Hybrid event-based asynchronous finite-time control for cyber-physical switched systems under denial-of-service attacks

Ren, Hangli; Zong, Guangdeng; Qian, Xiaoliang; Yue, Weichao; Shi, Kaibo

doi:10.1016/j.jfranklin.2022.11.028

Cited by 15 publications

(2 citation statements)

References 38 publications

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“…CPS has the advantages of high integration, efficient collaboration, high self-adaptation, safety and reliability, and has been widely used in smart cities, smart medical care, smart manufacturing and other fields. [4][5][6] Currently, scholars have conducted in-depth research on the theoretical framework of CPS modeling, control and optimization, and proposed a variety of theoretical methods and algorithms, such as data transmission mechanism, 7,8 neural networks 9,10 and information fusions, 11,12 to provide theoretical support for the application of CPS.…”

Section: Introductionmentioning

confidence: 99%

“…Since the insufficient security of the data transmission channel, the presence of vulnerabilities in devices and human factors, data in CPS systems is vulnerable to various attacks, such as denial of service attacks, 7 false data injection attacks, 13 and reply attacks, 14 which threatens the security and reliability of the system. The security problem analysis of CPS has become one of the important research directions.…”

Section: Introductionmentioning

confidence: 99%

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Sampled‐data control for cyber physical systems via identifying false data injection attacks

Yu,

Wei,

Jia

et al. 2023

Adaptive Control & Signal

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SummaryIn this paper, we discuss the security control problem of cyber physical systems based on identifying false data injection attacks. First, the unknown adversary randomly attacks the measurement output, a mechanism is set in the sensor to update the measurement output to the constant, called the one‐valued quantized mechanism. Then, the Bienayme–Chebyshev inequality and the one‐valued quantized mechanism are utilized to design an identification algorithm, the estimated value of the false data injection attack and the minimum identification time can be obtained. Furthermore, based on the LMI theory, sampled‐data control gains with and without attacks are obtained to ensure the system mean‐square exponential stable, respectively. And the corresponding maximum sampling period of the controller is obtained. Finally, numerical examples verify the correctness and effectiveness of the theory.

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