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Neural network approach for solving UAV team cooperative control

机译:神经网络解决无人机团队协同控制的方法

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One of the key algorithm research areas for unpiloted aerial vehicles team cooperative control is solution of network optimization models. Computational speed is an important success criterion as much of the cooperative work is done in real time. The linear programming (LP) class of approaches has been shown to be the fastest technique according to AFRL's work. In this paper a neural network (NN) approach to solving the constrained LP problem will be introduced and compared to a typical public domain LP solver. Computational time will be used as a comparison and it will be shown that significant time savings results from the NN approach.
机译:网络优化模型的求解是无人飞行器队协同控制的关键算法研究领域之一。计算速度是一个重要的成功标准,因为许多协作工作都是实时完成的。根据AFRL的工作,线性编程(LP)类方法已被证明是最快的技术。本文将介绍一种用于解决约束LP问题的神经网络(NN)方法,并将其与典型的公共领域LP解算器进行比较。计算时间将用作比较,并且将显示NN方法可节省大量时间。

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