A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 13
Issue 8
IEEE/CAA Journal of Automatica Sinica
| Citation: | N. He, W. Li, and K. Ma, “Resilient MPC for constrained CPS against FDI attacks with adaptive dual-horizon mechanism,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 8, pp. 2000–2002, Aug. 2026. doi: 10.1109/JAS.2025.125618
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| [1] |
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, Art. no. 111591, 2024. doi: 10.1016/j.automatica.2024.111591
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| [2] |
C. Gu, X. Wang, K. Li, X. Yin, S. Li, and L. Wang, “Enhanced tube-based event-triggered stochastic model predictive control with additive uncertainties,” IEEE/CAA J. Autom. Sinica, vol. 12, no. 3, pp. 596–605, 2025. doi: 10.1109/JAS.2024.124974
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| [3] |
Y. Xia, X. Wang, X. Yin, et al., “Federated accelerated deep reinforcement learning for multi-zone HVAC control in commercial buildings,” IEEE Trans. Smart Grid, vol. 16, no. 3, pp. 2599–2610, 2025. doi: 10.1109/TSG.2024.3524756
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| [4] |
Z. Yu, H. Gao, X. Cong, N. Wu, and H. H. Song, “A survey on cyber–physical systems security,” IEEE Internet of Things Journal, vol. 10, no. 24, pp. 21670−21686, Dec.15, 2023.
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| [5] |
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
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| [6] |
X. Liu, L. Qiu, J. Rodríguez, K. Wang, Y. Li, and Y. Fang, “Learning-based resilient FCS-MPC for power converters under actuator FDI attacks,” IEEE Trans. Power Electronics, vol. 39, no. 10, pp. 12716–12728, 2024. doi: 10.1109/TPEL.2024.3416292
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J. Wang, Y. Song, and G. Wei, “Security-based resilient robust model predictive control for polytopic uncertain systems subject to deception attacks and RR protocol,” IEEE Trans. Systems, Man, and Cybern.: Systems, vol. 52, no. 8, pp. 4772–4783, 2022. doi: 10.1109/TSMC.2021.3103538
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| [8] |
K. Ma, N. He, and Z. Fan, “Resilient self-triggered predictive control for nonlinear system under dual-channel deception attacks,” Nonlinear Dynamics, vol. 112, no. 22, pp. 20081–20099, 2024. doi: 10.1007/s11071-024-10080-5
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| [9] |
Z.-H. Pang, L.-Z. Fan, K. Liu, and G.-P. Liu, “Detection of stealthy false data injection attacks against networked control systems via active data modification,” Inf. Sci., vol. 546, pp. 192–205, 2021. doi: 10.1016/j.ins.2020.06.074
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| [10] |
A. Li and J. Sun, “Self-triggered model predictive control for nonlinear continuous-time networked system via ensured performance control samples selection,” Int. J. Control, vol. 95, no. 10, pp. 2793–2801, 2022. doi: 10.1080/00207179.2021.1936189
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| [11] |
H. Michalska and D. Q. Mayne, “Robust receding horizon control of constrained nonlinear systems,” IEEE Trans. Autom. Control, vol. 38, no. 11, pp. 1623–1633, 1993. doi: 10.1109/9.262032
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