Successive lag synchronization on nonlinear dynamical networks via linear feedback control

Nonlinear Dynamics - Successive lag synchronization (SLS) is defined as a new synchronization pattern, which means that lag synchronization appears between two successively numbered nodes in a...     

On pinning control of some typical discrete-time dynamical networks

Recently, the pinning control of complex dynamical networks to their homogeneous states has been studied by many researchers, most of the dynamical networks are continuous-time ones, i.e., their dynamical behavior can be described by ODEs. An interesting result is that, for a continuous-time network, its desired (homogeneous) state can be achieved by pinning some nodes with relatively large degrees (also called the specifically pinning scheme [Wang XF, Chen GR. Pinning control of scale-free dynamical networks. Physica A 2002;310:521–31]). Is this specifically pinning scheme also effective for the discrete-time dynamical networks? In this paper, we demonstrate that the pinning control for a discrete-time dynamical network is difficult, and sometimes it is impossible to achieve the desired state just by controlling the nodes with larger degrees. In order to control the discrete-time dynamical networks successfully, we may need to control all the nodes. Finally, we also consider how to extend the interval for the feedback gain d for successful control.     

Adaptive mechanism between dynamical synchronization and epidemic behavior on complex networks

Many realistic epidemic networks display statistically synchronous behavior which we will refer to as epidemic synchronization. However, to the best of our knowledge, there has been no theoretical study of epidemic synchronization. In fact, in many cases, synchronization and epidemic behavior can arise simultaneously and interplay adaptively. In this paper, we first construct mathematical models of epidemic synchronization, based on traditional dynamical models on complex networks, by applying the adaptive mechanisms observed in real networks. Then, we study the relationship between the epidemic rate and synchronization stability of these models and, in particular, obtain the conditions of local and global stability for epidemic synchronization. Finally, we perform numerical analysis to verify our theoretical results. This work is the first to draw a theoretical bridge between epidemic transmission and synchronization dynamics and will be beneficial to the study of control and the analysis of the epidemics on complex networks.     

Effect of the coupling matrix with a weight parameter on synchronization pattern in a globally coupled network

In this paper, effect of the coupling matrix with a weight parameter on synchronization pattern in a globally coupled network is investigated. On the basis of matrix theory, the threshold values of the coupling strength and the weight parameter for cluster synchronization have been obtained by utilizing the attractiveness criteria of the invariant synchronization manifold. It shows that cluster synchronization bifurcation comes forth, which concept is first put forward. That is to say, via changing the weight parameter and the coupling strength, the purpose of controlling the number of clusters is achieved, which provides a new idea for control the number of clusters in a network. Numerical simulations are given to demonstrate the theoretical results. In addition, the theoretical results and the numerical simulations also show that full synchronization may not be realized even if the network is globally coupled when there are some negative couplings.     

带Bergman度量的有界典型域上Laplace-Beltrami算子谱的下界

本文估计了带K?hler度量的有界典型域上Laplace-Beltrami算子谱的下界,给出了带K?hler度量的第二类有界典型域上Laplace-Beltrami算子谱的下界的范围.特别地,对于秩为1的区域,本文给出的结论与已有结论相一致.     

Dynamical analysis and control strategies of an SIVS epidemic model with imperfect vaccination on scale-free networks

Nonlinear Dynamics - Vaccination is an effective method to prevent the spread of infectious diseases. In this paper, we develop an SIVS epidemic model with degree-related transmission rates and...     

Adaptive cluster synchronization in networks with time-varying and distributed coupling delays

This paper studies the adaptive cluster synchronization of a generalized linearly coupled network with time-varying delay and distributed delays. This network includes nonidentical nodes displaying different local dynamical behaviors, while for each cluster of that network the internal dynamics is uniform (such as chaotic, periodic, or stable behavior). In particular, the generalized coupling matrix of this network can be asymmetric and weighted. Two different adaptive laws of time-varying coupling strength and a linear feedback control are designed to achieve the cluster synchronization of this network. Some sufficient conditions to ensure the cluster synchronization are obtained by using the invariant principle of functional differential equations and linear matrix inequality (LMI). Numerical simulations verify the efficiency of our proposed adaptive control method.     

Optimal control and optimization algorithm of nonlinear impulsive delay system producing 1,3-Propanediol

According to the controllability of pulse times and the amount of jumps in the states at these times in the process of fed-batch culture producing 1,3-propanediol, this paper proposes a terminal optimal control model, whose constraint condition is the nonlinear impulsive delay system. The existence of optimal control is discussed and an optimization algorithm which is applied to each subinternal over one cycle for this optimal control problem is constructed. Finally, the numerical simulations show that the terminal intensity of producing 1,3-propanediol has been increased obviously.     

Successive lag synchronization on nonlinear dynamical networks via aperiodically intermittent control

Nonlinear Dynamics - Successive lag synchronization (SLS) for nonlinear dynamical networks is investigated by using aperiodically intermittent control. Different from previous works about the SLS,...     

Epidemic outbreaks on networks with effective contacts

In real-world networks of disease transmission, the incidence of infection among individuals conforms to a certain fixed probability of effective contact between them, which must meet some necessary conditions for the disease to continue to spread. Based on susceptible/infective/removed (SIR) models in homogeneous or heterogeneous networks, we find that these models evolve dynamically just like in networks without connectivity fluctuations if all the susceptible individuals are supposed to have the same effective contact. This means that effectively heterogeneous contacts play a striking role in epidemic dynamics. To go a step further, we introduce the effective contact function (ECF) into models and present an analytical and numerical study for the threshold and dynamical behaviors of epidemic incidence. The power-law and proportional ECFs are considered, and, we demonstrate analytically that the epidemic incidence is generally a monotone decreasing function of the epidemic threshold and increasing function of the number of effective contacts. Certain exceptional cases are also discussed. This tells us that we cannot always focus on the threshold to evaluate the extent of epidemic outbreaks.