| Autor: |
Ling Chen, Guanqi Wang, Feng Li |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 12, Pp 48388-48393 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3384237 |
| Popis: |
This study addresses $\mathcal {H}_{\infty }$ filtering against DoS attacks within the framework of singular Markov jump systems. To provide a more comprehensive depiction of the issue pertaining to cyber security, DoS attacks are perceived as occurring in an unpredictable manner and can be represented by a collection of a random variable that follows the Bernoulli distribution. Consequently, the corresponding filter error system is formulated. Utilizing a set of viable linear matrix inequalities, this research establishes criteria of stochastically admissible for filter error system, ensuring a specified $\mathcal {H}_{\infty }$ performance. A filter design method under DoS attacks is proposed. Finally, the effectiveness of this method is demonstrated through a practical example involving a tunnel diode model. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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