Position control of a tail-sitter UAV using successive linearization based model predictive control. (October 2019)

• Record Type: Journal Article
• Authors: Zhou, Weifeng; Li, Boyang; Sun, Jingxuan; Wen, Chih-Yung; Chen, Chih-Keng
• Is Part Of: Control engineering practice. Volume 91(2019)
• Publication Date: 2019-10
• Subjects: Tail-sitter -- VTOL -- UAV -- MPC -- Aerodynamic -- Disturbance; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2019.104125
• Languages: English
• ISSNs: 0967-0661

Abstract

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 Highlights: A vertical take-off and landing tail-sitter unmanned aerial vehicle is controlled. A successive linearization based model predictive control method is proposed. The aerodynamic model is augmented in the SLMPC method. The weight parameter in the objective function can be time varying. The tail-sitter UAV has been tested in both simulation and flight test.