Event-Triggered Resilient L∞ Control for Markov Jump Systems Subject to Denial-of-Service Jamming Attacks

• Published in: IEEE transactions on cybernetics Vol. 52; no. 10; pp. 10240 - 10252
• Main Authors: Zeng, Pengyu, Deng, Feiqi, Liu, Xiaohua, Gao, Xiaobin
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aerospace electronics; Criteria; Denial of service attacks; denial-of-service (DoS) jamming attacks; Denial-of-service attack; event-triggering scheme (ETS); Feedback control; Jamming; L-infinity control; Liapunov functions; Lower bounds; L∞ control; Markov jump systems; Markov processes; Power system stability; Sampled data systems; State feedback; Switches
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2021.3063244

In this article, the event-triggered resilient <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{\infty } </tex-math></inline-formula> control problem is concerned for the Markov jump systems in the presence of denial-of-service (DoS) jamming attacks. First, a fixed lower bound-based event-triggering scheme (ETS) is presented in order to avoid the Zeno problem caused by exogenous disturbance. Second, when DoS jamming attacks are involved, the transmitted data are blocked and the old control input is kept by using the zero-order holder (ZOH). On the basis of this process, the effect of DoS attacks on ETS is further discussed. Next, by utilizing the state-feedback controller and multiple Lyapunov functions method, some criteria incorporating the restriction of DoS jamming attacks are proposed to guarantee the <inline-formula> <tex-math notation="LaTeX">\mathcal {L}_{\infty } </tex-math></inline-formula> control performance of the event-triggered Markov closed-loop jump system. In particular, the bounded transition rates rather than the exact ones are taken into account. That is appropriate for the practical environment in which transition rates of the Markov process are difficult to measure accurately. Correspondingly, some criteria are proposed to obtain state-feedback gains and event-triggering parameters simultaneously. Finally, we provide two examples to show the effectiveness of the proposed method.