Output synchronization of reaction–diffusion neural networks under random packet losses via event-triggered sampled–data control

Abstract

For space-varying reaction–diffusion neural networks (RDNNs), this article mainly studies the output synchronization via an event-triggered sampled-data (ETSD) control under spatially point measurements (SPMs) with random packet losses. To reduce the communication burden, an ETSD control scheme is adopted to decrease the unnecessary SD and the update frequency of the controller. Meanwhile, the problem of random packet losses in the communication channels from controller to actuator is considered. Some synchronization criteria based on spatial linear matrix inequalities (SLMIs) are established through an ETSD controller under SPMs with random packet losses to guarantee the mean square exponential stability of synchronization error system with drive and response dynamics via utilizing inequality techniques and Lyapunov functional. Furthermore, we express SLMIs as LMIs for solving the ETSD control design problem for output synchronization of space-varying RDNNs. Finally, the effectiveness of the proposed method is demonstrated by one numerical example.