Recursive filtering of networked nonlinear systems: a survey

References

• Arasaratnam, I., & Haykin, S. (2009). Cubature Kalman filters. IEEE Transactions on Automatic Control, 54(6), 1254–1269. https://doi.org/10.1109/TAC.2009.2019800
   Web of Science ®Google Scholar
• Arasaratnam, I., Haykin, S., & Hurd, T. R. (2010). Cubature Kalman filtering for continuous-discrete systems: Theory and simulations. IEEE Transactions on Signal Processing, 58(10), 4977–4993. https://doi.org/10.1109/TSP.2010.2056923
   Web of Science ®Google Scholar
• Aung, H., Soon, J. J., Goh, S. T., Lew, J. M., & Low, K.-S. (2020). Battery management system with state-of-charge and opportunistic state-of-health for a miniaturized satellite. IEEE Transactions on Aerospace and Electronic Systems, 56(4), 2978–2989. https://doi.org/10.1109/TAES.7
   Web of Science ®Google Scholar
• Ballreich, D. (2019). Stable and efficient cubature rules by metaheuristic optimization with application to Kalman filtering. Automatica, 101, 157–165. https://doi.org/10.1016/j.automatica.2018.11.041
   Web of Science ®Google Scholar
• Berman, N., & Shanked, U. (2006). H∞ control for discrete-time nonlinear stochastic systems. IEEE Transactions on Automatic Control, 51(6), 1041–1046. https://doi.org/10.1109/TAC.2006.876808
   Web of Science ®Google Scholar
• Boutayeb, M., Rafaralahy, H., & Darouach, M. (1997). Convergence analysis of the extended Kalman filter used as an observer for nonlinear deterministic discrete-time systems. IEEE Transactions on Automatic Control, 42(4), 581–586. https://doi.org/10.1109/9.566674
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Chen, W., Ding, D., Ge, X., Han, Q.-L., & Wei, G. (2020). H∞ containment control of multi-agent systems under event-triggered communication scheduling: The finite-horizon case. IEEE Transactions on Cybernetics, 50(4), 1372–1382. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Chen, S., Ma, L., & Ma, Y. (2020). Distributed set-membership filtering for nonlinear systems subject to round-robin protocol and stochastic communication protocol over sensor networks. Neurocomputing, 385, 13–21. https://doi.org/10.1016/j.neucom.2019.11.056
   Web of Science ®Google Scholar
• Cui, B., Chen, X., Tang, X., Huang, H., & Liu, X. (2018). Robust cubature Kalman filter for GNSS/INS with missing observations and colored measurement noise. ISA Transactions, 72, 138–146. https://doi.org/10.1016/j.isatra.2017.09.019
   PubMed Web of Science ®Google Scholar
• Daid, A., Busvelle, E., & Aidene, M. (2020). On the convergence of the unscented Kalman filter. European Journal of Control. Advance online publication. https://doi.org/10.1016/j.ejcon.2020.05.003
   PubMed Web of Science ®Google Scholar
• Ding, D., Han, Q.-L., & Ge, J. W. (2020). Secure state estimation and control of cyber-physical systems: A survey. IEEE Transactions on Systems, Man, and Cybernetics-Systems. Advance online publication. https://doi.org/10.1109/TSMC.2020.3041121
   Web of Science ®Google Scholar
• Ding, L., Han, Q.-L., Ning, B., & Yue, D. (2020). Distributed resilient finite-time secondary control for heterogeneous battery energy storage systems under denial-of-service attacks. IEEE Transactions on Industrial Informatics, 16(7), 4909–4919. https://doi.org/10.1109/TII.9424
   Web of Science ®Google Scholar
• Ding, D., Han, Q.-L., Wang, Z., & Ge, X. (2019). A survey on model-based distributed control and filtering for industrial cyber-physical systems. IEEE Transactions on Industrial Informatics, 15(5), 2483–2499. https://doi.org/10.1109/TII.9424
   Web of Science ®Google Scholar
• Ding, D., Han, Q.-L., Wang, Z., & Ge, X. (2020). Distributed recursive filtering of cyber-physical systems with security defenses. IEEE Transactions on Systems, Man and Cybernetics-Systems. Advance online publication. https://doi.org/10.1109/TSMC.2019.2960541
   Web of Science ®Google Scholar
