Guiding vector field-based guidance under wind disturbances applied to a tailsitter UAV

TL;DR

This paper introduces a GVF-based guidance law for tailsitter UAVs that performs well under wind disturbances, especially with initial deviations, and compares it to traditional guidance methods through simulations.

Contribution

It proposes a modified GVF ensuring exponential stability and extends the tailsitter's differential flatness to include wind effects, enhancing guidance robustness.

Findings

GVF-based guidance outperforms in initial deviation scenarios

Both guidance strategies perform similarly under small initial errors

Modified GVF guarantees exponential stability

Abstract

This paper develops a guidance control law based on a parametric Guiding Vector Field (GVF) and integrates it with a state-of-the-art acceleration and attitude control architecture for tailsitters. The resulting framework enables a direct comparison between traditional trajectory-tracking guidance and GVF-based path-following guidance using a realistic tailsitter model operating under windy conditions. Through extensive simulations, it is shown that for agile flight scenarios with wind and small initial position error, both guidance strategies achieve comparable tracking performance, indicating that the additional complexity introduced by the GVF formulation is not always justified. However, the GVF-based approach exhibits an advantage when initial deviation from the path is present, yielding smooth and well-behaved convergence toward the desired path. Two additional contributions support this evaluation. First, a modification of the parametric GVF is proposed that guarantees exponential stability of the tracking error dynamics for a single integrator system. Second, the differential flatness transform of a tailsitter vehicle is extended to account for explicit knowledge of the wind velocity vector.