Emergency landing trajectory optimization for a fixed-wing UAV under engine failure

Xiang Fang, Florian Holzapfel, Neng Wan, Hamidreza Jafarnejadsani, Donglei Sun, Naira Hovakimyan

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)


With the growing popularity of autonomous unmanned aerial vehicles (UAVs), the improvement of safety for UAV operations has become increasingly important. In this paper, a landing trajectory optimization scheme is proposed to generate reference landing trajectories for a fixed-wing UAV with accidental engine failure. For a specific landing objective, two types of landing trajectory optimization algorithms are investigated: i) trajectory optimization algorithm with nonlinear UAV dynamics, and ii) trajectory optimization algorithm with linearized UAV dynamics. An initialization procedure that generates an initial guess is introduced to accelerate the convergence of the optimization algorithms. The effectiveness of the proposed scheme is verified in a high-fidelity UAV simulation environment, where the optimized landing trajectories are tracked by a UAV equipped with an L1 adaptive altitude controller in both the offline and online modes.

Original languageEnglish
Title of host publicationAIAA Scitech 2019 Forum
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105784
Publication statusPublished - 2019
Externally publishedYes
EventAIAA Scitech Forum, 2019 - San Diego, United States
Duration: 7 Jan 201911 Jan 2019

Publication series

NameAIAA Scitech 2019 Forum


ConferenceAIAA Scitech Forum, 2019
Country/TerritoryUnited States
CitySan Diego

ASJC Scopus subject areas

  • Aerospace Engineering


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