• Ding, L., Han, Q.-L., & Zhang, X.-M. (2020). Distributed secondary control for active power sharing and frequency regulation in islanded microgrids using an event-triggered communication mechanism. IEEE Transactions on Industrial Informatics, 15(7), 3910–3922. https://doi.org/10.1109/TII.9424
   Web of Science ®Google Scholar
• Ding, D., Wang, Z., Dong, H., & Shu, H. (2012). Distributed H∞ state estimation with stochastic parameters and nonlinearities through sensor networks: The finite-horizon case. Automatica, 48(8), 1575–1585. https://doi.org/10.1016/j.automatica.2012.05.070
   Web of Science ®Google Scholar
• Ding, D., Wang, Z., & Han, Q.-L. (2020). 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
   Web of Science ®Google Scholar
• Ding, D., Wang, Z., Han, Q.-L., & Wei, G. (2019). Neural-network-based output-feedback control under Round-Robin scheduling protocols. IEEE Transactions on Cybernetics, 49(6), 2372–2384. https://doi.org/10.1109/TCYB.2018.2827037
   PubMed Web of Science ®Google Scholar
• Ding, D., Wang, Z., Ho, D. W. C., & Wei, G. (2017). Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks. Automatica, 78, 231–240. https://doi.org/10.1016/j.automatica.2016.12.026
   Web of Science ®Google Scholar
• Ding, D., Wang, Z., Lam, J., & Shen, B. (2015). Finite-horizon H∞ control for discrete time-varying systems with randomly occurring nonlinearities and fading measurements. IEEE Transactions on Automatic Control, 60(9), 2488–2491. https://doi.org/10.1109/TAC.2014.2380671
   Web of Science ®Google Scholar
• Donkers, M. C. F., Heemels, W. P. M. H., van de Wouw, N., & Hetel, L. (2019). Stability analysis of networked control systems using a switched linear systems approach. IEEE Transactions on Automatic Control, 56(9), 2101–2115. https://doi.org/10.1109/TAC.2011.2107631
   Web of Science ®Google Scholar
• Fan, Y., Liu, L., Feng, G., & Wang, Y. (2015). Self-triggered consensus for multi-agent systems with zeno-free triggers. IEEE Transactions on Automatic Control, 60(10), 2779–2784. https://doi.org/10.1109/TAC.2015.2405294
   Web of Science ®Google Scholar
• Ge, X., Han, Q.-L., Ding, L., Wang, Y., & Zhang, X.-M. (2020). Dynamic event-triggered distributed coordination control and its applications: A survey of trends and techniques. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(9), 3112–3125. https://doi.org/10.1109/TSMC.6221021
   Web of Science ®Google Scholar
• Ge, X., Han, Q.-L., & Wang, Z. (2019a). A dynamic event-triggered transmission scheme for distributed set-membership estimation over wireless sensor networks. IEEE Transactions on Cybernetics, 49(1), 171–183. https://doi.org/10.1109/TCYB.2017.2769722
   PubMed Web of Science ®Google Scholar
• Ge, X., Han, Q.-L., & Wang, Z. (2019b). A threshold-parameter-dependent approach to designing distributed event-triggered H∞ consensus filters over sensor networks. IEEE Transactions on Cybernetics, 49(4), 1148–1159. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Ge, X., Han, Q.-L., Zhang, X.-M., Ding, L., & Yang, F. (2020). Distributed event-triggered estimation over sensor networks: A survey. IEEE Transactions on Cybernetics, 50(3), 1306–1320. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• 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 No. 108557. https://doi.org/10.1016/j.automatica.2019.108557
   PubMed Web of Science ®Google Scholar
• Ghaoui, L., & Calafiore, G. (2001). Robust filtering for discrete-time systems with bounded noise and parametric uncertainty. IEEE Transactions on Automatic Control, 46(7), 1084–1089. https://doi.org/10.1109/9.935060
   Web of Science ®Google Scholar
• Girard, A. (2015). Dynamic triggering mechanisms for event-triggered control. IEEE Transactions on Automatic Control, 60(7), 1992–1997. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Hu, J., Wang, Z., & Gao, H. (2018). Joint state and fault estimation for time-varying nonlinear systems with randomly occurring faults and sensor saturations. Automatica, 97, 150–160. https://doi.org/10.1016/j.automatica.2018.07.027
   Web of Science ®Google Scholar
