Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89371
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Title: Position control of a tail-sitter UAV using successive linearization based model predictive control
Authors: Zhou, W 
Li, B 
Sun, J 
Wen, CY 
Chen, CK
Issue Date: Oct-2019
Source: Control engineering practice, Oct. 2019, v. 91,104125, p. 1-13
Abstract: A successive linearization based model predictive control (SLMPC) method is proposed to control a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hovering flight. The dynamic model of the vehicle is derived, including a low-fidelity aerodynamic model and a propulsion system model. The position controller is developed by a state–space prediction model augmented with estimated disturbance and feedback integration terms. The time-varying weight in the objective function is included and the velocity of vehicle is considered as reference to improve the performance. The system is first tested in a software-in-loop environment followed by the real-time indoor flight tests. The results demonstrate the vehicle can precisely follow a trajectory and stably hold position under unsteady wind disturbance.
Keywords: Aerodynamic
Disturbance
MPC
Tail-sitter
UAV
VTOL
Publisher: Pergamon Press
Journal: Control engineering practice 
ISSN: 0967-0661
DOI: 10.1016/j.conengprac.2019.104125
Rights: © 2019 Elsevier Ltd. All rights reserved.
© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Zhou, W., Li, B., Sun, J., Wen, C.-Y., & Chen, C.-K. (2019). Position control of a tail-sitter UAV using successive linearization based model predictive control. Control Engineering Practice, 91, 104125 is available at https://dx.doi.org/10.1016/j.conengprac.2019.104125.
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