Security event-triggered control for Markovian jump neural networks against actuator saturation and hybrid cyber attacks
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Publication:2230837
DOI10.1016/j.jfranklin.2021.07.022zbMath1471.93174OpenAlexW3190702403MaRDI QIDQ2230837
Yahan Deng, Hongqian Lu, Wu-Neng Zhou
Publication date: 28 September 2021
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jfranklin.2021.07.022
Discrete event control/observation systems (93C65) Stochastic systems in control theory (general) (93E03) Networked control (93B70)
Related Items (5)
Event-triggered finite-time synchronization for uncertain neural networks with quantizations ⋮ Resilient fixed-time synchronization of neural networks under DoS attacks ⋮ Improved criteria of sampled-data master-slave synchronization for chaotic neural networks with actuator saturation ⋮ Resilient adaptive event‐triggered synchronization control of piecewise‐homogeneous Markov jump delayed neural networks under aperiodic DoS attacks ⋮ Event‐triggered control of complex‐valued networked control systems under randomly occurring deception attacks
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