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Distributed Extremum Seeking with Stochastic Perturbations

机译:随机扰动寻求分布的极值

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This paper considers seeking an unknown source in the two-dimensional (2D) space with a multi-agent system. Each agent has no knowledge about its own position and the distribution of the source signal. To resolve these challenges, we design distributed extrmum seeking (ES) controllers with stochastic perturbations for the multi-agent system, where each agent carries a single sensor to measure the value of the signal strength at its current position and cooperates with its neighbors. We prove the local exponential convergence of the multi-agent system, both almost surely and in probability, to a small neighborhood of the source by stochastic averaging theory. In addition, the distributed ES controllers are applied into nonholonomic unicycles by introducing a coordinate transformation. Finally, simulations illustrate the effectiveness of the distributed ES controllers.
机译:本文考虑了使用多智能体系的二维(2D)空间中的未知源。每个代理都没有了解其自己的位置和源信号的分布。为了解决这些挑战,我们设计具有用于多种子体系统的随机扰动的分布式Extrumum寻找,其中每个试剂带有单个传感器,以测量其当前位置处的信号强度的值并与其邻居配合。我们通过随机平均理论证明了多助理系统的局部指数融合,几乎肯定地,几乎肯定地和概率,到源的小邻域。此外,通过引入坐标变换,分布式ES控制器被应用于非完整的单体剪辑。最后,模拟说明了分布式ES控制器的有效性。

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