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具有事件触发机制的非线性多智能体系统针对通信故障和死区输入的自适应分布式控制

Adaptive Distributed Control of Nonlinear Multiagent Systems With Event-Triggered for Communication Faults and Dead-Zone Inputs.

作者信息

Sun Jiayue, Xu Zhiming, Zhang Huaguang, Chai Tianyou, Wang Shiyang

出版信息

IEEE Trans Cybern. 2024 Oct;54(10):5877-5886. doi: 10.1109/TCYB.2024.3440356. Epub 2024 Oct 9.

DOI:10.1109/TCYB.2024.3440356
PMID:39159033
Abstract

This article studies the containment control problem of nonlinear multiagent systems (MASs) subjected to communication link faults and dead-zone inputs. In case of an unknown fault in the communication link, there is no constant Laplacian matrix anymore and each follower agent cannot be informed of the global information simultaneously. To deal with this problem, an adaptive compensating estimator is constructed to estimate the signal spanned by the leaders. Instead of using the linear filter, a nonlinear filter is employed, which both solves the classical complexity explosion in the traditional backstepping method and flushes out the usefulness of the boundary layer error. Considering the dead zone input, we propose two event-triggered schemes, that is, the update-triggered scheme and the transmit-triggered scheme. In the former, the threshold function involves the tracking errors and additional dynamic variable, which can provide the desirable tradeoff between the containment control performance of the considered MASs and saving communication resources. In the latter, the triggered condition is designed according to the characteristic of dead zone, which makes the communication burden be reduced further. Following the backstepping design framework, an adaptive containment control is constructed, it is shown that the containment error can converge to an adjustable residual set even if MASs are subjected to the unknown and bounded communication link faults and dead-zone inputs. Finally, an example is given to show the effectiveness of the proposed results.

摘要

本文研究了存在通信链路故障和死区输入的非线性多智能体系统(MASs)的包容控制问题。在通信链路出现未知故障的情况下,不再存在常数拉普拉斯矩阵,并且每个跟随智能体无法同时获取全局信息。为解决该问题,构造了一种自适应补偿估计器来估计领导者所生成的信号。采用了非线性滤波器而非线性滤波器,这既解决了传统反步法中经典的复杂度爆炸问题,又消除了边界层误差的影响。考虑到死区输入,我们提出了两种事件触发方案,即更新触发方案和传输触发方案。在前者中,阈值函数涉及跟踪误差和附加动态变量,这可以在所考虑的MASs的包容控制性能和节省通信资源之间提供理想的权衡。在后者中,根据死区特性设计触发条件,这进一步减轻了通信负担。遵循反步设计框架,构造了一种自适应包容控制,结果表明,即使MASs受到未知且有界的通信链路故障和死区输入的影响,包容误差也能收敛到一个可调节的残差集。最后,给出一个例子以说明所提结果的有效性。

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