弹性分布式MPC用于动态合的多个网络物理系统,这些系统可能受到严重攻击.
IEEE transactions on cybernetics
|May 26, 2025
概括
本研究介绍了针对网络物理系统 (CPS) 的弹性分布式模型预测控制 (DMPC) 算法,以应对严重的网络攻击. 尽管攻击的持续时间和干扰是未知的,但DMPC确保了系统稳定性和约束满足.
科学领域:
- 控制工程 控制工程 控制工程
- 网络物理系统安全 网络物理系统安全
- 分布式控制 分布式控制
背景情况:
- 网络物理系统 (CPS) 越来越容易受到针对通信道的复杂网络攻击.
- 现有的控制策略往往缺乏对未知和适应性攻击模式的弹性.
- 在逆境条件下确保系统稳定性和性能是一个关键的挑战.
研究的目的:
- 为受约束,动态合的多个CPS提出一个弹性分布式模型预测控制 (DMPC) 算法.
- 为了应对对控制器-执行器 (C-A),传感器-控制器 (S-C) 和子系统间通道的严重攻击.
- 为了保证系统性能和约束满足,而无需攻击者事先了解.
主要方法:
- 一步时间延迟策略被纳入本地模型预测控制器 (MPC) 设计中,用于数据验证.
- 约束收紧技术用于开发无限地平线MPC问题的最小保守约束.
- 为了确保递归可行性,导出一个等价的有限束集.
- 实现了一个探测器模块,以识别和减轻改数据的影响.
主要成果:
- 拟议的DMPC算法证明了对多个通信道的严重攻击的弹性.
- 在所有允许的攻击场景和干扰下,系统实现了统一的最终边界性 (UUB).
- 在整个无限地平线控制问题中,限制满意度保持不变,即使攻击持续时间未知.
- 算法的有效性通过全面的案例研究来验证.
结论:
- 开发的弹性DMPC算法有效地提高了网络物理系统的安全性和可靠性.
- 该方法为在对抗性网络威胁下运营的CPS提供了强大的解决方案.
- 这些发现有助于推进安全可靠的分布式控制系统.
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