Title
Generalized State Estimation for Markovian Coupled Networks Under Round-Robin Protocol and Redundant Channels.
Abstract
In this paper, the problem of generalized state estimation for an array of Markovian coupled networks under the round-Robin protocol (RRP) and redundant channels is investigated by using an extended dissipative property. The randomly varying coupling of the networks under consideration is governed by a Markov chain. With the aid of using the RRP, the transmission order of nodes is availably orchestrated. In this case, the probability of occurrence data collisions through a shared constrained network may be reduced. The redundant channels are also used in the signal transmission to deal with the frangibility of networks caused by a single channel in the networks. The network induced phenomena, that is, randomly occurring packet dropouts and randomly occurring quantization are fully considered. The main purpose of the research is to find a desired estimator design approach such that the extended (Ω₁,Ω₂,Ω₃) - ɣ-stochastic dissipativity property of the estimation error system is guaranteed. In terms of the Lyapunov-Krasovskii methodology, the Kronecker product and an improved matrix decoupling approach, sufficient conditions for such an addressed problem are established by means of handling some convex optimization problems. Finally, the serviceability of the proposed method is explained by providing an illustrated example.
Year
DOI
Venue
2019
10.1109/TCYB.2018.2799929
IEEE transactions on cybernetics
Keywords
Field
DocType
State estimation,Channel estimation,Symmetric matrices,Protocols,Markov processes,Quantization (signal)
Transmission (telecommunications),Topology,Mathematical optimization,Markov process,Kronecker product,Markov chain,Symmetric matrix,Quantization (signal processing),Convex optimization,Mathematics,Estimator
Journal
Volume
Issue
ISSN
49
4
2168-2275
Citations 
PageRank 
References 
32
0.72
12
Authors
4
Name
Order
Citations
PageRank
Hao Shen1107469.50
Shicheng Huo2452.25
Jinde Cao311399733.03
Tingwen Huang45684310.24