382
Views
36
CrossRef citations to date
0
Altmetric
Articles

Finite-time distributed resilient state estimation subject to hybrid cyber-attacks: a new dynamic event-triggered case

, &
Pages 2832-2844 | Received 30 Jan 2022, Accepted 23 May 2022, Published online: 20 Oct 2022

References

  • Baig, Z. A., Sanguanpong, S., Firdous, S. N., Nguyen, T. G., & So-In, C. (2020). Averaged dependence estimators for DoS attack detection in IoT networks. Future Generation Computer Systems, 102, 198–209. https://doi.org/10.1016/j.future.2019.08.007
  • Battistelli, G., Chisci, L., Mugnai, G., Farina, A., & Graziano, A. (2015). Consensus-based linear and nonlinear filtering. IEEE Transactions on Automatic Control, 60(5), 1410–1415. https://doi.org/10.1109/TAC.2014.2357135
  • Cattivelli, F. S., & Sayed, A. H. (2010). Diffusion strategies for distributed Kalman filtering and smoothing. IEEE Transactions on Automatic Control, 55(9), 2069–2084. https://doi.org/10.1109/TAC.2010.2042987
  • Chen, B., Ho, D. W. C., Zhang, W., & Yu, L. (2019). Distributed dimensionality reduction fusion estimation for cyber-physical systems under DoS attacks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(2), 455–468. https://doi.org/10.1109/TSMC.2017.2697450
  • Chen, W., Ding, D., Dong, H., & Wei, G. (2019). Distributed resilient filtering for power systems subject to denial-of-service attacks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(8), 1688–1697. https://doi.org/10.1109/TSMC.6221021
  • Ding, D., Wang, Z., & Han, Q.-L. (2019). A set-membership approach to event-triggered filtering for general nonlinear systems over sensor networks. IEEE Transactions on Automatic Control, 65(4), 1792–1799. https://doi.org/10.1109/TAC.9
  • Ge, X., Han, Q.-L., Zhong, M., & Zhang, X.-M. (2019). Distributed Krein space-based attack detection over sensor networks under deception attacks. Automatica, 109, Article 108557. https://doi.org/10.1016/j.automatica.2019.108557
  • Ge, X., Xiao, S., Han, Q.-L., Zhang, X.-M., & Ding, D. (2022). Dynamic event-triggered scheduling and platooning control co-design for automated vehicles over vehicular ad-hoc networks. IEEE/CAA Journal of Automatica Sinica, 9(1), 31–46. https://doi.org/10.1109/JAS.2021.1004060
  • Hu, J., Wang, Z., Alsaadi, F. E., & Hayat, T. (2017). Event-based filtering for time-varying nonlinear systems subject to multiple missing measurements with uncertain missing probabilities. Information Fusion, 38, 74–83. https://doi.org/10.1016/j.inffus.2017.03.003
  • Hu, J., Wang, Z., Liu, G.-P., Jia, C., & Williams, J. (2020). Event-triggered recursive state estimation for dynamical networks under randomly switching topologies and multiple missing measurements. Automatica, 115, Article 108908. https://doi.org/10.1016/j.automatica.2020.108908
  • Ju, Y., Ding, D., He, X., Han, Q.-L., & Wei, G. (in press). Consensus control of multi-agent systems using fault-estimation-in-the-loop: Dynamic event-triggered case. IEEE/CAA Journal of Automatica Sinica. https://doi.org/10.1109/JAS.2021.1004386
  • Kar, S., Moura, J. M. F., & Ramanan, K. (2012). Distributed parameter estimation in sensor networks: Nonlinear observation models and imperfect communication. IEEE Transactions on Information Theory, 58(6), 3575–3605. https://doi.org/10.1109/TIT.2012.2191450
  • Li, Q., Shen, B., Wang, Z., Huang, T., & Luo, J. (2019). Synchronization control for a class of discrete time-delay complex dynamical networks: A dynamic event-triggered approach. IEEE Transactions on Cybernetics, 49(5), 1979–1986. https://doi.org/10.1109/TCYB.6221036
  • Li, Q., Shen, B., Wang, Z., & Sheng, W. (2020). Recursive distributed filtering over sensor networks on Gilbert-Elliott channels: A dynamic event-triggered approach. Automatica, 113, Article 108681.
