Macroscopic model-based swarm guidance for a class of contaminant tracking applications
Macroscopic model-based swarm guidance for a class of contaminant tracking applications
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DOI：
10.1080/00207179.2020.1833250
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发表时间：
2020-10
影响因子：
2.1
通讯作者：
Meysam Ghanavati;A. Chakravarthy;P. Menon
中科院分区：
文献类型：
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作者：
Meysam Ghanavati;A. Chakravarthy;P. Menon
本文解决了引导一群无人机 (UAV) 跟踪 3 维空间中污染物时空演化的问题。污染物和无人机群均使用偏微分方程 (PDE) 进行建模。使用平流偏微分方程对污染物的扩散进行建模，而控制无人机群的偏微分方程则基于非线性气体动力学模型。基于动态反演的方法与优化公式相结合，用于设计最佳制导律，使无人机群能够跟踪污染物的演变，从而使无人机群采用其空间密度分布与污染物密度成正比的配置。评估了制导律对群内无人机之间未知相互作用影响的鲁棒性。通过模拟说明了制导律的有效性。
In this paper, the problem of guidance of a swarm of Unmanned Aerial Vehicles (UAVs) to track the spatio-temporal evolution of a contaminant in 3-dimensional space is addressed. The contaminant and the UAV swarm are both modelled using Partial Differential Equations (PDEs). The spread of the contaminant is modelled using an advection PDE, while the PDE governing the UAV swarm is based on a nonlinear gas dynamic-like model. A dynamic inversion-based approach, combined with an optimisation formulation, is used to design optimal guidance laws that enable the UAV swarm to track the evolution of the contaminant, so that the swarm takes a configuration such that its spatial density distribution is proportional to the contaminant density. The robustness of the guidance laws to the unknown interaction effects among the UAVs within the swarm is assessed. The efficacy of the guidance laws is illustrated using simulations.