Abstract
The high maneuverability of fixed-wing unmanned aerial vehicles (UAVs) exposes these systems to several dynamical and parametric uncertainties, severely affecting the fidelity of modeling and causing limited guidance autonomy. This article shows enhanced autonomy via adaptation mechanisms embedded in the guidance law: a vector-field method is proposed that does not require a priori knowledge of the UAV course time constant, coupling effects, and wind amplitude/direction. Stability and performance are assessed using the Lyapunov theory. The method is tested on software-in-the loop and hardware-in-the-loop UAV platforms, showing that the proposed guidance law outperforms state-of-the-art guidance controllers and standard vector-field approaches in the presence of significant uncertainty.
| Original language | English |
|---|---|
| Pages (from-to) | 4597-4607 |
| Journal | IEEE/ASME Transactions on Mechatronics |
| Volume | 27 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2022 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Adaptive guidance
- adaptive sliding-mode control
- Adaptive systems
- Aerodynamics
- Autonomous aerial vehicles
- fixed-wing unmanned aerial vehicles (UAV)
- Navigation
- Orbits
- Standards
- Uncertainty
- unknown dynamics
- vector field (VF)