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Mixed H2/H∞ State Estimation for Discrete-Time Switched Complex Networks With Random Coupling Strengths Through Redundant Channels.

Authors :
Chen, Yun
Wang, Zidong
Wang, Licheng
Sheng, Weiguo
Source :
IEEE Transactions on Neural Networks & Learning Systems. Oct2020, Vol. 31 Issue 10, p4130-4142. 13p.
Publication Year :
2020

Abstract

This article investigates the mixed H2/H∞ state estimation problem for a class of discrete-time switched complex networks with random coupling strengths through redundant communication channels. A sequence of random variables satisfying certain probability distributions is employed to describe the stochasticity of the coupling strengths. A redundant-channel-based data transmission mechanism is adopted to enhance the reliability of the transmission channel from the sensor to the estimator. The purpose of the addressed problem is to design a state estimator for each node, such that the error dynamics achieves both the stochastic stability (with probability 1) and the prespecified mixed H2/H∞ performance requirement. By using the switched system theory, an extensive stochastic analysis is carried out to derive the sufficient conditions ensuring the stochastic stability as well as the mixed H2/H∞ performance index. The desired state estimator is also parameterized by resorting to the solutions to certain convex optimization problems. A numerical example is provided to illustrate the validity of the proposed estimation scheme. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
2162237X
Volume :
31
Issue :
10
Database :
Academic Search Index
Journal :
IEEE Transactions on Neural Networks & Learning Systems
Publication Type :
Periodical
Accession number :
146358969
Full Text :
https://doi.org/10.1109/TNNLS.2019.2952249