Cluster synchronization for nonlinearly time-varying delayed coupling complex networks with stochastic perturbation via periodically intermittent pinning control

Sampled-data state estimation for a class of delayed complex networks via intermittent transmission

“…Hence, a multitude of literatures have studied dynamical behaviors of delayed complex networks since time delays might lead to deterioration in their performances. Particularly, several synchronization problems of delayed complex networks and the corresponding control methods have been investigated during the past decades, such as cluster synchronization [3], passivity synchronization [4], pinning synchronization [5], finite time synchronization [6], etc..…”

Exponential Synchronization of Dynamical Network with Distributed Delays Via Intermittent Control

“…For any given dynamical network, the key point for designing intermittent controllers is to derive the synchronization conditions with respect to the control rate, control gains and system parameters. Recently, many valuable results about intermittent control are obtained [17][18][19][20][21][22][23][24][25][26][27][28][29][30]. In Refs.…”

“…Further, in Refs. [23][24][25][26][27][28][29][30], synchronization of dynamical networks with delay (including constant and time-varying delays) is investigated via intermittent control. Particularly, in Refs.…”

A graph‐theoretic method to stabilize the delayed coupled systems on networks based on periodically intermittent control

“…Hence, it is critical to stabilize the delayed coupled systems on networks (DCSNs). More and more attention has been paid to the investigation of the stabilization control problem of DCSNs since it plays significant roles in many potential applications such as physiological states, for instance, Feng et al 13 successfully investigated the cluster synchronization of nonlinearly time-varying delayed coupling complex networks based on periodically intermittent pinning control; Wu et al 15 considered the exponential stabilization of delayed memristor-based neural networks via continuous linear state feedback control; Zeng et al 16 studied the exponential stabilization of memristive neural networks with time delays by optimal control. Other control methods have also been introduced to stabilize the delayed systems, such as intermittent control, 17 impulsive control, 18 sampled-data control, 19 and compound control strategy.…”