Citation: | S. Shen, R. Chai, Y. Xia, and S. Chai, “Resilient nonlinear MPC with a dynamic event-triggered strategy under DoS attacks,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 0, pp. 1–3, Aug. 2024. |
[1] |
C. De Persis and P. Tesi, “Input-to-state stabilizing control under Denial-of-Service,” IEEE Trans. Autom. Control, vol. 60, no. 11, pp. 2930–2944, 2015. doi: 10.1109/TAC.2015.2416924
|
[2] |
M. S. Mahmoud, M. M. Hamdan, and U. A. Baroudi, “Modeling and control of cyber-physical systems subject to cyber attacks: A survey of recent advances and challenges,” Neurocomputing, vol. 338, pp. 101–115, 2019. doi: 10.1016/j.neucom.2019.01.099
|
[3] |
G. Franzè, F. Tedesco and D. Famularo, “Resilience against replay attacks: A distributed model predictive control scheme for networked multi-agent systems,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 628–640, 2021. doi: 10.1109/JAS.2020.1003542
|
[4] |
S. Shen, C. Zhang, R. Chai, L. Dai, S. Chai, and Y. Xia, “Stabilizing nonlinear model predictive control under denial-of-service attack via dynamic samples selection,” Automatica, vol. 164, p. 111591, 2024. doi: 10.1016/j.automatica.2024.111591
|
[5] |
W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen, “Data-driven resilient predictive control under denial-of-service,” IEEE Trans. Autom. Control, vol. 68, no. 8, pp. 4722–4737, 2023. doi: 10.1109/TAC.2022.3209399
|
[6] |
T. Huang, D. Wu, and M. Ilić, “Cyber-resilient automatic generation control for systems of AC microgrids,” IEEE Trans. Smart Grid, vol. 15, no. 1, pp. 886–898, 2024. doi: 10.1109/TSG.2023.3272632
|
[7] |
S. Hu, F. Yang, S. Gorbachev, D. Yue, V. Kuzin, and C. Deng, “Resilient control design for networked DC microgrids under time-constrained DoS attacks,” ISA Trans., vol. 127, pp. 197–205, 2022. doi: 10.1016/j.isatra.2022.02.022
|
[8] |
Q. Sun, K. Zhang, and Y. Shi, “Resilient model predictive control of cyber-physical systems under DoS attacks,” IEEE Trans. Industrial Informatics, vol. 16, no. 7, pp. 4920–4927, 2020. doi: 10.1109/TII.2019.2963294
|
[9] |
G. Franzè, W. Lucia, and F. Tedesco, “Resilient model predictive control for constrained cyber-physical systems subject to severe attacks on the communication channels,” IEEE Trans. Autom. Control, vol. 67, no. 4, pp. 1822–1836, 2022. doi: 10.1109/TAC.2021.3084237
|
[10] |
H. Li and Y. Shi, “Event-triggered robust model predictive control of continuous-time nonlinear systems,” Automatica, vol. 50, no. 5, pp. 1507–1513, 2014. doi: 10.1016/j.automatica.2014.03.015
|
[11] |
Z. Hu, R. Su, K. -V. Ling, Y. Guo, and R. Ma, “Resilient event-triggered MPC for load frequency regulation with wind turbines under false data injection attacks,” IEEE Trans. Autom. Science and Engineering, 2023.
|
[12] |
Y. Dai, M. Li, K. Zhang, and Y. Shi, “Robust and resilient distributed MPC for cyber-physical systems against DoS attacks,” IEEE Trans. Industrial Cyber-Physical Systems, vol. 1, pp. 44–55, 2023. doi: 10.1109/TICPS.2023.3283229
|
[13] |
B. Li, X. Zhou, Z. Ning, X. Guan, and K. -F. C. Yiu, “Dynamic event-triggered security control for networked control systems with cyber-attacks: A model predictive control approach,” Information Sciences, vol. 612, pp. 384–398, 2022. doi: 10.1016/j.ins.2022.08.093
|
[14] |
J. Chen, H. Zhang, and G. Yin, “Distributed dynamic event-triggered secure model predictive control of vehicle platoon against DoS attacks,” IEEE Trans. Vehicular Technology, vol. 72, no. 3, pp. 2863–2877, 2023. doi: 10.1109/TVT.2022.3215966
|
[15] |
A. Eqtami, S. Heshmati-Alamdari, D. V. Dimarogonas, and K. J. Kyriakopoulos, “Self-triggered model predictive control for nonholonomic systems,” in Proc. European Control Conf., Zurich, Switzerland, 2013. pp. 638−643.
|