Wang, Jiazheng and Ren, Xiaoqiang and Dey, Subhrakanti and Shi, Ling (2021) Remote state estimation with usage-dependent Markovian packet losses. Automatica, 123. p. 109342. ISSN 0005-1098

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Abstract

In this paper, we consider a problem of packet scheduling in the setting of remote estimation with usage-dependent Markovian packet losses. A sensor measures the state of a discrete-time linear process, computes the estimate via a local Kalman filter, and sends the packets to a remote estimator via a network. The link state evolves as a two-state Markov chain, and its state transition depends on the network usage. The aim is to design the scheduling policy which balances the estimation quality and the energy consumption. We identify the problem as a Markov decision process (MDP) and prove the structural properties of the optimal policy. Furthermore, based on the structural properties, we derive the sufficient and necessary condition of the mean square stability of the remote estimator. Simulation examples are provided to illustrate the results.

Item Type:	Article
Keywords:	Kalman filters; State estimation; Networked control systems; Markov decision processes;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	18496
Identification Number:	https://doi.org/10.1016/j.automatica.2020.109342
Depositing User:	Subhrakanti Dey
Date Deposited:	09 May 2024 11:27
Journal or Publication Title:	Automatica
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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