Event-driven synchronization of chaotic neural networks subject to actuator saturation

This paper discusses event-driven synchronization control problem for chaotic neural networks subject to actuator saturation. Firstly, in order to reduce the load of network, the event-driven scheme is introduced to determine whether the sampled state should be sent to the controller. Secondly, a synchronization error model is constructed to describe the master-slave synchronization system with event-driven scheme and actuator saturation in a unified framework. Thirdly, based on Lyapunov-Krasovskii functional, sufficient conditions for stabilization are obtained which can ensure synchronization of the master system and slave system; particularly, co-design of controller and the event-triggered matrix is achieved based on the above stability condition. Lastly, a numerical example is presented to show the effectiveness of the proposed approach.