Neural‐network‐based control for discrete‐time nonlinear systems with denial‐of‐service attack: The adaptive event‐triggered case

DOI10.1002/rnc.5831zbMath1527.93298OpenAlexW3202339433MaRDI QIDQ6063164

Xue-Li Wang, Derui Ding, Qing-Long Han, Xiaohua Ge

Publication date: 2 December 2023

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/rnc.5831

zbMATH Keywords

neural networksadaptive dynamic programmingdenial-of-service attacksadaptive event-triggered mechanism

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Discrete-time control/observation systems (93C55) Discrete event control/observation systems (93C65)

Related Items (6)

Proportional–integral-type estimator design for delayed recurrent neural networks under encoding–decoding mechanism ⋮ Distributed multi-step subgradient projection algorithm with adaptive event-triggering protocols: a framework of multiagent systems ⋮ Non-fragile l₂-l_∞ state estimation for time-delayed artificial neural networks: an adaptive event-triggered approach ⋮ Event-triggered ℒ ₂  − ℒ _∞ control for discrete-time Markov jump systems with DoS attacks and exogenous disturbance ⋮ Resource-efficient and secure distributed state estimation over wireless sensor networks: a survey ⋮ Fault detection of networked dynamical systems: a survey of trends and techniques

Cites Work

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