• Hu, J., Wang, Z., Liu, S., & Gao, H. (2016). A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements. Automatica, 64, 155–162. https://doi.org/10.1016/j.automatica.2015.11.008
   Web of Science ®Google Scholar
• Hu, J., Wang, Z., Liu, G.-P., & Williams, J. (2020). Event-triggered recursive state estimation for dynamical networks under randomly switching topologies and multiple missing measurements. Automatica, 115, Article ID: 108908. Advance online publication. https://doi.org/10.1016/j.automatica.2020.108908
   Web of Science ®Google Scholar
• Hu, J., Wang, Z., Liu, G.-P., & Zhang, H. (2020). Variance-constrained recursive state estimation for time-varying complex networks with quantized measurements and uncertain inner coupling. IEEE Transactions on Neural Networks and Learning Systems, 31(6), 1955–1967. https://doi.org/10.1109/TNNLS.5962385
   PubMed Web of Science ®Google Scholar
• Hu, J., Wang, Z., Shen, B., & Gao, H. (2013). Quantised recursive filtering for a class of nonlinear systems with multiplicative noises and missing measurements. International Journal of Control, 86(4), 650–663. https://doi.org/10.1080/00207179.2012.756149
   Web of Science ®Google Scholar
• Huang, Y., Zhang, Y., Xu, B., Wu, Z., & Chambers, J. A. (2018). A new adaptive extended Kalman filter for cooperative localization. IEEE Transactions on Aerospace and Electronic Systems, 54(1), 353–368. https://doi.org/10.1109/TAES.7
   Web of Science ®Google Scholar
• Jiang, K., Zhang, H., Karimi, H. R., Lin, J., & Song, L. (2020). Simultaneous input and state estimation for integrated motor-transmission systems in a controller area network environment via an adaptive unscented kalman filter. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(4), 1570–1579. https://doi.org/10.1109/TSMC.6221021
   Web of Science ®Google Scholar
• Ju, Y., Wei, G., Ding, D, & Liu, S. (2020). A novel fault detection method under weighted try-once-discard scheduling over sensor networks. IEEE Transactions on Control of Network Systems, 7(3), 1489–1499. https://doi.org/10.1109/TCNS.6509490
   Web of Science ®Google Scholar
• Ju, Y., Wei, G., Ding, D., & Zhang, S. (2020). Fault detection for discrete time-delay networked systems with round-robin protocol in finite-frequency domain. International Journal of Systems Science, 50(13), 2497–2509. https://doi.org/10.1080/00207721.2019.1671530
   Web of Science ®Google Scholar
• Julier, S., Uhlmann, J., & Durrant-Whyte, H. (1995). A new approach for filtering nonlinear systems. In Proceedings of 1995 American control conference – ACC'95 (Vol. 3, pp. 1628–1632).
   Google Scholar
• Kooshkbaghi, M., & Marquez, H. J. (2020). Event-triggered discrete-time cubature Kalman filter for nonlinear dynamical systems with packet dropout. IEEE Transactions on Automatic Control, 65(5), 2278–2285. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Li, X., Dong, H., Wang, Z., & Han, F. (2019). Set-membership filtering for state-saturated systems with mixed time-delays under weighted try-once-discard protocol. IEEE Transactions on Circuits and Systems II: Express Briefs, 66(2), 312–316. https://doi.org/10.1109/TCSII.2018.2855701
   Web of Science ®Google Scholar
• Li, S., Hu, Y., Zheng, L., Li, Z., Chen, X., Fernando, T., Iu, H. H. C, Wang, Q., & Liu, X. (2019). Stochastic event-triggered cubature Kalman filter for power system dynamic state estimation. IEEE Transactions on Circuits and Systems II: Express Briefs, 66(9), 1552–1556. https://doi.org/10.1109/TCSII.8920
   Web of Science ®Google Scholar
• Li, L., Niu, M., Xia, Y., Yang, H., & Yan, L. (2019). Event-triggered distributed fusion estimation with random transmission delays. Information Sciences, 475, 67–81. https://doi.org/10.1016/j.ins.2018.09.022
   Web of Science ®Google Scholar
• Li, Q., Wang, Z., Sheng, W., Alsaadi, F. E., & Alsaadi, F. E. (2020). Dynamic event-triggered mechanism for H∞ non-fragile state estimation of complex networks under randomly occurring sensor saturations. Information Sciences, 509, 304–316. https://doi.org/10.1016/j.ins.2019.08.063
