Fully Distributed Consensus Tracking of Multiagent Systems With a High-Dimensional Leader and Directed Communication Topology

We study the asymptotic consensus tracking problem for multiagent systems (MASs) with uncertain dynamics under directed communication topology, where the leader has higher dimensional dynamics than followers. In our approach, the uncertainties are approximated by a neural network with arbitrary accuracy in compact regions. To remove the effects of leader's high dimensional dynamics on consensus, a compensation controller with adaptive coupling strengths is designed. Moreover, to eliminate the effects of uncertain dynamics and external disturbances on consensus, a discontinuous feedback controller with neuro-adaptive law is given. Furthermore, we show fully distributed asymptotic consensus tracking of the considered MAS under the designed compensator plus the feedback controller can be achieved if the communication topology contains a directed spanning tree with the leader being the root. In addition, a theorem is given under the undirected topology. Finally, we perform a simulation to validate the theoretical result.