二阶多智能体系统的分布式最优资源分配

H. Tian, Nanxiang Yu, Wei Zhu
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引用次数: 0

摘要

研究了全局网络资源约束下二阶多智能体系统的资源分配问题。提出了一种仅利用局部信息的分布式连续时间算法。利用矩阵变换和微分不等式技术,得到了无向连通图下的指数收敛性。为了降低能耗和通信成本,设计了一种分布式事件触发算法。证明了该算法不仅指数收敛于最优分配,而且事件触发时间序列不表现出芝诺行为。最后,通过数值算例验证了理论结果的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed optimal resource allocation with second‐order multi‐Agent systems
This paper studies the resource allocation problems with second‐order multi‐agent systems under the constraint of the global network resource. A novel distributed continuous‐time algorithm, which only uses the local information, is proposed. By using matrix transform and differential inequality technique, the exponential convergence is obtained under the undirected and connected graph. To reduce energy consumption and communication costs, a distributed event‐triggered algorithm is designed. It is proved that not only this algorithm converges exponentially to the optimal allocation, but also the event‐triggered time sequence does not exhibit Zeno‐behavior. Finally, numerical examples illustrate the effectiveness of theoretical results.
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