@inproceedings{113cde31d36d43eca39b0fa7b1529c34,
title = "Model predictive control for path tracking of a VTOL tail-sitter UAV in an HIL simulation environment",
abstract = "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.",
author = "Boyang Li and Weifeng Zhou and Jingxuan Sun and Wen, {Chih Yung} and Chen, {Chih Keng}",
note = "Funding Information: This work is supported by Innovation and Technology Commission, Hong Kong under Contract No. ITS/334/15FP. Publisher Copyright: {\textcopyright} 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.; AIAA Modeling and Simulation Technologies Conference, 2018 ; Conference date: 08-01-2018 Through 12-01-2018",
year = "2018",
doi = "10.2514/6.2018-1919",
language = "English",
isbn = "9781624105289",
series = "AIAA Modeling and Simulation Technologies Conference, 2018",
publisher = "American Institute of Aeronautics and Astronautics Inc. (AIAA)",
number = "209959",
booktitle = "AIAA Modeling and Simulation Technologies",
address = "United States",
edition = "209959",
}