   Web of Science ®Google Scholar
• Li, J., Wei, G., Ding, D., & Li, Y. (2019). Set-membership filtering for discrete time-varying nonlinear systems with censored measurements under Round-Robin protocol. Neurocomputing, 281, 20–26. https://doi.org/10.1016/j.neucom.2017.11.033
   Web of Science ®Google Scholar
• Li, L., & Xia, Y. (2015). UKF-based nonlinear filtering over sensor networks with wireless fading channel. Information Sciences, 316, 132–147. https://doi.org/10.1016/j.ins.2015.04.026
   Web of Science ®Google Scholar
• Li, L., Yu, D., Xia, Y., & Yang, H. (2019). Remote nonlinear state estimation with stochastic event-triggered sensor schedule. IEEE Transactions on Cybernetics, 49(3), 734–745. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Liu, S., Wang, Z., Chen, Y., & Wei, G. (2020). Protocol-based unscented Kalman filtering in the presence of stochastic uncertainties. IEEE Transactions on Automatic Control, 65(3), 1303–1309. https://doi.org/10.1109/TAC.2019.2929817
   Web of Science ®Google Scholar
• Liu, Q., Wang, Z., He, X., & Zhou, D. H. (2015). Event-based H∞ consensus control of multi-agent systems with relative output feedback: The finite-horizon case. IEEE Transactions on Automatic Control, 60(9), 2553–2558. https://doi.org/10.1109/TAC.2015.2394872
   Web of Science ®Google Scholar
• Liu, Q., Wang, Z., He, X., & Zhou, D. H. (2018). Event-triggered resilient filtering with measurement quantization and random sensor failures: Monotonicity and convergence. Automatica, 94, 458–464. https://doi.org/10.1016/j.automatica.2018.03.031
   Web of Science ®Google Scholar
• Liu, S., Wang, Z., Hu, J., & Wei, G. (2020). Protocol-based extended Kalman filtering with quantization effects: The Round-Robin case. International Journal of Robust and Nonlinear Control, 30(18), 7927–7946. https://doi.org/10.1002/rnc.5205.
   Web of Science ®Google Scholar
• Liu, D., Wang, Z., Liu, Y., & Alsaadi, F. E. (2020). Extended Kalman filtering subject to random transmission delays: Dealing with packet disorders. Information Fusion, 60, 80–86. https://doi.org/10.1016/j.inffus.2020.02.006
   Web of Science ®Google Scholar
• Liu, L., Wang, Y., Ma, L., Zhang, J., & Bo, Y. (2018). Robust finite-horizon filtering for nonlinear time-delay Markovian jump systems with weighted try-once-discard protocol. Systems Science and Control Engineering, 6(1), 180–194. https://doi.org/10.1080/21642583.2018.1474396
   Web of Science ®Google Scholar
• Liu, S., Wang, Z., Wei, G., & Li, M. (2020). Distributed set-membership filtering for multi-rate systems under the Round-Robin scheduling over sensor networks. IEEE Transactions on Cybernetics, 50(5), 1910–1920. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Liu, Y., Wang, Z., & Zhou, D. H. (2018). Quantised polynomial filtering for nonlinear systems with missing measurements. International Journal of Control, 91(10), 2250–2260. https://doi.org/10.1080/00207179.2017.1337933
   Web of Science ®Google Scholar
• Liu, S., Wei, G., Song, Y., & Liu, Y. (2016). Extended Kalman filtering for stochastic nonlinear systems with randomly occurring cyber attacks. Neurocomputing, 207, 708–716. https://doi.org/10.1016/j.neucom.2016.05.060
   Web of Science ®Google Scholar
• Long, Y., Park, J. H., & Ye, D. (2019). Frequency-dependent fault detection for networked systems under uniform quantization and try-once-discard protocol. International Journal of Robust and Nonlinear Control, 30(2), 787–803. https://doi.org/10.1002/rnc.v30.2
   Web of Science ®Google Scholar
• Ma, L., Wang, Z., Lam, H. K., & Kyriakoulis, N. (2016). Distributed event-based set-membership filtering for a class of nonlinear systems with sensor saturations over sensor networks. IEEE Transactions on Cybernetics, 47(11), 3772–3783. https://doi.org/10.1109/TCYB.2016.2582081
   PubMed Web of Science ®Google Scholar
