Adaptive Event-Triggered Nonfragile State Estimation for Fractional-Order Complex Networked Systems With Cyber Attacks

This article addresses the adaptive event-triggered nonfragile state estimation for the fractional-order complex networked systems subject to randomly occurring nonlinearities and adversarial network attacks, in which the order of fractional derivative operator satisfies 0 < p < 1 . To reduce...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2022-04, Vol.52 (4), p.2121-2133
Main Authors: Tan, Yushun, Xiong, Menghui, Zhang, Baoyong, Fei, Shumin
Format: Article
Language:English
Subjects:
Adaptive event-triggered scheme (AETS)
Circuit design
Complex networks
cyber attacks
Cyberattack
Cybersecurity
Feasibility
fractional-order complex networked system
Functionals
Linear matrix inequalities
nonfragile state estimation
Operators (mathematics)
randomly occurring nonlinearities
Singular value decomposition
Stability augmentation
State estimation
Stochastic processes
Uncertainty
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Summary:This article addresses the adaptive event-triggered nonfragile state estimation for the fractional-order complex networked systems subject to randomly occurring nonlinearities and adversarial network attacks, in which the order of fractional derivative operator satisfies 0 < p < 1 . To reduce unnecessary transmission burden as much as possible in an allowable range, an adaptive event-triggered scheme (AETS) is introduced to determine whether the data released by the sensor should be transmitted to the nonfragile state estimator. First, based on the considerations of the designed AETS and stochastic cyber-attacks, one constructs a newly fractional-order estimation error system model. Then, by employing the Lyapunov functional approach and the properties of Mittag-Leffler (M-L) functions, a sufficient condition is obtained to ensure the augmented error system stochastic mean-square stability; moreover, by making use of matrix's singular value decomposition (SVD), the desired nonfragile state estimator is designed, and the estimator gains can be obtained by finding the feasible solutions of linear matrix inequality (LMI). Finally, a numerical example and Chua's circuit model example are given to illustrate the feasibility of the designed nonfragile estimator.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2021.3049231