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System Identification Guidance For Multirotor Aircraft: Dynamic Scaling and Test Techniques

机译:多旋翼飞机系统识别指南:动态缩放和测试技术

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State-space system identification was performed in order to extract flight dynamic models for hovering flight of a 56 cm, 1.56 kg hexacopter unmanned aerial vehicle (UAV). Different input excitation techniques were tested to determine which maneuvers provided high quality system identification results for small scale multirotor vehicles. These input excitation techniques included automated frequency sweeps, varying in amplitude, and multi-sine sweeps. Coherence, Cramer-Rao bounds, and insensitivities were used as metrics for comparing the system identification results. A parametric variation of frequency sweep amplitudes were performed in all axes (roll, yaw, pitch and heave) in order to provide guidance on frequency sweep amplitude for small scale multirotor unmanned aerial systems (UAS). The dynamics of the 56 cm hexacopter were used to estimate the dynamics of a larger 127 cm hexacopter via Froude scaling based on hub-to-hub distance as the characteristic length. The scaled results were compared to an actual system identification model of a 127 cm hexacopter.
机译:进行状态空间系统识别,以提取用于56厘米,1.56千克六直升机无人飞行器(UAV)悬停飞行的飞行动力学模型。测试了不同的输入励磁技术,以确定哪种机动为小型多旋翼飞行器提供了高质量的系统识别结果。这些输入激励技术包括自动扫频,幅度变化和多正弦扫频。相干性,Cramer-Rao界和不敏感度用作比较系统识别结果的指标。在所有轴(侧倾,偏航,俯仰和升沉)上执行了扫频幅度的参数变化,以便为小型多旋翼无人机系统(UAS)的扫频幅度提供指导。 56厘米六旋翼飞机的动力学用于通过轮毂到轮毂的距离作为特征长度的Froude比例估计更大的127厘米六旋翼飞机的动力学。将缩放后的结果与127厘米六轴飞行器的实际系统识别模型进行了比较。

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