• Mao, J., Ding, D., Dong, H., & Ge, X. (2020). Event-based distributed adaptive Kalman filtering with unknown covariance of process noises. IEEE Transactions on Systems, Man and Cybernetics: Systems. Advance online publication. https://doi.org/10.1109/TSMC.2019.2960050
   Web of Science ®Google Scholar
• Mao, J., Ding, D., Song, Y., Liu, Y., & Alsaadi, F. E. (2017). Event-based recursive filtering for time-delayed stochastic nonlinear systems with missing measurements. Signal Processing, 134, 158–165. https://doi.org/10.1016/j.sigpro.2016.12.004
   Web of Science ®Google Scholar
• Mao, J., Ding, D., Wei, G., & Liu, H. (2019). Networked recursive filtering for time-delayed nonlinear stochastic systems with uniform quantization under round-robin protocol. International Journal of Systems Science, 50(4), 871–884. https://doi.org/10.1080/00207721.2019.1586002
   Web of Science ®Google Scholar
• Mousavinejad, E., Yang, F., Han, Q.-L., Ge, X., & Vlacic, L. (2019). Distributed cyber attacks detection and recovery mechanism for vehicle platooning. IEEE Transactions on Intelligent Transportation Systems, 21(9), 3821–3834. https://doi.org/10.1109/TITS.6979
   Web of Science ®Google Scholar
• Muller, L. O., Caiazzo, A., & Blanco, P. J. (2019). Reduced-order unscented Kalman filter with observations in the frequency domain: Application to computational hemodynamics. IEEE Transactions on Biomedical Engineering, 66(5), 1269–1276. https://doi.org/10.1109/TBME.10
   PubMed Web of Science ®Google Scholar
• Park, C.-H., & Chang, J.-H. (2019). Shrinkage sinusoidal phase estimation based on spherical simplex unscented transform and bootstrap method. Transactions on Emerging Telecommunications Technologies, 30(7), e3592. https://doi.org/10.1002/ett.v30.7
   Web of Science ®Google Scholar
• Phogat, K. S., & Chang, D. (2020). Invariant extended Kalman filter on matrix Lie groups. Automatica, 114. Advance online publication. https://doi.org/10.1016/j.automatica.2020.108812
   Web of Science ®Google Scholar
• Qi, J., Sun, K., Wang, J., & Liu, H. (2018). Dynamic state estimation for multi-machine power system by unscented Kalman filter with enhanced numerical stability. IEEE Transactions on Smart Grid, 9(2), 1184–1196. https://doi.org/10.1109/TSG.2016.2580584
   Web of Science ®Google Scholar
• Schweppe, F. (1968). Recursive state estimation: Unknown but bounded errors and system inputs. IEEE Transactions on Automatic Control, 13(1), 102–107. https://doi.org/10.1109/TAC.1968.1098790
   Web of Science ®Google Scholar
• Shen, B., Wang, Z., & Hung, Y. S. (2010). Distributed consensus H∞ filtering in sensor networks with multiple missing measurements: The finite-horizon case. Automatica, 46(10), 1682–1688. https://doi.org/10.1016/j.automatica.2010.06.025
   Web of Science ®Google Scholar
• Shen, Y., Wang, Z., Shen, B., Alssadi, F. E., & Alssadi, F. E. (2020). Fusion estimation for multi-rate linear repetitive processes under weighted try-once-discard protocol. Information Fusion, 55, 281–291. https://doi.org/10.1016/j.inffus.2019.08.013
   Web of Science ®Google Scholar
• Shen, Y., Wang, Z., Shen, B., & Han, Q.-L. (2020). Recursive state estimation for networked multi-rate multi-sensor systems with distributed time-delays under the Round-Robin protocol. IEEE Transactions on Cybernetics. Advance online publication. https://doi.org/10.1109/TCYB.2020.3021350
   Web of Science ®Google Scholar
• Shen, B., Wang, Z., Wang, D., & Li, Q. (2020). State-saturated recursive filter design for stochastic time-varying nonlinear complex networks under deception attacks. IEEE Transactions on Neural Networks and Learning Systems, 31(10), 3788–3800. https://doi.org/10.1109/TNNLS.5962385
   PubMed Web of Science ®Google Scholar
• Shen, B., Wang, Z., Wang, D., & Liu, H. (2020). Distributed state-saturated recursive filtering over sensor networks under Round-Robin protocol. IEEE Transactions on Cybernetics, 50(8), 3605–3615. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Shen, Z., Yao, G., Xie, Q., & Jiang, F. (2020). Optimisation of delay tolerance in wireless sensor networks based on unscented Kalman filter estimation. International Journal of Sensor Networks, 33(2), 63–73. https://doi.org/10.1504/IJSNET.2020.107871
