Leader-Following Consensus for a Class of Nonlinear State Time-delays Multiagent Systems

This paper focuses on the consensus tracking problem for a class of nonlinear multiagent systems with state time-delays and dead-zone input. Based on the backstepping technique, a consensus control protocol is proposed, where the nonlinear terms in the system are approximated with the radial basic function neural networks (RBFNNs). Combining the Lyapunov-Krasovskii functional and Young’s inequalities, the adverse effects of time-delays have been eliminated. At the same time, the nonlinear input problem is solved by converting the dead-zone to a combination of linear terms and bounded disturbance terms. The proposed control protocol guarantees that the convergence of the consensus error will converge to a limited neighborhood around the origin. Finally, the numerical results further illustrate the feasibility of the theoretical results.