Adaptive control for a VTOL UAV operating near a wall

  • Daewon Lee
  • , Asad Ullah Awan
  • , Suseoung Kim
  • , H. Jin Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Scopus citations

Abstract

In this paper, we proposed a neural-network-based adaptive controller to adapt against unknown, possibly time varying, external disturbances for a quadrotor UAV. The proposed algorithm can estimate uncertain forces, which occurs when flying in narrow areas, near walls and/or other surfaces, so that the controller can maintain satisfactory position tracking performance despite these disturbances. A proof for stability with the pro- posed algorithm is provided. Experimental results show that, with the proposed NN based adaptation algorithm, position tracking performance of quadrotor UAV shows satisfactory improvement in presence of external disturbances.

Original languageEnglish (US)
Title of host publicationAIAA Guidance, Navigation, and Control Conference 2012
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
ISBN (Print)9781600869389
DOIs
StatePublished - 2012
Externally publishedYes
EventAIAA Guidance, Navigation, and Control Conference 2012 - Minneapolis, MN, United States
Duration: Aug 13 2012Aug 16 2012

Publication series

NameAIAA Guidance, Navigation, and Control Conference 2012

Conference

ConferenceAIAA Guidance, Navigation, and Control Conference 2012
Country/TerritoryUnited States
CityMinneapolis, MN
Period8/13/128/16/12

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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