Leader-Following Consensus for a Class of Nonlinear Strick-Feedback Multiagent Systems With State Time-Delays
针对有向拓扑下具有未知非线性和状态时滞的严格反馈多智能体系统，提出一种基于反步法和神经网络的自适应一致性控制协议，有效减轻计算负担并保证跟踪误差收敛。
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.