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

Stefano Fari*, Ximan Wang, Spandan Roy, Simone Baldi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)
117 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)1613-1622
JournalIEEE Transactions on Aerospace and Electronic Systems
Issue number2
Publication statusPublished - 2020

Bibliographical note

Accepted Author Manuscript


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


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