Leader-Following Consensus for a Class of Nonlinear Strick-Feedback Multiagent Systems With State Time-Delays

Abstract

This paper studies the leader-following consensus problem for a class of strict-feedback multiagent systems with unknown nonlinearities and state time-delays under directed topology. By using the backstepping technique, an adaptive consensus control protocol is proposed, where neural networks are employed to neutralize uncertain nonlinearities. To eliminate the effects of time-delays, Lyapunov–Krasovskii functionals, and Young’s inequalities are used in the design process. It is notable that the computation burden is dramatically alleviated by proposing a novel adaptive mechanism. For communication topology containing a spanning tree, the proposed controller guarantees that the consensus tracking error will converge to an adjustable neighborhood of the origin. Finally, a numerical example is provided to validate the effectiveness of our result.