Optimal control of UAVs using the sparse grid characteristic method
Optimal control of UAVs using the sparse grid characteristic method
复制标题
利用稀疏网格特征法对无人机进行优化控制
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
L. Wilcox
中科院分区：
文献类型：
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作者：
W. Kang;O. Yakimenko;L. Wilcox
利用反馈控制实现无人驾驶车辆的实时最优机动需要高效的计算算法。无人机的稳定性和跟踪控制得到了广泛的应用。然而，需要最小化成本函数的无人机的最优控制是具有挑战性的。本文的方法是基于稀疏网格特征方法。在求解HJB方程时，使用稀疏网格来减轻维数的困扰。在每个网格点上，使用基于庞特里亚金极大（或极小）原理的特征方法计算最优控制。该算法由两部分组成，一是设计反馈控制律的HJB方程的离线计算算法，二是利用插值法实现实时地平线后退控制的在线算法。将该方法应用于无人机模型，对闭环控制进行了验证。
Real-time optimal maneuvering of unmanned vehicles using feedback control requires efficient computational algorithms. Stability and tracking controls of UAVs have been widely used. However, the optimal control of UAVs that requires minimizing a cost functional is challenging. The approach in this paper is based on a sparse grid characteristic method. Sparse grids are used to mitigate the curse of dimensionality in solving the HJB equation. At each grid point, the optimal control is computed using the characteristic method based on the Pontryagin Maximum (or Minimum) Principle. The algorithm consists of two parts, the off-line computational algorithm to solve the HJB equation for the design of a feedback control-law and the on-line algorithm for real-time receding horizon control using interpolation. The method is applied to a UAV model to test the closed-loop control.