Addressing Unmodeled Path-Following Dynamics via Adaptive Vector Field

Addressing Unmodeled Path-Following Dynamics via Adaptive Vector Field: A UAV Test Case

Fari, S. (TU Delft Team Bart De Schutter; Politecnico di Milano; Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR))
Wang, X. (TU Delft Team Bart De Schutter; China State Shipbuilding Corporation)
Roy, S. (TU Delft Ship Design, Production and Operations)
Baldi, S. (TU Delft Team Bart De Schutter; Southeast University)

2020

The actual performance of model-based path-following methods for unmanned aerial vehicles (UAVs) shows considerable dependence on the wind knowledge and on the fidelity of the dynamic model used for design. This study analyzes and demonstrates the performance of an adaptive vector field (VF) control law which can compensate for the lack of knowledge of the wind vector and for the presence of unmodeled course angle dynamics. Extensive simulation experiments, calibrated on a commercial fixed-wing UAV and proven to be realistic, show that the new VF method can better cope with uncertainties than its standard version. In fact, while the standard VF approach works perfectly for ideal first-order course angle dynamics (and perfect knowledge of the wind vector), its performance degrades in the presence of unknown wind or unmodeled course angle dynamics. On the other hand, the estimation mechanism of the proposed adaptive VF effectively compensates for wind uncertainty and unmodeled dynamics, sensibly reducing the path-following error as compared to the standard VF.

Adaptive vector field
fixed-wing unmanned aerial vehicles (UAV)
path-following
unmodeled course angle dynamics

http://resolver.tudelft.nl/uuid:f0e86e88-a079-4750-8bfa-79a57ceb36cb

https://doi.org/10.1109/TAES.2019.2925487

0018-9251

IEEE Transactions on Aerospace and Electronic Systems, 56 (2), 1613-1622

Accepted Author Manuscript

Institutional Repository

journal article

© 2020 S. Fari, X. Wang, S. Roy, S. Baldi