Exponential consensus of non‐linear stochastic multi‐agent systems with ROUs and RONs via impulsive pinning control

Stochastic synchronization of delayed multiagent networks with intermittent communications: An impulsive framework

“…implies that x i (t) is left continuous at t = t k , e i (t) = x i (t) − x 0 (t) is the tracking error vector, (t) = [ 1 (t), … , n (t)] T ∈ R n is the Brownian motion defined on (Ω,  ,  t≥0 , ), and i ∶ R + × R n × R n → R n×n is the diffusion coefficient matrix and satisfies the following Assumption 2. The stochastic background and terminology can refer to related works [46][47][48] and the references therein. Assumption 2. i (t, e i (t), e i (t − (t))) is locally Lipschitz continuous and satisfies the linear growth condition, i (t, 0, 0) = 0 n .…”

“…Therefore, it is reasonable to consider the effects of stochastic disturbances during the process of information transmission of multiagent networks linked by communication graphs. 47,48 The common requirement in most existing literatures on the synchronization or consensus for multiagent networks is that the communication topology needs to be fixed or static, and the information is transmitted continuously among multiagents. However, this is not always the case in reality due to technological limitations of sensors or external disturbances.…”

Finite-Time Stability and Stabilization of Impulsive Stochastic Delayed Neural Networks With Rous and Rons

“…Furthermore, in real life, there exist many stochastic disturbances in physical systems and mechanical equipment, for instance, noise disturbances, randomly occurring uncertainties (ROUs) and randomly occurring nonlinearities (RONs) [26]. NNs, of course, are often subject to kinds of stochastic disturbances.…”

“…Therefore, it is of great importance to research on the stochastic models of NNs. And in the meantime, most of the scholars are fascinated by the stochastic neural networks (SNNs) [26]- [31]. In [26], authors proposed the impulsive pinning control to investigate the exponential consensus of stochastic multi-agent systems with ROUs and RONs by means of the Lyapunov function and the Halanay differential inequality.…”

“…And in the meantime, most of the scholars are fascinated by the stochastic neural networks (SNNs) [26]- [31]. In [26], authors proposed the impulsive pinning control to investigate the exponential consensus of stochastic multi-agent systems with ROUs and RONs by means of the Lyapunov function and the Halanay differential inequality. In [31], by using the Razumikhin techniques, authors studied the robust exponential stability of impulsive SNNs with delayed impulses.…”