zbMATH — the first resource for mathematics

Distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks. (English) Zbl 1357.93096
Summary: This paper is concerned with the distributed recursive filtering problem for a class of discrete time-delayed stochastic systems subject to both uniform quantization and deception attack effects on the measurement outputs. The target plant is disturbed by the multiplicative as well as additive white noises. A novel distributed filter is designed where the available innovations are from not only the individual sensor but also its neighboring ones according to the given topology. Attention is focused on the design of a distributed recursive filter such that, in the simultaneous presence of time-delays, deception attacks and uniform quantization effects, an upper bound for the filtering error covariance is guaranteed and subsequently minimized by properly designing the filter parameters via a gradient-based method at each sampling instant. Furthermore, by utilizing the mathematical induction, a sufficient condition is established to ensure the asymptotic boundedness of the sequence of the error covariance. Finally, a simulation example is utilized to illustrate the usefulness of the proposed design scheme of distributed filters.

93E11 Filtering in stochastic control theory
93E10 Estimation and detection in stochastic control theory
93C55 Discrete-time control/observation systems
93E03 Stochastic systems in control theory (general)
Full Text: DOI
[1] Amin, S.; Schwartz, G. A.; Shankar Sastry, S., Security of interdependent and identical networked control systems, Automatica, 49, 1, 186-192, (2013) · Zbl 1257.93012
[2] Basin, M.; Alcorta-Garcia, A.; Rodriguez-Gonzalez, J., Optimal filtering for linear systems with state and observation delays, International Journal of Robust and Nonlinear Control, 15, 17, 859-871, (2005) · Zbl 1086.93058
[3] Basin, M.; Martinez-Zuniga, R., Optimal linear filtering over observations with multiple delays, International Journal of Robust and Nonlinear Control, 14, 8, 685-696, (2004) · Zbl 1057.93055
[4] Brockett, R. W.; Liberzon, D., Quantized feedback stabilization of linear systems, IEEE Transactions on Automatic Control, 55, 7, 1279-1289, (2000) · Zbl 0988.93069
[5] Chen, H.; Liang, J.; Wang, Z., Pinning controllability of autonomous Boolean control networks, Science China Information Sciences, 59, 7, (2016), Art. No. 070107
[6] Ding, D.; Wang, Z.; Ho, D. W.C.; Wei, G., Observer-based event-triggering consensus control for multi-agent systems with lossy sensors and cyber attacks, IEEE Transactions on Cybernetics, (2016)
[7] Ding, D.; Wei, G.; Zhang, S.; Liu, Y.; Alsaadi, F. E., On scheduling of deception attacks for discrete-time networked systems equipped with attack detectors, Neurocomputing, 219, 99-106, (2017)
[8] Dong, H.; Wang, Z.; Alsaadi, F. E.; Ahmad, B., Event-triggered robust distributed state estimation for sensor networks with state-dependent noises, International Journal of General Systems, 44, 2, 254-266, (2015) · Zbl 1309.93100
[9] Dong, H.; Wang, Z.; Gao, H., Distributed \(H_\infty\) filtering for a class of Markovian jump nonlinear time-delay systems over lossy sensor networks, IEEE Transactions on Industrial Electronics, 60, 10, 4665-4672, (2013)
[10] Dong, H.; Wang, Z.; Shen, B.; Ding, D., Variance-constrained \(H_\infty\) control for a class of nonlinear stochastic discrete time-varying systems: the event-triggered design, Automatica, 72, 28-36, (2016) · Zbl 1344.93089
[11] Fawzi, H.; Tabuada, P.; Diggavi, S., Secure estimation and control for cyber-physical systems under adversarial attacks, IEEE Transactions on Automatic Control, 59, 6, 1454-1467, (2014) · Zbl 1360.93201
