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Parameter Identification Method for Quad-Rotor UAV Based on the Lyapunov-MARI Algorithm

机译:基于Lyapunov-MARI算法的四旋翼无人机参数辨识方法

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The traditional parameter identification method of the quad-rotor UAV (Unmanned Aerial Vehicle) model requires special experimental equipment, and the experimental process is very complex. To overcome this problem, the current paper proposes a Lyapunov-MARI (Model Reference Adaptive Identification) algorithm, which only needs the UAV and some common sensors to realize the parameter identification. Firstly, the current paper determines specific parameters which are not easy to be measured in the quad-rotor UAV model. These parameters mainly include the three axis moments of inertia, the rotors lift coefficient and drag coefficient. Then, for the moments of inertia, the traditional period measurement method of the Rope Suspension Approach is improved. For the lift and drag coefficients, the Lyapunov-MARI algorithm is proposed for the parameter identification. The result shows that the flight state calculated by the identified parameters are compatible with the actual flight data.
机译:四旋翼无人机模型的传统参数识别方法需要专用的实验设备,实验过程非常复杂。为了克服这个问题,本文提出了一种Lyapunov-MARI(模型参考自适应识别)算法,该算法仅需要无人机和一些通用的传感器即可实现参数识别。首先,本文确定了在四旋翼无人机模型中不易测量的特定参数。这些参数主要包括三个轴的惯性矩,转子的升力系数和阻力系数。然后,对于惯性矩,改进了“绳索悬吊法”的传统周期测量方法。对于升力和阻力系数,提出了Lyapunov-MARI算法进行参数辨识。结果表明,由所识别的参数计算出的飞行状态与实际飞行数据兼容。

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