and autonomy of UAV operations in complex environments.