Distributed resilient state estimation over sensor networks with random nonlinearities, fading measurements, and stochastic gain variations

The distributed H∞ resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under consideration involves three phenomena of incomplete information: randomly occurring nonlinearities, fading measurements, and random gain var...

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Published inInternational journal of robust and nonlinear control Vol. 32; no. 3; pp. 1510 - 1525
Main Authors Qian, Wei, Guo, Simeng, Zhao, Yunji, Fei, Shumin
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 01.02.2022
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Abstract The distributed H∞ resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under consideration involves three phenomena of incomplete information: randomly occurring nonlinearities, fading measurements, and random gain variations. The probabilistic characteristics of the above phenomena are depicted by three sets of independent random variables subject to more general random distribution. Based on the above model, by applying Lyapunov functional approach and random distribution solution method, the asymptotic stability in the mean square sense of the estimation error system with a given H∞ attenuation level is proved. Further, the estimator parameters are solved by introducing a novel linearization method. Finally, a numerical simulation is given to illustrate the validity of the theoretical results.
AbstractList The distributed H∞ resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under consideration involves three phenomena of incomplete information: randomly occurring nonlinearities, fading measurements, and random gain variations. The probabilistic characteristics of the above phenomena are depicted by three sets of independent random variables subject to more general random distribution. Based on the above model, by applying Lyapunov functional approach and random distribution solution method, the asymptotic stability in the mean square sense of the estimation error system with a given H∞ attenuation level is proved. Further, the estimator parameters are solved by introducing a novel linearization method. Finally, a numerical simulation is given to illustrate the validity of the theoretical results.
The distributed resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under consideration involves three phenomena of incomplete information: randomly occurring nonlinearities, fading measurements, and random gain variations. The probabilistic characteristics of the above phenomena are depicted by three sets of independent random variables subject to more general random distribution. Based on the above model, by applying Lyapunov functional approach and random distribution solution method, the asymptotic stability in the mean square sense of the estimation error system with a given attenuation level is proved. Further, the estimator parameters are solved by introducing a novel linearization method. Finally, a numerical simulation is given to illustrate the validity of the theoretical results.
Author Fei, Shumin
Qian, Wei
Zhao, Yunji
Guo, Simeng
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CitedBy_id crossref_primary_10_1080_00207721_2022_2062802
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crossref_primary_10_1016_j_ins_2023_119288
crossref_primary_10_1109_TNSE_2022_3229889
crossref_primary_10_1016_j_automatica_2023_111408
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Snippet The distributed H∞ resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under...
The distributed resilient state estimation problem of nonlinear discrete systems in sensor networks is investigated in this article. The system model under...
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SubjectTerms Asymptotic methods
Attenuation
Discrete systems
distributed resilient state estimation
Fading
fading measurements
H-infinity control
Independent variables
Mathematical models
Nonlinear systems
Nonlinearity
Parameter estimation
random gain variations
Random variables
randomly occurring nonlinearities
sensor network
State estimation
Title Distributed resilient state estimation over sensor networks with random nonlinearities, fading measurements, and stochastic gain variations
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Frnc.5905
https://www.proquest.com/docview/2617107501
Volume 32
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