Flocking of Multi-agent Systems with Unknown Nonlinear Dynamics and Heterogeneous Virtual Leader

This paper investigates the flocking control of multi-agent systems with unknown nonlinear dynamics while virtual leader information is heterogeneous. The uncertain nonlinearity in considered, and weaker constraint on velocity measurements assumed. In addition, a bounded assumption also considered. It than Lipschitz condition adopted most methods. To avoid fragmentation, we construct new potential function based penalty idea when initial network disconnected. A dynamical law including adjust parameter designed to achieve stable flocking. proven that velocities all agents approach consensus no collision happens between mobile agents. Finally, several simulations verify effectiveness design, indicate proposed method has high convergence broader applicability practical applications more stringent restrictions.