计算机科学
服务拒绝攻击
方案(数学)
网络数据包
模型预测控制
事件(粒子物理)
理论(学习稳定性)
集合(抽象数据类型)
班级(哲学)
控制理论(社会学)
控制(管理)
计算机网络
互联网
数学
人工智能
万维网
数学分析
程序设计语言
物理
机器学习
量子力学
作者
Yiwen Qi,Simeng Zhang,Wenke Yu,Jie Huang
标识
DOI:10.1016/j.ins.2022.10.088
摘要
This paper studies model predictive security control (MPSC) for networked switched systems under denial-of-service (DoS) attacks. Most of existing works only adjust the triggering scheme when being attacked. Different from them, this paper proposes a novel timing-response event-triggering scheme (TR-ETS) to reduce the impact of attacks on system performance, which can not only configure system resources adaptively, but also accurately detect attack information and compensate the attacked data. Specifically, the proposed scheme includes two event-based triggers, which can dynamically and jointly regulate the communication/calculation ability, generate virtual attack sequences and acquire the number of passive packet loss. Then, based on the triggered states, a class of model predictive controllers is designed to optimize the control action. Due to possible strong attacks, a security control framework including network and local loops be introduced and a permissable type-switching mechanism (PTM) is used. Under the permissable controllers (i.e., network and local controllers), sufficient conditions for the stability of closed-loop switched systems are derived. In addition, a set of model predictive optimization algorithm using linear matrix inequalities (LMIs) technique is addressed. Finally, the effectiveness of the proposed method is verified by illustrative examples.
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