Dynamic Analysis Of Uncertain Complex Networks

Both fields of control and synchronization and complex network studies are international hotspots. In this thesis, we did some deep and detailed studies on control and synchronization of uncertain complex networks which are is an important research subjects in the above field. We put forward and discussed several new methods for control and synchronization in several uncertain complex networks.The main contributions of this thesis are as follows:Firstly, we consider the problem of control in uncertain generic complex networks. For generic complex networks with unknown dynamics of nodes and unknown coupling functions including uniform and nonuniform inner couplings, some simple linear feedback controllers with updated strengths are designed using the well-known LaSalle invariance principle. The state of an uncertain generic complex network can be controlled to an arbitrary assigned state of an isolated node of the network. To confirm the result ,the famous Lorenz system is stimulated as the nodes of the complex networks.Secondly, a class of uncertain time-varying complex dynamical networks is studied in this thesis. On the grounds of that model then the locally and globally decentralized synchronization of these networks are thoroughly investigated. Several network synchronization criteria are deduced. Especially, the assumptions adopted and decentralized control laws designed are considerably simple. An illustrative example along with the respective numerical and computer simulation results is also given to demonstrate the effectiveness of the proposed synchronization control synthesis.At last, we study adaptive–impulsive synchronization of uncertain complex dynamical networks. Based on the stability analysis of impulsive system, several network synchronization criteria for local and global adaptive–impulsive synchronization are established. Numerical example is also given to illustrate the results.