Dramatic advances in the eld of complex networks have been witnessed in the past few years. This paper reviews some important results in this direction of rapidly evolving research, with emphasis on the relationship between the dynamics and the topology of complex networks. Basic quantities and typical examples of various complex networks are described; and main network models are introduced, including regular, random, small-world and scale-free models. The robustness of connectivity and the epidemic dynamics in complex networks are also evaluated. To that end, synchronization in various dynamical networks are discussed according to their regular, small-world and scale-free connections.

In this paper, a systematic design approach based on time-delay feedback is developed for anticontrol of chaos in a continuous-time system. This anticontrol method can drive a finite-dimensional, continuous-time, autonomous system from nonchaotic to chaotic, and can also enhance the existing chaos of an originally chaotic system. Asymptotic analysis is used to establish an approximate relationship between a time-delay differential equation and a discrete map. Anticontrol of chaos is then accomplished based on this relationship and the differential-geometry control theory. Several examples are given to verify the effectiveness of the methodology and to illustrate the systematic design procedure.

A time-delay chaotification approach can be applied to the Chua's circuit by adding a small-amplitude time-delay feedback voltage to the circuit. The chaotic dynamics of this newly derived time-delay Chua's circuit is studied by theoretical analysis, verified by computer simulations as well as by circuit experiments.

Recently, it has been demonstrated that many large complex networks display a scale-free feature, that is, their connectivity distributions are in the power-law form. In this paper, we investigate the synchronization phenomenon in scale-free dynamical networks.We show that if the coupling strength of a scale-free dynamical network is greater than a positive threshold, then the network will synchronize no matter how large it is. We show that the synchronizability of a scale-free dynamical network is robust against random removal of nodes, but is fragile to specific removal of the most highly connected nodes.

A time-delay feedback control approach is developed for making a continuous-time minimum-phase system chaotic. The approach is based on the geometric control theory and a suitable approximate relationship between a time-delay differential equation and a discrete map. If the original system has an exponentially stable equilibrium point, then a simple time-delay output-feedback controller with arbitrarily small amplitude can drive the system chaotic. Two different types of simulation examples are included for demonstration.

It is now known that the complexity of network topology has a great impact on the stabilization of complex dynamical networks. In this work, we study the control of random networks and scale-free networks. Conditions are investigated for globally or locally stabilizing such networks. Our strategy is to apply local feedback control to a small fraction of network nodes. We propose the concept of virtual control for microscopic dynamics throughout the process with different pinning schemes for both random networks and scale-free networks.We explain the main reason why significantly less local controllers are required by specifically pinning the most highly connected nodes in a scale-free network than those required by the randomly pinning scheme, and why there is no significant difference between specifically and randomly pinning schemes for controlling random dynamical networks. We also study the synchronization phenomenon of controlled dynamical networks in the stabilization process, both analytically and numerically.

This brief proposes a unified approach for generating chaos in -dimensional continuous-time affine systems, with 3, based on the normal form of chaotic systems and nonlinear control theory. A feedback-control law is designed to make a feedback linearizable system topologically conjugate to a reference chaotic system, thereby forcing the given system to become chaotic. Furthermore, if the relative degree of a given feedback unlinearizable system is not less than three and the corresponding internal dynamics of the system is input-to-state stable, then a feedback-control law can still be designed to drive a subsystem of such a controlled system topologically conjugate to a reference chaotic system, thereby generating chaos from that subsystem.

In this paper, the problem of making a stable nonlinear autonomous system chaotic or enhancing the existing chaos of an originally chaotic system by using a small-amplitude feedback controller is studied. The designed controller is a linear feedback controller composed with a nonlinear modulo or sawtooth function, which can lead to uniformly bounded state vectors of the controlled system with positive Lyapunov exponents, thereby yielding chaotic dynamics. We mathematically prove that the controlled system is indeed chaotic in the sense of Li and Yorke. A few potential applications of the new chaoti cation algorithm are briefly discussed.

In the past few years, the discovery of small-world and scale-free properties of many natural and artificial complex networks has stimulated a great deal of interest in studying the underlying organizing principles of various complex networks, which has led to dramatic advances in this emerging and active field of research. The present article reviews some basic concepts, important progress, and significant results in the current studies of various complex networks, with emphasis on the relationship between the topology and the dynamics of such complex networks. Some fundamental properties and typical complex network models are described; and, as an example, epidemic dynamics are analyzed and discussed in some detail. Finally, the important issue of robustness versus fragility of dynamical synchronization in complex networks is introduced and discussed.

By combining the technique of observer design in nonlinear control systems theory and the technique of phase space reconstruction in nonlinear dynamical systems theory, we show that synchronization of smooth (hyper)chaotic systems can be attained with any scalar transmitted signal. The proposed method has been illustrated via two examples.