旋翼无人机作为低成本的新型遥感平台逐渐受到研究者与应用者的重视, 旋翼无人机搭载商用遥感, 具有地面分辨率高、响应迅速、使用维护方便等优点, 很好地弥补了传统遥感的缺陷, 在实际使用中抗干扰能力成为旋翼机遥感系统的重要性能指标。为了弥补常规多旋翼无人机航向控制力矩不足, 首先设计了六轴十二旋翼无人机结构并建立了其动力学模型, 然后针对农业遥感平台抗扰动能力的要求, 设计了专用的带有微分跟踪器、扩张状态观测器和非线性状态误差反馈控制律的自抗扰控制算法。其次通过仿真验证了控制器的稳定性与有效性, 通过实际风扰试验测试了该控制算法在11.2 m/s的短时风扰影响下仍保持良好的轨迹跟踪特性。最后在六轴十二旋翼无人机搭载自主研发的商品化微型高光谱仪MNS2001和两轴稳定云台, 在特定区域水稻上空定点进行光谱遥感测量, 在300~900 nm光谱范围内, 悬停区域上空多次测量的相对误差不超过5%, 试验表明该旋翼机遥感平台具有良好的稳定性和可靠性, 可以进一步应用于农业遥感领域并辅助生产管理。

As a new low-cost remote sensing platform, rotor UAV has been paid much attention by researchers and applications. Rotor UAV equipped with commercial remote sensing has many advantages, such as high ground resolution, quick response and easy maintenance, which make up for the shortcomings of traditional remote sensing, in practical use the anti-interference ability has become an important part of the remote sensing system of the rotor. In order to make up for the lack of conventional multi rotor torque heading control, firstly, six axis twelve-rotor UAV structure was designed and its dynamic model was established, then according to the anti disturbance capability of agricultural remote sensing platform requirements, the special algorithm of active disturbance rejection controller(ADRC) was designed with differential tracker, extended state observer and nonlinear state error feedback control law. Secondly, the stability and effectiveness of the controller was verified by simulation. The real wind disturbance test shows that the control algorithm maintains good trajectory tracking characteristics under the influence of instantaneous wind disturbance of 11.2 m/s. Finally, the UAV equipped with self-developed commercial high micro spectrometer MNS2001 and two axis stabilized in six axis twelve tilt rotor, fixed spectral remote sensing measurements in a particular area of rice over 300-900 nm in the spectral range, spectral reflectance hovering over the region of multiple measurement relative error was less than 5%. The test results show that the rotor has a good platform for remote sensing stability and reliability can be further applied in the field of agricultural remote sensing and auxiliary production management.