Event-Triggered Control for Switched Systems With Recurrent Neural Networks Subject to Stochastic Cyber-Attacks

This paper concentrates on event-triggered control for switched systems with recurrent neural networks. The significance of this paper is, a method of designing observers combined with event-triggered controllers for switched systems with neural networks is developed. Different from conventional switched systems, for the issue that when system state contains unknown items, this study adopts neural networks to approach the items. Then, considering the neural networks time-delay, transmission delay and stochastic cyber-attacks, closed-loop switched augmented estimation error systems are established. By utilizing multiple Lyapunov functions, sufficient conditions that guarantee the mean-square exponential stability of closed-loop switched systems are given. Subsequently, the controller and observer gains and event-triggering parameters are obtained. At last, a numerical simulation is provided to demonstrate the effectiveness of proposed method.