Publications

This paper is concerned with synchronization control of a multiplex network, in which two different kinds of relationships among agents coexist. Hybrid coupling, including continuous linear coupling and impulsive coupling, is proposed to model the coexisting distinguishable interactions. First, by adding impulsive controllers on a small portion of agents, local synchronization is analyzed by linearizing the error system at the desired trajectory. Then, global synchronization is studied based on the Lyapunov stability theory, where a time-varying coupling strength is involved. To further deal with the time-varying coupling strength, an adaptive updating law is introduced and a corresponding sufficient condition is obtained to ensure synchronization of the multiplex network towards the desired trajectory. Networks of Chua's circuits and other chaotic systems with double layers of interactions are simulated to verify the proposed method.

Social networks are complex in their forming and growing processes. Tremendous empirical evidence in undirected social networks, such as Facebook, Quora and Foursquare, demonstrates that, to a large extent, individuals are associated with each other not by preference but through other organizing rules. One such rule found in many real social networks is the Henneberg growth mechanism, with which a triangle will be formed whenever an individual joins a community. Inspired by this mechanism, a novel social network model, named Henneberg growth model, is proposed in this paper. Some topological and dynamical properties of the model in common interest are analyzed. Experimental results show that the function and structure of the model are in remarkable agreement with two huge-scale Facebook network datasets. The finding suggests that the Henneberg growth mechanism is indeed fundamental for modeling some undirected social networks like the Facebook.

The conventional LoRa system is not able to sustain long-range communication over fading channels. To resolve the challenging issue, this paper investigates a two-hop opportunistic amplify-and-forward relaying LoRa system. Based on the best relay-selection protocol, the analytical and asymptotic bit error rate (BER), achievable diversity order, coverage probability, and throughput of the proposed system are derived over the Nakagamim fading channel. Simulative and numerical results show that although the proposed system reduces the throughput compared to the conventional LoRa system, it can significantly improve BER and coverage probability. Hence, the proposed system can be considered as a promising platform for low-power, long-range and highly reliable wireless-communication applications.

The issue of opinion sharing and formation has received considerable attention in the academic literature, and a few models have been proposed to study this problem. However, existing models are limited to the interactions among nearest neighbors, ignoring those second, third, and higher-order neighbors, despite the fact that higher-order interactions occur frequently in real social networks. In this paper, we develop a new model for opinion dynamics by incorporating long-range interactions based on higher-order random walks. We prove that the model converges to a fixed opinion vector, which may differ greatly from those models without higher-order interactions. Since direct computation of the equilibrium opinions is computationally expensive, which involves the operations of huge-scale matrix multiplication and inversion, we design a theoretically convergence-guaranteed estimation algorithm that approximates the equilibrium opinion vector nearly linearly in both space and time with respect to the number of edges in the graph. We conduct extensive experiments on various social networks, demonstrating that the new algorithm is both highly efficient and effective.

Traditional network analysis focuses on the representation of complex systems with only pairwise interactions between nodes. However, the higher-order structure, which is beyond pairwise interactions, has a great influence on both network dynamics and function. Ranking cliques could help understand more emergent dynamical phenomena in large-scale complex networks with higher-order structures, regarding important issues, such as behavioral synchronization, dynamical evolution, and epidemic spreading. In this paper, motivated by multi-node interactions in a topological simplex, several higher-order centralities are proposed, namely, higher-order cycle (HOC) ratio, higher-order degree, higher-order H-index, and higher-order PageRank (HOP), to quantify and rank the importance of cliques. Experiments on both synthetic and real-world networks support that, compared with other traditional network metrics, the proposed higher-order centralities effectively reduce the dimension of a large-scale network and are more accurate in finding a set of vital nodes. Moreover, since the critical cliques ranked by the HOP and the HOC are scattered over a complex network, the HOP and the HOC outperform other metrics in ranking cliques that are vital in maintaining the network connectivity, thereby facilitating network dynamical synchronization and virus spread control in applications.

In this study, the problem of stochastic consensus in multi-agent systems of non-linear dynamical agents with state-dependent noise perturbations and repairable actuator failures is investigated. By appropriately constructing a Lyapunov function and using tools from the stochastic differential equations theory, it is proved that mean-square consensus in the closed-loop multi-agent systems with a fixed strongly connected topology can be achieved exponentially if the coupling strength of relative states among neighbouring agents is larger than a threshold value depending on the actuator failure rate. The convergence rate is also analytically given. The results are then extended to the more general case where the communication topology only contains a directed spanning tree. Numerical simulations are finally provided to illustrate the effectiveness of the theoretical analysis.

In this paper, an optimal hybrid tracking control problem for continuous neutral time-delay systems is formulated and studied. An optimal linear integral quadratic cost function that has a high-gain property is used for tracking control specification. Two interpolation methods are applied to directly convert the original analog neutral time-delay system into an equivalent digital retarded time-delay system, and meanwhile convert the continuous-time quadratic cost function into a discretized form. Then, an extended state vector is constructed for an associate extended discrete-time optimal control problem without time delay. Using the standard discrete-time linear-quadratic optimal control theory and an indirect digital redesign technique with a predictive feature, an effective digital tracker is designed for the original analog neutral time-delay system. An example is finally given for illustrating the effectiveness of the new tracker design method.

A total of 606 co-occurrence networks of Chinese characters and words are constructed from rhymes, free verses, and prose poems. It is found that 98.5 % of networks have scale-free properties, while 19.8 % of networks do not have small-world features, especially the clustering coefficients in 5.6 % of networks are zero. In addition, 61.4 % of networks have significant hierarchical structures, and 98 % of networks are disassortative. For the above observed phenomena, analysis is provided with interpretation from a linguistic perspective.

No abstract is provided for this article.

Differing from the existing literature on node consensus, this brief studies consensus taking place on the edges of networked dynamical systems. A distributed edge quasi-consensus protocol is developed to lead the states of all edges to converge into a bounded region. For a connected network with nonnegative initial edge states, it is proved that the edge quasi-consensus can be reached while the states of all edges can be kept nonnegative. Moreover, the nonnegative edge quasi-consensus of networked systems with edge state constraints or input saturation is analyzed, respectively. Numerical simulations are provided to verify the effectiveness of the protocols.

Summary In this paper, the distributed H ∞ robust control problem synthesized with transient performance is investigated for a group of autonomous agents governed by uncertain general linear node dynamics. Based on the relative information between neighboring agents and some information of other agents, distributed state‐feedback and observer‐type output‐feedback control protocols are designed and analyzed, respectively. By using tools from robust control theory, conditions for the existence of controllers for solving such a problem are established. It is shown that the problem of distributed H ∞ robust control synthesized with transient performance can be converted to the H ∞ control problem synthesized with transient performance for decoupled linear systems of the same low dimensions. Finally, simulation examples are provided to illustrate the effectiveness of the design. Copyright © 2014 John Wiley & Sons, Ltd.