中图分类号： TP273
文献标识码： A
DOI： 10.19358/j.issn.2096-5133.2020.06.014
引用格式： 吴慕兰. 基于障碍Lyapunov函数的多智能体系统误差约束同步[J].信息技术与网络安全，2020，39(6)：73-79.

Synchronization of multi-agent systems with error constraints based on barrier Lyapunov function

Abstract： Synchronization of multi-agent systems with error constraints requires that the states of agents synchronize, meanwhile the synchronization error is required to be confined by a predefined bound. This paper proposes a distributed neuro-adaptive control for synchronization of the leader-follower multi-agent systems with error constraints, where both the leader and the followers are governed by unknown nonlinear dynamics. To solve the problem of synchronization error constraints, neural networks are employed to approximate the unknown nonlinearities of the system dynamics, and a novel distributed barrier Lyapunov function (DBLF) is developed to confine the synchronization errors. Then distributed neuro-adaptive control protocols are derived based on the Lyapunov stability analysis, in which the Lyapunov function is defined in terms of the proposed DBLF. A simulation example is finally provided to verify that the synchronization error constraints can be realized by employing the proposed control protocols.

Key words : multi-agent systems；synchronization error constraints；adaptive control；neural network；barrier Lyapunov function