Group Consensus Control in Uncertain Networked Euler-Lagrange Systems Based on Neural Network Strategy

This paper investigates the group consensus problem for a network consisting of Euler-Lagrange systems under directed topology with acyclic partition via neural network strategy. The neural network based controller achieves group consensus for uncertain networked Euler-Lagrange systems. By exploiting thoroughly the specific structure of the network topology, the stable analysis of the group consensus problem for such uncertain networked systems is also provided. Furthermore, a necessary and sufficient condition for ensuring that the systems reach group consensus is established. Finally, examples and simulations are given to show the effectiveness of the presented theoretical results.