具有连续数据包损失和随机采样数据的多代理系统的领先跟随采样数据共识
IEEE transactions on cybernetics
|October 3, 2024
概括
本研究涉及线性多代理系统 (MAS) 中的领先后续共识,其中包括随机抽样间隔和连续数据包损失 (SPL). 使用利亚普诺夫理论和矩阵重建方法来获得一种新的共识标准,以实现强大的控制.
科学领域:
- 控制理论 控制理论
- 系统工程 系统工程
- 网络化系统 网络化系统
背景情况:
- 在实际应用中,采样数据系统面临着不可预测的物理限制.
- 这些约束导致随机抽样间隔偏离预期值.
- 连续的数据包丢失 (SPLs) 进一步复杂化了系统动态.
研究的目的:
- 为解决线性多代理系统 (MAS) 的领先跟随样本数据共识问题.
- 为了解释由连续的数据包丢失和随机抽样间隔引入的双重随机性.
- 在不确定的抽样条件下制定一个强大的共识协议.
主要方法:
- 确定同等采样间隔的关系,考虑到随机性和SPLs.
- 制定共识问题作为等效离散时间MAS的随机稳定性问题.
- 使用利亚普诺夫理论和矢量化技术推导出共识标准.
- 使用矩阵重建方法来确定矩阵产品的数学预期.
主要成果:
- 在线MAS在随机抽样和SPL下获得了领先跟随样本数据共识的新型共识标准.
- 用矩阵重建方法确定关键矩阵产品的数学预期.
- 一个共识协议的获取是基于衍生标准设计的.
结论:
- 拟议的方法有效地解决了在随机抽样和连续的数据包损失的情况下,领先跟随抽样数据的共识问题.
- 衍生出的共识标准和设计的协议为网络控制系统提供了一个强大的解决方案,不确定性.
- 理论结果通过实践示例来验证.
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