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An Experiment on Closed-loop System Identification of UAV Using Dual-rate Sampling

机译:双速率采样的无人机闭环系统辨识实验

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This paper reports on a closed-loop system identification experiment of an unmanned air vehicle (UAV) with the sampling period of the measured output being an integral multiple of the hold period of the control input. In more detail, the period of the control input of UAV is 5ms, while the position and attitude as the output of UAV are measured by a motion capture system with the sampling period 10ms. A dynamical model of UAV during hovering flight, which is an unstable system, is obtained using a dual-rate closed-loop subspace model identification method. The key point of our method is to apply a closed-loop subspace model identification method proposed by the authors, in order to obtain the so-called lifted model from dual-rate sampling data. Practical usefulness of our dual-rate closed-loop subspace model identification method has been demonstrated by the lab-scale real-life experiment.
机译:本文报道了一种无人机的闭环系统识别实验,该实验的实测输出采样周期为控制输入保持周期的整数倍。更详细地,无人飞行器的控制输入的周期是5ms,而作为无人飞行器的输出的位置和姿态是由运动捕获系统以10ms的采样周期来测量的。利用双速率闭环子空间模型辨识方法,获得了一种不稳定的无人机悬停飞行过程中的动力学模型。该方法的重点是应用作者提出的闭环子空间模型识别方法,以便从双速率采样数据中获得所谓的提升模型。通过实验室规模的实际实验证明了我们的双速率闭环子空间模型识别方法的实用性。

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