Static output feedback secure synchronization control for Markov jump neural networks under hybrid cyber-attacks

Ziwei Zhang, Zongjie Chen, Zhang Sheng, Dan Li and Jing Wang

Applied Mathematics and Computation, 2022, vol. 430, issue C

Abstract: This paper investigates the secure synchronization control problem for Markov jump neural networks subjected to cyber-attacks where the synchronization controller is based on mode-independent static output feedback strategy. The communication networks are supposed to be subject to mixed forms of cyber-attacks: deception attack and denial of service attack. The fundamental purpose concentrates that how to achieve stochastic stability of closed-loop system by applying the static output feedback strategy regardless of whether hybrid cyber-attacks occur. Furthermore, with the help of Lyapunov stability theory and linear matrix inequality technology, sufficient conditions to guarantee that the closed-loop system satisfies the specified H∞/passive performance are established. Then, the specific expression of static output feedback controller is indicated by an effective decoupling method. Eventually, a numerical example verifies the effectiveness of the proposed approach.

Keywords: Markov jump neural networks; Static output feedback strategy; Deception attack; Denial of service attack (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003484

DOI: 10.1016/j.amc.2022.127274

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