   Web of Science ®Google Scholar
• Singh, A. K. (2019). Exponentially fitted cubature kalman filter with application to oscillatory dynamical systems. IEEE Transactions on Circuits And Systems I-Regular Papers, 67(8), 2793–2752. https://doi.org/10.1109/TCSI.2020.2985867
   Web of Science ®Google Scholar
• Song, H., Ding, D., Dong, H., & Han, Q.-L. (2020). Distributed maximum correntropy filtering for stochastic nonlinear systems under deception attacks. IEEE Transactions on Cybernetics. Advance online publication. https://doi.org/10.1109/TCYB.2020.3016093
   Web of Science ®Google Scholar
• Song, J., Ding, D., Liu, H., & Wang, X. (2020). Non-fragile distributed state estimation over sensor networks subject to DoS attacks: The almost sure stability. International Journal of Systems Science, 51(6), 1119–1132. https://doi.org/10.1080/00207721.2020.1752843
   Web of Science ®Google Scholar
• Song, W., Wang, Z., Wang, J., & Shan, J. (2020). Particle filtering for a class of cyber-physical systems under Round-Robin protocol subject to randomly occurring deception attacks. Information Sciences, 544(12), 298–307. https://doi.org/10.1016/j.ins.2020.07.047.
   Web of Science ®Google Scholar
• Song, W., Wang, J., Zhao, S., & Shan, J. (2019). Event-triggered cooperative unscented Kalman filtering and its application in multi-UAV systems. Automatica, 105, 264–273. https://doi.org/10.1016/j.automatica.2019.03.029
   Web of Science ®Google Scholar
• Tan, H., Shen, B., Liu, Y., Alsaadi, F. E., & Ahmad, B. (2020). Event-triggered multi-rate fusion estimation for uncertain system with stochastic nonlinearities and colored measurement noises. Information Fusion, 36, 313–320. https://doi.org/10.1016/j.inffus.2016.12.003
   Web of Science ®Google Scholar
• Tan, H., Shen, B., Peng, K., & Liu, H. (2020). Robust recursive filtering for uncertain stochastic systems with amplify-and-forward relays. International Journal of Systems Science, 51(7), 1188–1199. https://doi.org/10.1080/00207721.2020.1754960
   Web of Science ®Google Scholar
• Tian, E., & Peng, C. (2020). Stability of networked control systems with stochastic protocols. IEEE Transactions on Cybernetics, 50(11), 4610–4618. https://doi.org/10.1109/TCYB.2020.2972384.
   PubMed Web of Science ®Google Scholar
• Wan, X., Wang, Z., Wu, M., & Liu, X. (2019). H∞ state estimation for discrete-time nonlinear singularly perturbed complex networks under the Round-Robin protocol. IEEE Transactions on Neural Networks and Learning Systems, 30(2), 415–426. https://doi.org/10.1109/TNNLS.2018.2839020
   PubMed Web of Science ®Google Scholar
• Wang, F., Wang, Z., Liang, J., & Liu, X. (2018). Resilient filtering for linear time-varying repetitive processes under uniform quantizations and Round-Robin protocols. IEEE Transactions on Circuits and Systems I: Regular Papers, 65(9), 2992–3004. https://doi.org/10.1109/TCSI.8919
   Web of Science ®Google Scholar
• Wang, D., Wang, Z., Shen, B., & Li, Q. (2019). H∞ finite-horizon filtering for complex networks with state saturations: The weighted try-once-discard protocol. International Journal of Robust and Nonlinear Control, 29(7), 2096–2111. https://doi.org/10.1002/rnc.4479
   Web of Science ®Google Scholar
• Wang, H., Xie, S., Zhou, B., & Wang, W. (2020). Non-fragile robust H∞ infinity filtering of Takagi-Sugeno fuzzy networked control systems with sensor failures. Sensors, 20(1). Advance online publication. https://doi.org/10.3390/s20010027
   Web of Science ®Google Scholar
• Wang, X., & Yaz, E. E. (2019). Second-order fault tolerant extended Kalman filter for discrete time nonlinear systems. IEEE Transactions on Automatic Control, 64(12), 5086–5093. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Wei, G., Liu, L., Wang, L., & Ding, D. (2020). Event-triggered control for discrete-time systems with unknown nonlinearities: An interval observer-based approach. International Journal of Systems Science, 51(6), 1019–1031. https://doi.org/10.1080/00207721.2020.1746441
