Research On Cooperative Control Of Complex Dynamic Network Systems Based On Swarm Intelligence

Recently, complex network has become an important interdisciplinary field, which attracts more and more researchers in physics, biology, mathematics, computer, etc, cooperative control of multi-agent system based on swarm-intelligence has become a hot topic in this area. In this paper, some research efforts are paid on the study on several problems in cooperative control of complex networks: movement of multi-agent system with leader and withoutleader is studied by using potential function approach. Then some control protocols based on algebraic graph theory and lyapunov stability theory are proposed to solve the finite-time reaching desired state of multi-agent system in complex entirvonment. Finally, movement of multi-agent system is studied by using kaermanfilter approach. Proper control and stability analysis and computer simulation are given in every research approach. The results have important theory significance and application value.The main innovative work and key points are listed as follows:(1) Movement of multi-agent system is studied by using potential function approach. The system are devided to two kinds: with leader and withoutleader. The movement object of system is to reach some desired or formation. In potential function, the attractive energy from desired situation or entirvonment to agents is used which has active to reach the object.(2) Finite-time cooperative control of multi-agent system is studied. some control protocols based on algebraic graph theory and lyapunov stability theory are proposed to solve the finite-time reaching desired state of multi-agent system. In the design of finite-time protocol, the communication time-delays are taken into account. The protocols can guarantee finite-time agreement of multi-agent system.(3) Finite-time cooperative control of multi-agent system is studied. Some obstacles are in the entirvonment. The movement object of system to. obstacle avoidance for multi-agent system and reach some desired formation is the main movement object. Through numerical simulations to show the effectiveness of the theoretical analysis results. (4) Movement of multi-agent system based on kaermanfilter approach is studied. The effect of entirvonment disturbance and sensor noise are taken into account. So kaermanfilter approach is used to predict the next situation of some agent to reduce the movement time.