  • Liu, J., Yang, M., Tian, E., Cao, J., & Fei, S. (2019). Event-based security control for state-dependent uncertain systems under hybrid-attacks and its application to electronic circuits. IEEE Transactions on Circuits and Systems I: Regular Papers, 66(12), 4817–4828. https://doi.org/10.1109/TCSI.8919
  • Liu, Q., Wang, Z., He, X., Ghinea, G., & Alsaadi, F. E. (2017). A resilient approach to distributed filter design for time-varying systems under stochastic nonlinearities and sensor degradation. IEEE Transactions on Signal Processing, 65(5), 1300–1309. https://doi.org/10.1109/TSP.2016.2634541
  • Liu, S., Wang, Z., Wei, G., & Li, M. (2020). Distributed set-membership filtering for multirate systems under the Round-Robin scheduling over sensor networks. IEEE Transactions on Cybernetics, 50(5), 1910–1920. https://doi.org/10.1109/TCYB.6221036
  • Ma, L., Wang, Z., Han, Q.-L., & Liu, Y. (2019). Distributed filtering for nonlinear time-delay systems over sensor networks subject to multiplicative link noises and switching topology. International Journal of Robust and Nonlinear Control, 29, 2941–2959. https://doi.org/10.1002/rnc.v29.10
  • Olfati-Saber, R. (2009). Kalman-consensus filter: Optimality, stability, and performance. In Proceedings of the 48th IEEE Conference on Decision and Control (pp. 7036–7042).
  • Pajic, M., Weimer, J., Bezzo, N., Sokolsky, O., Pappas, G. J., & Lee, I. (2017). Design and implementation of attack-resilient cyberphysical systems: With a focus on attack-resilient state estimators. IEEE Control Systems Magazine, 37(2), 66–81. https://doi.org/10.1109/MCS.2016.2643239
  • Peng, C., Sun, H., Yang, M., & Wang, Y. (2019). A survey on security communication and control for smart grids under malicious cyber attacks. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(8), 1554–1569. https://doi.org/10.1109/TSMC.6221021
  • Shen, B., Wang, Z., & Qiao, H. (2017). Event-triggered state estimation for discrete-time multidelayed neural networks with stochastic parameters and incomplete measurements. IEEE Transactions on Neural Networks and Learning Systems, 28(5), 1152–1163. https://doi.org/10.1109/TNNLS.2016.2516030
  • Song, H., Ding, D., Dong, H., & Yi, X. (2022). Distributed filtering based on Cauchy-kernel-based maximum correntropy subject to randomly occurring cyber-attacks. Automatica, 135, Article 110004.
  • Sun, Y., Ding, D., Dong, H., & Wei, G. (2020). Resilient ℓ2- ℓ∞ filtering with dwell-time-based communication scheduling. Nonlinear Analysis: Hybrid Systems, 37, Article 100901.
