Flocking control of multiple agents in noisy environments

Birds, bees, and fish often flock together in groups to find the source of food (target) based on local information. Inspired by this natural phenomenon, a flocking control algorithm is designed to coordinate the activities of multiple agents in noisy environments. Based on this algorithm, all agents can form a network and maintain connectivity. This is of great advantage for agents to exchange information. In addition, collision avoidance among agents is guaranteed in the whole process of target tracking. We show that even with noisy measurements the flocks can achieve cohesion and follow the moving target. We also investigate the stability and scalability of our algorithm. The numerical simulations are performed to demonstrate the effectiveness of the proposed algorithm.