基于鞍点法的自适应分布式资源分配算法
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作者单位:

1.中国矿业大学信息与控制工程学院;2.东北大学流程工业综合自动化国家重点实验室

作者简介:

通讯作者:

中图分类号:

TP13

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)江苏省自然科学基金


An adaptive distributed resource allocation algorithm via saddle point dynamics
Author:
Affiliation:

School of Information and Control Engineering, China University of Mining and Technology

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan), Natural Science Foundation of Jiangsu Province

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    摘要:

    本文研究一类带有不等式约束为凸函数的多智能体系统分布式资源分配问题. 在资源分配问题中,各智能体拥有仅自身可知的局部成本函数和局部凸不等式约束. 分布式资源分配旨在如何利用智能体间的信息交互设计一种分布式优化算法, 完成定量资源分配的同时还保证最小化全局成本函数. 针对该问题, 基于卡罗需- 库恩-塔克条件和比例积分控制思想, 本文首先提出一种自适应分布式优化算法. 其中凸不等式约束的对偶变量可实现自适应获取. 其次, 为了降低系统的通信资源消耗, 本文设计一种动态事件触发控制策略实现了离散时间通信的分布式资源分配算法. 最后, 通过数值仿真验证了本文所设计算法的有效性.

    Abstract:

    This paper studies the distributed resource allocation problem with convex inequality constraints over the multi-agent systems. The local cost function and convex inequality constraints are known by themselves of each agent in the resource allocation problem. The aim of the distributed resource allocation problem is how to design a distributed optimization algorithm by using the information exchange between neighboring agents while minimizing the global cost functions. For this problem, based on the Karush-Kuhn-Tucker condition and proportional integral control idea, we first provide an adaptive distributed optimization algorithm, in which the dual variable of the inequality is obtained adaptively. Second, to reduce the communication resource consumption of the system, the discrete-time communication of the distributed resource allocation algorithm is realized by designing a dynamic event-triggered control scheme in this paper. Finally, we show that the effectiveness of our proposed algorithms by the numerical simulation.

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历史
  • 收稿日期:2021-11-21
  • 最后修改日期:2022-03-22
  • 录用日期:2022-03-28
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