在对抗性环境下的网络物理系统的弹性分布式优化:基于事件的方法
Zirui Liao1, Shaoping Wang2, Jian Shi2
1School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China; Ningbo Institute of Technology, Beihang University, Ningbo, 315800, China; Shenyuan Honors College, Beihang University, Beijing, 100191, China.
ISA transactions
|April 20, 2024
概括
本研究介绍了一种由事件触发的算法,用于网络物理系统 (CPS) 中的弹性分布式优化,以确保尽管存在对抗性攻击,但仍能实现代理融合. 该方法提高了准确性,并减少了微电网经济调度等实际应用的通信开销.
科学领域:
- 网络物理系统 (CPSs) 是指
- 分布式优化 分布式优化
- 控制理论 控制理论
背景情况:
- 网络物理系统需要强大的优化算法,以便在敌对条件下可靠地运行.
- 现有的分布式优化方法往往缺乏对复杂的网络攻击的弹性.
- 事件触发机制为高效和安全的分布式控制提供了潜力.
研究的目的:
- 为网络物理系统 (CPS) 开发一种弹性分布式优化算法,在敌对环境下有效运行.
- 针对两个特定的攻击场景:f-总和f-局部攻击.
- 为了确保良性代理商的趋同和最佳性,尽管有恶意代理商的行为.
主要方法:
- 一个事件触发机制集成到分布式优化框架中.
- 该算法旨在优化多个代理的平均凸成本函数.
- 理论分析用于在攻击场景下推导收和最佳性条件.
主要成果:
- 拟议的具有事件触发 (RDO-E) 算法的弹性分布式优化保证了良性代理在f-总和f-局部攻击下以有限的错误范围趋同.
- 建立了最佳性条件,确保即使有恶意代理,也能达到安全区间的趋同.
- 数字示例表明,与现有的弹性算法相比,它具有更高的准确性和更低的通信开销.
结论:
- RDO-E算法为在对抗性CPS环境中分布式优化提供了强大的和高效的解决方案.
- 该算法的实际可行性通过在多微电网系统中成功应用于弹性经济调度问题来验证.
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