Development of model predictive controller for a tail-sitter VTOL UAV in hover flight

Boyang Li, Weifeng Zhou, Jingxuan Sun, Chih Yung Wen, Chih Keng Chen

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)


This paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.

Original languageEnglish
Article number2859
JournalSensors (Switzerland)
Issue number9
Publication statusPublished - Sept 2018


  • Flight experiment
  • Hardware-in-loop (HIL) simulation
  • Model predictive control (MPC)
  • Tail-sitter
  • Unmanned aerial vehicles (UAV)
  • Vertical takeoff and landing (VTOL)


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