Minimum-time Path Convergence for UAVs in Wind Using Vector Field Guidance

Atharva Navsalkar, Sikha Hota
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Abstract

We present a novel guidance algorithm for unmanned aircraft to converge to a smooth path optimising time in the presence of wind. A Lyapunov vector field based method is used to achieve convergence and tracking. The proposed framework performs better in comparison with the similar work existing in literature. The presented approach modifies the vector field according to the velocity of the wind, facilitating faster convergence. A customised optimisation algorithm is then used to find a suitable design parameter for vector fields. To demonstrate the efficacy of the proposed approach, numerical simulations are shown and the results are compared with the optimal time paths obtained using optimal control theory.
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基于矢量场制导的无人机风场最小时间路径收敛
提出了一种新的无人驾驶飞机在有风情况下收敛到平滑路径优化时间的制导算法。采用基于李雅普诺夫向量场的方法来实现收敛和跟踪。与文献中已有的类似工作相比,所提出的框架表现得更好。该方法根据风速对矢量场进行修正,加快了收敛速度。然后使用定制的优化算法为矢量场找到合适的设计参数。为了验证该方法的有效性,进行了数值仿真,并将仿真结果与最优控制理论得到的最优时间路径进行了比较。
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