Distributed adaptive consensus tracking control for non-linear multi-agent systems with time-varying delays

In this study, a novel distributed adaptive controller is provided for consensus control of high-order non-linear multi-agent systems with unknown time-varying delays. The system is subject to uncertain disturbances, and the agents' dynamics are not known. Unlike the existing literature, the proposed method does not require time-delay terms in system dynamics to be bounded. A neural network is used to model the unknown non-linear dynamics. Then, despite the destabilising effect of the unknown delays, some adaptive rules based on the dynamic surface control are designed to achieve the consensus objective. The semi-global uniform boundedness of the resultant closed-loop signals and the convergence of the tracking errors to a neighbourhood of the origin are shown mathematically. Simulations verify the effectiveness of the results.