对于具有动态定量化的非同质马尔科夫跳跃系统的异步故障检测过,可能会受到新型混合网络攻击
Mingang Hua1, Ni Sun1, Feiqi Deng2
1College of Artificial Intelligence and Automation, Hohai University, Changzhou 213200, China.
ISA transactions
|September 25, 2024
概括
本研究介绍了一种异步故障检测过器,用于面临动态量子化和混合网络攻击的不均马尔科夫跳跃系统. 该方法在复杂的网络条件下确保了系统稳定性和性能.
科学领域:
- 控制系统工程 控制系统工程
- 网络物理系统安全 网络物理系统安全
- 随机系统分析 随机系统分析
背景情况:
- 非均的马尔科夫跳跃系统容易受到网络攻击和数据定量化,影响故障检测可靠性.
- 现有的故障检测方法经常与异步信息和复杂的攻击场景作斗争.
研究的目的:
- 为非均的马尔科夫跳跃系统开发一个异步故障检测过器.
- 为应对动态量化和新型混合网络攻击模型所带来的挑战.
- 在不确定的条件下确保随机稳定性和H∞性能.
主要方法:
- 利用基于多重组结构的过渡概率来建模非均的马尔科夫过程.
- 在异步过器中使用隐藏的马尔科夫模型来访问全面的工厂模式信息.
- 开发了一种新的混合网络攻击模式,包括欺骗,拒绝服务和联合攻击.
- 构建了一个Lyapunov功能,以获得足够的稳定性和性能条件.
主要成果:
- 建立了足够的条件,以实现H∞性能的随机稳定性.
- 拟议的异步故障检测过模型证明了在非异热连续动反应堆上的实际适用性.
- 模拟结果验证了开发的设计方法的有效性和实用性.
结论:
- 拟议的异步故障检测过器有效地处理动态量子化和混合网络攻击在非均的马尔科夫跳跃系统.
- 该方法确保了强大的系统性能和稳定性,通过工业应用和模拟进行验证.
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