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Consensus-based Distributed Kalman-Bucy Filter for Continuous-time Systems

机译:基于共识的连续时间分布式卡尔曼-Bucy滤波器

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Abstract: In this paper we introduce a distributed consensus-based Kalman filter for distributed state estimation of continuous-time systems. In particular, we achieve stability of the estimation error only assuming that all agents together are able to observe the system, which is in contrast to each agent possessing this property individually. The algorithm is implementable without any precomputation of filter parameters, such as coupling strength, or global knowledge about the graph.
机译:摘要:在本文中,我们介绍了一种基于分布共识的卡尔曼滤波器,用于连续时间系统的分布状态估计。特别是,我们仅在所有代理都能够观测系统的前提下,才能实现估计误差的稳定性,这与每个拥有该属性的代理形成对比。该算法无需滤波器参数的任何预计算即可实现,例如耦合强度或关于图形的全局知识。

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