Adaptive flocking with a virtual leader of multiple agents governed by nonlinear dynamics

We investigate the flocking problem of multiple nonlinear dynamical mobile agents with a virtual leader in a dynamic proximity network. We assume that only a fraction of agents in the network are informed and propose a connectivity-preserving flocking algorithm. Under the assumption that the initial network is connected, we introduce local adaptation strategies for both the weights on the velocity navigational feedback and the coupling strengths that enable all agents to track the virtual leader, without requiring the knowledge of the agent dynamics. The resulting flocking algorithm works even for the case where only one agent is informed.