Adaptive leader-following consensus of nonlinear multi-agent systems with jointly connected topology

This paper studies the leader-following consensus problem of general multi-agent systems, in which dynamics of all agents are affected by unknown nonlinear dynamics. By parameterizing the unknown nonlinear terms, a distributed adaptive consensus algorithm is proposed for each follower agent. With a modified labeling rule, consensus analysis is conducted for the multi-agent systems with jointly connected topology based on algebraic graph theory and Lyapunov theory. Finally, a simulation example is provided to validate the theoretical results.