   Web of Science ®Google Scholar
• Wen, C., Wang, Z., Hu, J., & Liu, Q. (2018). Recursive filtering for state-saturated systems with randomly occurring nonlinearities and missing measurements. International Journal of Robust and Nonlinear Control, 28(5), 1715–1727. https://doi.org/10.1002/rnc.v28.5
   Web of Science ®Google Scholar
• Wen, C., Wang, Z., Liu, Q., & Alsaadi, F. E. (2018). Recursive distributed filtering for a class of state-saturated systems with fading measurements and quantization effects. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(6), 930–941. http://dx.doi.org/10.1109/TSMC.2016.2629464
   Web of Science ®Google Scholar
• Witsenhausen, H. (1968). Sets of possible states of linear systems given perturbed observations. IEEE Transactions on Automatic Control, 13(5), 556–558. https://doi.org/10.1109/TAC.1968.1098995
   Web of Science ®Google Scholar
• Wu, C., Magana, M. E., & Cotilla-Sanchez, E. (2019). Dynamic frequency and amplitude estimation for three-phase unbalanced power systems using the unscented Kalman filter. IEEE Transactions on Instrumentation and Measurement, 68(9), 3387–3395. https://doi.org/10.1109/TIM.19
   Web of Science ®Google Scholar
• Xia, Y., Yu, D., Li, L., Yang, H., & Xie, W. (2018). Data-driven filtering for nonlinear systems with bounded noises and quantized measurements. IEEE Transactions on Circuits and Systems I: Regular Papers, 65(10), 3404–3413. https://doi.org/10.1109/TCSI.8919
   Web of Science ®Google Scholar
• Xie, W, & Zhu, Q. (2020). Self-triggered state-feedback control for stochastic nonlinear systems with Markovian switching. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(9), 3200–3209. https://doi.org/10.1109/TSMC.6221021
   Web of Science ®Google Scholar
• Yan, H., Xu, X., Zhang, H., & Yang, F. (2017). Distributed event-triggered H∞ state estimation for T-S fuzzy systems over filtering networks. Journal of the Franklin Institute-Engineering and Applied Mathematics, 354(9), 3760–3779. https://doi.org/10.1016/j.jfranklin.2016.05.019
   Web of Science ®Google Scholar
• Yan, H., Zhang, H., Yang, F., Huang, C., & Chen, S. (2018). Distributed H∞ filtering for switched repeated scalar nonlinear systems with randomly occurred sensor nonlinearities and asynchronous switching. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 48(12), 2263–2270. https://doi.org/10.1109/TSMC.2017.2754495
   Web of Science ®Google Scholar
• Yang, F., Xia, N., & Han, Q.-L. (2017). Event-based networked islanding detection for distributed solar PV generation systems. IEEE Transactions on Industrial Informatics, 13(1), 322–329. https://doi.org/10.1109/TII.2016.2607999
   Web of Science ®Google Scholar
• Zames, G. (1981). Feedback and optimal sensitivity: Model reference transformation, multiplicative seminorms and approximative inverses. IEEE Transactions on Automatic Control, 26(2), 301–320. https://doi.org/10.1109/TAC.1981.1102603
   Web of Science ®Google Scholar
• Zarei, J., Kowsari, E., & Razavi-Far, R. (2019). Induction motors fault detection using square-root transformed cubature quadrature Kalman filter. IEEE Transactions on Energy Conversion, 34(2), 870–877. https://doi.org/10.1109/TEC.60
   Web of Science ®Google Scholar
• Zarei, J., & Shokri, E. (2015). Convergence analysis of non-linear filtering based on cubature Kalman filter. IET Science Measurement and Technology, 9(3), 294–305. https://doi.org/10.1049/iet-smt.2014.0056
   Web of Science ®Google Scholar
• Zhang, X.-M., Han, Q.-L., Ge, X., Ding, D., Ding, L., Yue, D., & Peng, C. (2020). Networked control systems: A survey of trends and techniques. IEEE/CAA Journal of Automatica Sinica, 7(1), 1–17. https://doi.org/10.1109/JAS.6570654
   Google Scholar
