Implementation Details and Flight Test Results of an Autonomous Soaring Controller
Implementation Details and Flight Test Results of an Autonomous Soaring Controller
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自主翱翔控制器的实施细节和飞行测试结果
DOI：
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发表时间：
2008
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通讯作者：
Daniel J. Edwards
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作者：
Daniel J. Edwards
* 仅使用140米发射的初始能量，一架自主滑翔机就覆盖了48公里，并通过主动搜索和利用自然发生的对流空气上升气流（热气流）在高空停留了1.5小时以上。北卡罗来纳州州立大学和美国海军研究实验室设计并实现了这种新的对流空气上升气流定位和制导算法的滑翔机为基础的无人机系统（UAS）。利用车辆能量变化率和车辆速度极坐标估计局部空气垂直运动。接下来，上升气流最初地理定位与基于质心的中心估计器作用于本地空气运动估计。然后，一个自适应网格的节点是实时构建的，每个节点的非线性回归相关系数计算，并选择最高的相关性节点，产生更好的中心估计。车辆指令速度已优化使用麦克里迪速度飞行理论，加上速度环，以提高越野性能。用飞行数据的样本演示了风漂校正、无相位滞后滤波和非线性上升气流参数化的效果。
*Using only the initial energy from a 140m launch, an autonomous soaring glider covered over 48km and stayed aloft for over 1.5hr by actively searching out and using naturally occurring convective air updrafts (thermals). North Carolina State University and the U.S. Naval Research Laboratory have designed and implemented this novel convective air updraft locating and guidance algorithm for glider-based unmanned aerial systems (UAS). The local air vertical motion is estimated using the vehicle energy rate of change and the vehicle speed polar. Next, updrafts are initially geo-located with a centroid-based center estimator acting on the local air motion estimates. Then, an adaptive grid of nodes is constructed in real-time, the nonlinear regression correlation coefficient for each node computed, and the highest correlation node chosen, yielding much improved center estimation. Vehicle commanded speed has been optimized using MacCready Speed-to-Fly theory, coupled with a Speed Ring to increase cross-country performance. The effects of wind-drift correction, no-phase-lag filtering, and nonlinear updraft-parameterization are demonstrated with samples of flight data.