The issue of time cost for the Kuramoto-oscillator network synchronization has received widespread attention. However, there is no relevant research on the stochastic synchronization of the Kuramoto-oscillator network with partial uncontrollable oscillators. This article investigates the synchronization problem of the Kuramoto-oscillator network in noisy environments using the pinning control strategy and multilayer distributed control. Previous research requires control of all oscillators, which implies a great control cost. To reduce the control cost, the finite/fixed time pinning controllers are designed to provide the conditions for synchronization in noisy environments, and then the upper bounds on the convergence time of the network are estimated. Finally, numerical simulations are performed to justify the theoretical conclusions.

In the research on complex networks, synchronizability is a significant measurement of network nature. Several research studies center around the synchronizability of single-layer complex networks and few studies on the synchronizability of multi-layer networks. Firstly, this paper calculates the Laplacian spectrum of multi-layer dual-center coupled star networks and multi-layer dual-center coupled star–ring networks according to the master stability function (MSF) and obtains important indicators reflecting the synchronizability of the above two network structures. Secondly, it discusses the relationships among synchronizability and various parameters, and numerical simulations are given to illustrate the effectiveness of the theoretical results. Finally, it is found that the two sorts of networks studied in this paper are of the same synchronizability, and compared with that of a single-center network structure, the synchronizability of two dual-center structures is relatively weaker.

In this paper, a class of fractional deterministic and stochastic susceptible-infected-removed- susceptible (SIRS) epidemic models with vaccination is proposed. For the fractional deterministic SIRS epidemic model, the existence of solution and the stability of equilibrium points are analyzed by using dynamic method. Then, the appropriate controls are established to effectively control the disease and eliminate it. On this basis, the fractional stochastic SIRS epidemic model with vaccination is further considered, and a numerical approximation method is proposed. The correctness of the conclusion is verified by numerical simulation.