Topology identification of an uncertain general complex dynamical network

Abstract

In real-world complex networks, there exists many uncertain information, such as uncertain topological structures and uncertain system parameters. Without question, the topology identification and parameter identification are two traditionally challenging questions in complex networks. Based on the adaptive observers, our approach can identify the topological structures and system parameters of the uncertain complex dynamical networks together. In particular, our method is also very effective for the complex networks with different node dynamics. Moreover, the proposed approach can be used to monitor the online evolution of network topological structures and system parameters. Finally, several typical simulations are used to verify the effectiveness of the proposed approach.