Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks

Chantapish Zamart; Thongchai Botmart; Wajaree Weera; Prem Junsawang; Chantapish Zamart; Thongchai Botmart; Wajaree Weera; Prem Junsawang

doi:10.3934/math.20231136

AIMS Mathematics

2023, Volume 8, Issue 9: 22274-22300. doi: 10.3934/math.20231136

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Research article

Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks

1.
Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand
2.
Department of Statistics, Faculty of Science, Khon Kaen University, Khon Kaen, 40002, Thailand

Received: 07 May 2023 Revised: 09 June 2023 Accepted: 26 June 2023 Published: 13 July 2023
MSC : 34D20, 37C75, 39A30

This article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyber-attacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor measurements should be sent out. The cyber-attacks that occur at random are described employing Bernoulli distributed variables. By the Lyapunov-Krasovskii stability theory, we apply an integral inequality with an exponential function to estimate the derivative of the Lyapunov-Krasovskii functionals (LKFs). We present new sufficient conditions in the form of linear matrix inequalities. The main objective of this research is to investigate the stochastic finite-time boundedness of GNNs with mixed interval time-varying delays and cyber-attacks by providing a decentralized event-triggered method and feedback controller. Finally, a numerical example is constructed to demonstrate the effectiveness and advantages of the provided control scheme.
- generalized neural networks,
- finite-time stability,
- time-varying delays,
- feedback control,
- cyber-attacks,
- decentralized event-triggered scheme
Citation: Chantapish Zamart, Thongchai Botmart, Wajaree Weera, Prem Junsawang. Finite-time decentralized event-triggered feedback control for generalized neural networks with mixed interval time-varying delays and cyber-attacks[J]. AIMS Mathematics, 2023, 8(9): 22274-22300. doi: 10.3934/math.20231136

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Abstract

This article investigates the finite-time decentralized event-triggered feedback control problem for generalized neural networks (GNNs) with mixed interval time-varying delays and cyber-attacks. A decentralized event-triggered method reduces the network transmission load and decides whether sensor measurements should be sent out. The cyber-attacks that occur at random are described employing Bernoulli distributed variables. By the Lyapunov-Krasovskii stability theory, we apply an integral inequality with an exponential function to estimate the derivative of the Lyapunov-Krasovskii functionals (LKFs). We present new sufficient conditions in the form of linear matrix inequalities. The main objective of this research is to investigate the stochastic finite-time boundedness of GNNs with mixed interval time-varying delays and cyber-attacks by providing a decentralized event-triggered method and feedback controller. Finally, a numerical example is constructed to demonstrate the effectiveness and advantages of the provided control scheme.

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