In nature, a fascinating phenomenon has usually been observed that a flock of birds, a school of fish and a colony of insects etc. form a regular, ordered collection to move. These systems consist of plenty of individuals is called Multi-Agent System, MAS for short. The coordination of MAS has become a hot topic in research recently.In this paper, we focus on the problems of the coordination condition of Multi-Agent Systems, the flocking control of Multi-Agent Systems and the formation control of Multi-Robot Systems. First, we simulate the Vicsek model with the constraint of position dependence. The results show that the connected condition of information topology is not the only constraint of model synchronization, which is the numerical foundation of future work. Second, for Multi-Agent Systems with first integrator model, using the model of neural networks and pinning control of complex networks, we design the basic flocking controller, flocking controller with constraint of actuator saturation and flocking controller with time-delayed information topology. Moreover, through theoretical proof and numerical simulation, the effectiveness of controllers is validated. Finally, for Multi-Robot Systems with double integrator model, using artificial potential field and virtual leader theory, we present two kinds of controller, one of which can meet the constraint of actuator saturation, the other of which can guarantee the desired distance and angle between two robots at the same time, and verify the controllers with theories and simulations.The research in this paper gives the numerical proof of convergence of Multi-Agent Systems. We relate the stability of neural network and pinning control of complex network to the flocking control of Multi-Agent Systems for the first time, and also improve the previous functions of artificial potential field for the formation of Multi-Robot Systems. All the work in paper has some value in theory and engineering. |