Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Department of Vehicle Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
Sensors (Basel). 2018 Aug 30;18(9):2859. doi: 10.3390/s18092859.
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.
本文提出了一种用于垂直起降（VTOL）倾转旋翼无人机（UAV）悬停飞行位置控制的模型预测控制器（MPC）。设计了一种具有悬停和高效率水平飞行能力的“十字”配置四旋翼倾转旋翼 UAV。基于风洞实验获得的空气动力学数据，建立了 UAV 的六自由度（DOF）非线性动力学模型。然后，利用增广线性化状态空间模型开发了模型预测位置控制器。在建模和优化过程中引入了测量和未测量的干扰模型，以提高干扰抑制能力。MPC 控制器首先在硬件在环（HIL）仿真环境中进行验证和调整，然后在机载飞行计算机上实现，用于实时室内实验。仿真和实验结果表明，在所提出的 MPC 位置控制器的条件下，在盛行风和阵风的情况下，具有良好的轨迹跟踪性能和鲁棒的位置保持能力。
