Research Center of Automation and Artificial Intelligence, Zhejiang University of Technology, Hangzhou, 310023, China.
Research Center of Automation and Artificial Intelligence, Zhejiang University of Technology, Hangzhou, 310023, China.
ISA Trans. 2022 Oct;129(Pt B):1-14. doi: 10.1016/j.isatra.2022.02.005. Epub 2022 Feb 10.
This paper is concerned with the injection attack estimation for a class of networked control systems with Deny-of-Service (DoS) attack, where unknown signals are injected into the sensor reading and actuator. The main goal is to design an estimator to estimate the injected signals subject to stochastic hidden DoS attack. By introducing a semi-Markov chain, the complex aperiodic sampling behavior caused by DoS attack is first modeled as a stochastic switching system. By using the Lyapunov stability theory and stochastic system analysis method, the σ-error mean square stability (σ-EMSS) conditions of estimation error system are then derived and the state of the attack estimation error system is shown to be uniformly ultimately bounded. Some linear matrix inequalities are proposed to determine the estimation gain matrices. Finally, both simulation and experimental studies on the motor system are conducted, and the effectiveness of the main results are demonstrated.
本文研究了一类具有拒绝服务（DoS）攻击的网络控制系统的注入攻击估计问题，其中未知信号被注入到传感器读数和执行器中。主要目标是设计一个估计器来估计注入信号，同时考虑随机隐藏 DoS 攻击。通过引入半马尔可夫链，首先将 DoS 攻击引起的复杂非周期采样行为建模为随机切换系统。利用李雅普诺夫稳定性理论和随机系统分析方法，推导出估计误差系统的σ-均方误差稳定性（σ-EMSS）条件，并证明了攻击估计误差系统的状态是一致最终有界的。提出了一些线性矩阵不等式来确定估计增益矩阵。最后，对电机系统进行了仿真和实验研究，验证了主要结果的有效性。
