Further results on event-triggered H∞ networked control for neural networks with stochastic cyber-attacks
作者：
Highlights：
• A new adaptive event-triggered scheme is introduced to save the system resources and decrease spurious triggering events.
• Based on the adaptive event-triggered scheme and the networked control, the closed-loop system is established for NNs subject to two types of stochastic cyber-attacks and limited network bandwidth.
• By making full use of information on the time-varying delays, the adaptive event trigger’s parameters, the neuron activation function and the cyber-attacks functions, a new LKF is constructed to derive less conservative condition for the closed-loop system to be mean-square asymptotically stable with a prescribed H∞ performance. Based on the condition, desired control gain is determined.
摘要
•A new adaptive event-triggered scheme is introduced to save the system resources and decrease spurious triggering events.•Based on the adaptive event-triggered scheme and the networked control, the closed-loop system is established for NNs subject to two types of stochastic cyber-attacks and limited network bandwidth.•By making full use of information on the time-varying delays, the adaptive event trigger’s parameters, the neuron activation function and the cyber-attacks functions, a new LKF is constructed to derive less conservative condition for the closed-loop system to be mean-square asymptotically stable with a prescribed H∞ performance. Based on the condition, desired control gain is determined.
论文关键词：Event-triggered scheme,Neural networks,Mean-square stable,Stochastic cyber-attacks,H∞ Performance
论文评审过程：Received 5 January 2020, Revised 5 May 2020, Accepted 31 May 2020, Available online 18 July 2020, Version of Record 18 July 2020.
论文官网地址：https://doi.org/10.1016/j.amc.2020.125431
