Decentralized adaptive consensus in multi-agent networks with jointly connected topologies

In this paper, the leader-following consensus problem of multi-agent is studied. An adaptive design method is presented for multi-agent systems with non-identical unknown nonlinear dynamics, and for a leader to be followed that is also nonlinear and unknown. By parameterizations of unknown nonlinear dynamics of all agents, a purely decentralized adaptive consensus algorithm is proposed in networks with jointly connected topologies by relative position feedback. Analysis of stability and parameter convergence of the proposed algorithm are conducted based on algebraic graph theory and Lyapunov theory. Finally, examples are given to validate the theoretical results.