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Self-Triggered Consensus Filtering over Asynchronous Communication Sensor Networks

Huiwen Xue1, Jiwei Wen1,*, Akshya Kumar Swain1, Xiaoli Luan1

1 Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214000, China
2 Department of Electrical, Computer and Software Engineering, University of Auckland, Auckland, 0632, New Zealand

* Corresponding Author: Jiwei Wen. Email: email

(This article belongs to this Special Issue: Advances on Modeling and State Estimation for Industrial Processes)

Computer Modeling in Engineering & Sciences 2023, 134(2), 857-871. https://doi.org/10.32604/cmes.2022.020127

Abstract

In this paper, a self-triggered consensus filtering is developed for a class of discrete-time distributed filtering systems. Different from existing event-triggered filtering, the self-triggered one does not require to continuously judge the trigger condition at each sampling instant and can save computational burden while achieving good state estimation. The triggering policy is presented for pre-computing the next execution time for measurements according to the filter’s own data and the latest released data of its neighbors at the current time. However, a challenging problem is that data will be asynchronously transmitted within the filtering network because each node self-triggers independently. Therefore, a co-design of the self-triggered policy and asynchronous distributed filter is developed to ensure consensus of the state estimates. Finally, a numerical example is given to illustrate the effectiveness of the consensus filtering approach.

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Cite This Article

Xue, H., Wen, J., Swain, A. K., Luan, X. (2023). Self-Triggered Consensus Filtering over Asynchronous Communication Sensor Networks. CMES-Computer Modeling in Engineering & Sciences, 134(2), 857–871.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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