Research On Flocking Control Of Complex Multi-agent Network

In recent years, with the development of computer technology and information processing technology, the cooperative control technology with the group as research object has made a rapid progress, and become one of the hotspots of scholars in various fields. Inspired by the large-scale clustering movement of the groups, flocking control research has attracted highly attention by numerous domestic and foreign researchers, and group cooperative control field become an important research direction by virtue of its good adaptability, robustness and self-organization. Taking into account the practical engineering application problems, how to achieve high efficiency of the global behavior with the control cost as little as possible, which has been an important research content in the field of flocking control.This dissertation mainly focuses on the pinning flocking control of complex multi-agent network based on the related knowledge of complex network, graph theory, control theory and the foundation of studying and summarizing the related research results. The main contents and contributions are as follows:1. The study of the flocking control problems on the hot topics in recent years is comprehensively summarized in this paper from three aspects which are the basic theory of related research contents, dynamic model of multi-agent network and control algorithm, which provide a solid theoretical foundation for subsequent research work.2. Considering the low flocking efficiency phenomenon for current multi-agent network, an effective pinning strategy is proposed to improve the control efficiency of multi-agent networks based on characteristics multiplicity of network of flocking control, and combining the graph theory and analytical of control theory method. The algorithm based on adjacency matrix of the multi-agent network topology structure and according to maximum multiplicity of its eigenvalue, the number of pinned nodes is obtained when the network controllable, then, using the control theory of PBH criterion to identify the specific pinned nodes and the pinning flocking control law is designed. With randomly select pinning strategy and the maximum degree pinning strategy, simulation results demonstrate that the proposed algorithm is effective in improving the control efficiency of the entire system.3. On the basic of deep research of flocking algorithm, the control efficiency directly affects the convergence speed of flocking control algorithm in multi-agent networks, and complex network topology has a great influence on the dynamic behavior characteristics of the network. With the community structure characteristics of complex network, a fast flocking algorithm of ER random network and BA scale free network based on community division algorithm is researched, which ensure the network connectivity and avoid the phenomenon of “block” or “local cohesion” in the dynamic evolution of flocking control. Combined with simulation experiment to study the influence of different initial topology distribution and the number of communities on the flocking convergence property, as well as the effect of average degree of ER and BA network and the heterogeneity of degree distribution of BA network on the convergence characteristic of complex network flocking control. In addition, the characteristics of flocking convergence slightly better which through the optimal modularity values of divided community number.