• Zhang, X.-M., Han, Q.-L., Ge, X., & Ding, L. (2020). Resilient control design based on a sampled-data model for a class of networked control systems under denial-of-service attacks. IEEE Transactions on Cybernetics, 50(8), 3616–3626. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Zhang, C.-K., He, Y., Jiang, L., Wu, M., & Zeng, H.-B. (2016). Summation inequalities to bounded real lemmas of discrete-time systems with time-varying delay. IEEE Transactions on Automatic Control, 62(5), 2582–2588. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Zhang, H., Wang, Z., Yan, H, Yang, F., & Zhou, X. (2019). Adaptive event-triggered transmission scheme and H∞ filtering co-design over a filtering network with switching topology. IEEE Transactions on Cybernetics, 49(12), 4296–4307. https://doi.org/10.1109/TCYB.6221036
   PubMed Web of Science ®Google Scholar
• Zhang, W.-A., Yu, L., & Feng, G. (2011). Optimal linear estimation for networked systems with communication constraints. IEEE Transactions on Circuits and Systems I-Regular Papers, 47(9), 1992–2000. https://doi.org/10.1016/j.automatica.2011.05.020
   Google Scholar
• Zhang, S., Zhao, J., Zhao, Y., & Li, G. (2016). Gain-constrained extended Kalman filtering with stochastic nonlinearities and randomly occurring measurement delays. Circuits, Systems, and Signal Processing, 35, 3957–3980. https://doi.org/10.1007/s00034-016-0244-4
   Web of Science ®Google Scholar
• Zhao, J. (2020). Dynamic state estimation with model uncertainties using H∞ extended Kalman filter. IEEE Transactions on Power Systems, 33(1), 1099–1100. https://doi.org/10.1109/TPWRS.2017.2688131
   Web of Science ®Google Scholar
• Zhao, J., & Mili, L. (2019). A decentralized H∞ unscented Kalman filter for dynamic state estimation against uncertainties. IEEE Transactions on Smart Grid, 10(5), 4870–4880. https://doi.org/10.1109/TSG.5165411
   Web of Science ®Google Scholar
• Zhao, D., Wang, Z., Wei, G., & Han, Q.-L. (2020). A dynamic event-triggered approach to observer-based PID security control subject to deception attacks. Automatica, 120, 109128. https://doi.org/10.1016/j.automatica.2020.109128.
   Web of Science ®Google Scholar
• Zhao, Z., Wang, Z., Zou, L., & Guo, J. (2020). Set-membership filtering for time-varying complex networks with uniform quantisations over randomly delayed redundant channels. International Journal of Systems Science. Advance online publication. https://doi.org/10.1080/00207721.2020.1814898
   Web of Science ®Google Scholar
• Zou, L., Wang, Z., & Gao, H. (2019a). Observer-based H-infinity control of networked systems with stochastic communication protocol: The finite-horizon case. Automatica, 63, 366–373. https://doi.org/10.1016/j.automatica.2015.10.045
   Web of Science ®Google Scholar
• Zou, L., Wang, Z., & Gao, H. (2019b). Set-membership filtering for time-varying systems with mixed time-delays under round-robin and weighted try-once-discard protocols. Automatica, 74, 341–348. https://doi.org/10.1016/j.automatica.2016.07.025
   Web of Science ®Google Scholar
• Zou, L., Wang, Z., Han, Q.-L., & Zhou, D. H. (2019). Recursive filtering for time-varying systems with random access protocol. IEEE Transactions on Automatic Control, 64(2), 720–727. https://doi.org/10.1109/TAC.2018.2833154
   Web of Science ®Google Scholar
• Zou, L., Wang, Z., Han, Q.-L., & Zhou, D. H. (2020a). Full information estimation for linear time-varying systems subject to Round-Robin protocol: A recursive filter approach. IEEE Transactions on Systems, Man, and Cybernetics:Systems. Advance online publication. https://doi.org/10.1109/TSMC.2019.2907620
   Web of Science ®Google Scholar
• Zou, L., Wang, Z., Han, Q.-L., & Zhou, D. H. (2020b). Moving horizon estimation for networked time-delay systems under Round-Robin protocol. IEEE Transactions on Automatic Control, 64(12), 5191–5198. https://doi.org/10.1109/TAC.9
   Web of Science ®Google Scholar
• Zou, L., Wang, Z., Hu, J., & Gao, H. (2017). On H∞ finite-horizon filtering under stochastic protocol: Dealing with high-rate communication networks. IEEE Transactions on Automatic Control, 62(9), 4884–4890. https://doi.org/10.1109/TAC.2017.2691310
   Web of Science ®Google Scholar