A self-adaptive control algorithm of the artificial fish formation

With the deep study of swarm intelligence, biologists found that fish swarm changes in formation gradually in time during their movement. This formation change leads to a better and more effective access to evade predator and opportunity to capture food, so that the group´s overall performance is improved. The architecture of artificial fish formation is established based on the behavioral model of artificial fish swarm. The mechanism of formation change is analyzed. A self-adaptive control algorithm of formation is proposed in this paper. The parameters optimized PSO algorithm is used to simulate the process of keeping its balance during the formation change. Thus, the problem on relative bad adaptability and large systematic traffic in existing algorithms of formation is resolved.