Model predictive control for path tracking of a VTOL tail-sitter UAV in an HIL simulation environment

Boyang Li, Weifeng Zhou, Jingxuan Sun, Chih-yung Wen, Chih Keng Chen

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

19 Citations (Scopus)


This paper investigates the application of Model Predictive Control (MPC) for path tracking of a vertical takeoff and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hovering. In this work, the nonlinear dynamic model of a quad-rotor tail-sitter UAV including the aerodynamic effect of the wing, propellers, and slipstream was developed. The cascaded MPC controllers were then built upon linearized dynamic models. Path tracking simulations were conducted in a hardware-in-loop (HIL) environment where the UAV model and controllers were running on a PC and a flight computer independently. The simulation results show that the proposed MPC controllers are capable to perform good path tracking and the ability of disturbance rejection under limited on-board computation resource.
Original languageEnglish
Title of host publicationAIAA Modeling and Simulation Technologies
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624105289
Publication statusPublished - 1 Jan 2018
EventAIAA Modeling and Simulation Technologies Conference, 2018 - Kissimmee, United States
Duration: 8 Jan 201812 Jan 2018


ConferenceAIAA Modeling and Simulation Technologies Conference, 2018
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Modelling and Simulation
  • Aerospace Engineering

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