This article presents the adaptive tracking control scheme of nonlinear multiagent systems under a directed graph and state constraints. In this article, the integral barrier Lyapunov functionals (iBLFs) are introduced to overcome the conservative limitation of the barrier Lyapunov function with error variables, relax the feasibility conditions, and simultaneously solve state constrained and coupling terms of the communication errors between agents. An adaptive distributed controller was designed based on iBLF and backstepping method, and iBLF was differentiated by means of the integral mean value theorem. At the same time, the properties of neural network are used to approximate the unknown terms, and the stability of the systems is proven by the Lyapunov stability theory. This scheme can not only ensure that the output of all the followers meets the output trajectory of the leader but also make the state variables not violate the constraint bounds, and all the closed-loop signals are bounded. Finally, the efficiency of the proposed controller is revealed.

中文翻译：

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使用积分障碍 Lyapunov 泛函的非线性多智能体系统的自适应神经一致性跟踪控制

本文提出了有向图和状态约束下非线性多智能体系统的自适应跟踪控制方案。本文引入积分势垒李雅普诺夫函数（iBLFs）来克服带误差变量的势垒李雅普诺夫函数的保守性限制，放宽可行性条件，同时求解智能体之间通信错误的状态约束项和耦合项。基于iBLF和反步法设计了自适应分布式控制器，并利用积分均值定理对iBLF进行微分。同时利用神经网络的性质来逼近未知项，并通过Lyapunov稳定性理论证明了系统的稳定性。该方案不仅可以保证所有跟随者的输出满足领导者的输出轨迹，而且可以使状态变量不违反约束界限，并且所有闭环信号都是有界的。最后，揭示了所提出的控制器的效率。