Distributed estimation based on weighted data aggregation over delayed sensor networks

In this paper, data aggregation laws and distributed observers over delayed sensor networks with any topology are proposed. In the proposed method, each node compensates communication delays of received data. For the delay compensation, each node predicts the future output based on state space model...

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Bibliographic Details
Published inIFAC Journal of Systems and Control Vol. 14; p. 100109
Main Authors Adachi, Ryosuke, Yamashita, Yuh, Kobayashi, Koichi
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.12.2020
Subjects
Distributed estimation
Sensor network
Distributed estimation
Sensor network
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Summary:In this paper, data aggregation laws and distributed observers over delayed sensor networks with any topology are proposed. In the proposed method, each node compensates communication delays of received data. For the delay compensation, each node predicts the future output based on state space models. To stabilize the aggregation data in any networks, the received data are multiplied by weight coefficients before the aggregation. The stability condition of the weighted aggregation laws is expressed by a weighted adjacency matrix. The aggregated value of the measurements at each node is expressed by a linear time-varying function of the current state. To estimate the state, we utilize the Kalman filters as the distributed observers. The effectiveness of the proposed method is confirmed by a numerical simulation.
ISSN:2468-6018
2468-6018
DOI:10.1016/j.ifacsc.2020.100109