多传感器和基于信息的事件触发分布式估计

Somayeh Davar, Arash Mohammadi
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摘要

本文的动机是最近对网络物理系统(cps)中大量传感器节点的利用的兴趣激增,以及管理传感器有限资源的关键重要性。为此,我们提出了一种基于信息触发机制的多传感器开环估计算法。在本文所考虑的开环拓扑中,每个传感器仅在特定事件(异步)发生时才将其测量值传输到融合中心(FC)。使用基于信息的触发机制识别事件,而不包含来自FC的反馈和/或在传感器级别实现本地滤波器。我们提出了一种基于每个局部观测到状态空间的投影的多传感器触发方法,该方法对应于传感器信息状态向量中可实现的增益。仿真结果表明,所提出的基于多传感器信息的触发机制与全速率估计机制基本一致。
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Multi-sensor and Information-Based Event Triggered Distributed Estimation
The paper is motivated by recent surge of interest in utilization of a large number of sensor nodes in cyber-physical systems (CPSs) and the critical importance of managing sensor's restricted resources. In this regard, we propose a multi-sensor and open-loop estimation algorithm with an information-based triggering mechanism. In the open-loop topology considered in this paper, each sensor transfers its measurements to the fusion centre (FC) only in occurrence of specific events (asynchronously). Events are identified using the information-based triggering mechanism without incorporation of a feedback from the FC and/or implementation of a local filter at the sensor level. We propose a multi-sensor triggering approach based on the projection of each local observation into the state-space which corresponds to the achievable gain in the sensor's information state vector. The simulation results show that the proposed multi-sensor information-based triggering mechanism closely follows its full-rate estimation counterpart.
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