Distributed control of uncertain nonlinear multi-agent systems in non-affine pure-feedback form using DSC technique

This paper discusses the output consensus problem of tracking a desired trajectory for a class of nonlinear multi-agent systems in non-affine pure-feedback form. An adaptive distributed control scheme is designed recursively by employing back-stepping method, dynamic surface control (DSC) technique, neutral networks (NNs) and graph theory. The precise knowledge of the uncertainties of the system is not required and the computational burden is reduced by the DSC approach. Also, norms of the unknown neural weight vectors are estimated instead of unknown neural weight vectors themselves. It can be proved that the proposed control strategy can force the output of agents in an undirected topology to track the desired trajectory and guarantee all signals in the closed-loop system uniformly ultimately bounded.