  • Wang, X., Ding, D., Dong, H., & Zhang, X.-M. (2021). Neural-network-based control for discrete-time nonlinear systems with input saturation under stochastic communication protocol. IEEE/CAA Journal of Automatica Sinica, 8(4), 766–778. https://doi.org/10.1109/JAS.6570654
  • Wang, X., Ding, D., Ge, X., & Han, Q.-L. (2021). Neural-network-based control for discrete-time nonlinear systems with denial-of-service attack: The adaptive event-triggered case. International Journal of Robust and Nonlinear Control, 32(5), 2760–2779. https://doi.org/10.1002/rnc.v32.5
  • Xu, Y., Lu, R., Shi, P., Li, H., & Xie, S. (2018). Finite-time distributed state estimation over sensor networks with round-robin protocol and fading channels. IEEE Transactions on Cybernetics, 48(1), 336–345. https://doi.org/10.1109/TCYB.2016.2635122
  • Yang, Y., Xu, H., & Yue, D. (2019). Observer-based distributed secure consensus control of a class of linear multi-agent systems subject to random attacks. IEEE Transactions on Circuits and Systems I: Regular Papers, 66(8), 3089–3099. https://doi.org/10.1109/TCSI.8919
  • Zhang, D., Shi, P., Zhang, W., & Yu, L. (2017). Energy-efficient distributed filtering in sensor networks: A unified switched system approach. IEEE Transactions on Cybernetics, 47(7), 1618–1629.
  • Zhang, D., Xu, Z., Karimi, H. R., & Wang, Q.-G. (2017). Distributed filtering for switched linear systems with sensor networks in presence of packet dropouts and quantization. IEEE Transactions on Circuits and Systems I: Regular Papers, 64(10), 2783–2796. https://doi.org/10.1109/TCSI.2017.2695481
  • Zhang, H., Cheng, P., Shi, L., & Chen, J. (2015). Optimal denial-of-service attack scheduling with energy constraint. IEEE Transactions on Automatic Control, 60(11), 3023–3028. https://doi.org/10.1109/TAC.9
  • Zhang, X.-M., Zhu, F., Zhang, J., & Liu, T. (2022). Attack isolation and location for a complex network cyber-physical system via zonotope theory. Neurocomputing, 469, 239–250. https://doi.org/10.1016/j.neucom.2021.10.070
  • Zhao, C., Lam, J., & Lin, H. (2021). State estimation of CPSs with deception attacks: Stability analysis and approximate computation. Neurocomputing, 423, 318–326. https://doi.org/10.1016/j.neucom.2020.10.055
  • Zhao, J., Gomez-Exposito, A., Netto, M., Mili, L., Abur, A., Terzija, V., Kamwa, I., Pal, B., Singh, A. K., Qi, J., Huang, Z., & Meliopoulos, A. P. S. (2019). Power system dynamic state estimation: Motivations, definitions, methodologies, and future work. IEEE Transactions on Power Systems, 34(4), 3188–3198. https://doi.org/10.1109/TPWRS.59
  • Zhu, M., & Martínez, S. (2014). On the performance analysis of resilient networked control systems under replay attacks. IEEE Transactions on Automatic Control, 59(3), 804–808. https://doi.org/10.1109/TAC.2013.2279896
  • Zhu, S., Chen, C., Li, W., Yang, B., & Guan, X. (2013). Distributed optimal consensus filter for target tracking in heterogeneous sensor networks. IEEE Transactions on Cybernetics, 43(6), 1963–1976. https://doi.org/10.1109/TSMCB.2012.2236647
  • Zou, L., Wang, Z., Han, Q.-L., & Zhou, D. H. (2021a). Full information estimation for time-varying systems subject to round-robin scheduling: A recursive filter approach. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(3), 1904–1916. https://doi.org/10.1109/TSMC.6221021
  • Zou, L., Wang, Z., Han, Q.-L., & Zhou, D. H. (2021b). Moving horizon estimation of networked nonlinear systems with random access protocol. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(5), 2937–2948. https://doi.org/10.1109/TSMC.2019.2918002
  • Zou, L., Wang, Z., Hu, J., & Dong, H. (2022). Ultimately bounded filtering subject to impulsive measurement outliers. IEEE Transactions on Automatic Control, 67(1), 304–319. https://doi.org/10.1109/TAC.2021.3081256
  • Zou, L., Wang, Z., & Zhou, D. H. (2020). Moving horizon estimation with non-uniform sampling under component-based dynamic event-triggered transmission. Automatica, 120, Article 109154.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.