Distributed adaptive output feedback consensus tracking for multi-agent systems with unknown nonlinearities

This paper considers the distributed consensus tracking problem for multi-agent systems with unknown nonlinearities in the followers. Based on parameterizing the nonlinearities of all followers, distributed adaptive consensus protocols with dynamic coupling gains are designed with the relative output information which are more practical than the state-feedback ones. The protocols guarantee that the consensus tracking errors converge to a small neighborhood around the origin and all the signals in the closed-loop dynamics are uniformly ultimately bounded. The dynamic coupling gains are updated without knowing the eigenvalues of the Laplacian matrix which is actually the global information. Finally, the theoretical results are illustrated through an example.