Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/78169
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Title: Model predictive control for path tracking of a VTOL tail-sitter UAV in an HIL simulation environment
Authors: Li, B 
Zhou, W 
Sun, J 
Wen, CY 
Chen, CK
Issue Date: 2018
Source: AIAA Modeling and Simulation Technologies Conference, 8-12 January 2018, Kissimmee, United States, AIAA 2018-1919, Session: Modeling and Simulation of Unmanned Aerial Systems
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.
Publisher: American Institute of Aeronautics and Astronautics Inc, AIAA
ISBN: 9781624105289
DOI: 10.2514/6.2018-1919
Rights: Copyright © 2018 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
This is the peer reviewed version of the following article: Li, B., Zhou, W., Sun, J., Wen, C., & Chen, C. (2018). Model predictive control for path tracking of a VTOL tailsitter UAV in an HIL simulation environment. In AIAA Modeling and Simulation Technologies Conference, 8-12 January 2018, Kissimmee, United States, AIAA 2018-1919, which has been published in final form at https://doi.org/10.2514/6.2018-1919.
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