基于通用吸引律的多智能体系统的有限持续一致性

Mingxuan Sun, Xing Li
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引用次数: 1

摘要

本文研究了多智能体系统共识收敛速度的改进问题,为此我们引入了一个通用吸引定律(GAL),该定律包含三个术语,这些术语指定了改进收敛性能的通用动作。将传统的双功率率吸引定律进行了改进,增加了一个比例项,使系统的收敛速度得到了显著提高。通过两相分析,给出了沉降时间函数上界的估计,得到的上界取决于初始状态,且与初始状态值无关,上界是有限的。为了实现多智能体系统的一致性,采用了GAL。设计了一种非线性协议,使系统实现了有限时一致性,并给出了数值结果验证了该协议的有效性。
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Finite-Duration Consensus of Multi-Agent Systems Using a Generic Attracting Law
This paper is concerned with the convergence rate improvement of consensus of multi-agent systems, for which we introduce a generic attracting law (GAL), involving three terms which specify a generic action for improvement of convergence performance. The conventional double power-rate attracting law is modified for forming GAL, by adding a proportional term, and the convergence rate of the system can be dramatically improved. Through the two-phase analysis, an estimate for the upper bound of the settling time function is given, by which the obtained upper bound depends upon the initial state, and is finite without regard to the value of the initial state. The GAL is adopted for the purpose of consensus of multi-agent systems. A nonlinear protocol is designed to make the system undertaken achieve finite-duration consensus, and numerical results are presented to validate its effectiveness.
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