[12] Gandhi, M. A.; Mili, L., Robust Kalman filter based on a generalized maximum-likelihood-type estimator, IEEE Transactions on Automatic Control, 58, 5, 2509-2520, (2010) · Zbl 1392.94216
[13] Gershon, E.; Shaked, U.; Yaesh, I., \(\mathcal{H}_\infty\) control and filtering of discrete-time stochastic systems with multiplicative noise, Automatica, 37, 3, 409-417, (2001) · Zbl 0989.93030
[14] Hou, N.; Dong, H.; Wang, Z.; Ren, W.; Alsaadi, F. E., Non-fragile state estimation for discrete Markovian jumping neural networks, Neurocomputing, 179, 238-245, (2016)
[15] Hu, J.; Chen, D.; Du, J., State estimation for a class of discrete nonlinear systems with randomly occurring uncertainties and distributed sensor delays, International Journal of General Systems, 43, 3-4, 387-401, (2014) · Zbl 1302.93201
[16] Hu, J.; Liu, S.; Ji, D.; Li, S., On co-design of filter and fault estimator against randomly occurring nonlinearities and randomly occurring deception attacks, International Journal of General Systems, 45, 5, 619-632, (2016) · Zbl 1342.93112
[17] Kluge, S.; Reif, K.; Brokate, M., Stochastic stability of the extended Kalman filter with intermittent observations, IEEE Transactions on Automatic Control, 55, 2, 514-518, (2010) · Zbl 1368.93717
[18] Kong, S.; Saif, M.; Zhang, H., Optimal filtering for-stochastic continuous-time systems with multiple delayed measurements, IEEE Transactions on Automatic Control, 58, 7, 1872-1877, (2013) · Zbl 1369.93634
[19] Li, Q.; Shen, B.; Liang, J.; Shu, H., Event-triggered synchronization control for complex networks with uncertain inner coupling, International Journal of General Systems, 44, 2, 212-225, (2015) · Zbl 1309.93101
[20] Li, Q.; Shen, B.; Liu, Y.; Alsaadi, F. E., Event-triggered \(\mathcal{H}_\infty\) state estimation for discrete-time stochastic genetic regulatory networks with Markovian jumping parameters and time-varying delays, Neurocomputing, 174, 912-920, (2016)
[21] Long, M.; Wu, C.-H.; Hung, J. Y., Denial of service attacks on network-based control systems: impact and mitigation, IEEE Transactions on Industrial Informatics, 1, 2, 85-96, (2005)
[22] Lu, L.-Z., Some new bounds for singular values and eigenvalues of matrix products, Annals of Operations Research, 98, 1-4, 141-148, (2000) · Zbl 0979.15017
[23] Lu, X.; Xie, L.; Zhang, H.; Wang, W., Robust Kalman filtering for discrete-time systems with measurement delay, IEEE Transactions on Circuits and Systems-II, 54, 6, 522-526, (2007)
[24] Marano, S.; Matta, V.; Tong, L., Distributed detection in the presence of Byzantine attacks, IEEE Transactions on Signal Processing, 57, 1, 16-29, (2009) · Zbl 1391.94534
[25] Olfati-Saber, R. (2007). Distributed Kalman filtering for sensor networks. In Proceedings of the 46th IEEE conference on decision and control, New Orleans, LA, (pp. 5492-5498).
[26] Pang, Z.-H.; Liu, G.-P., Design and implementation of secure networked predictive control systems under deception attacks, IEEE Transactions on Control Systems Technology, 20, 5, 1334-1342, (2012)
[27] Reif, K.; G√ľnther, S.; Yaz, E.; Unbehauen, R., Stochastic stability of the discrete-time extended Kalman filter, IEEE Transactions on Automatic Control, 44, 4, 714-728, (1999) · Zbl 0967.93090
[28] Rojas, A. J.; Lotero, F., Signal-to-noise ratio limited output feedback control subject to channel input quantization, IEEE Transactions on Automatic Control, 60, 2, 475-479, (2015) · Zbl 1360.93266
[29] Simon, D.; Chia, T., Kalman filtering with state equality constraints, IEEE Transactions on Aerospace and Electronic Systems, 38, 1, 128-136, (2002)
[30] Theodor, Y.; Shaked, U., Robust discrete-time minimum-variance filtering, IEEE Transactions on Signal Processing, 44, 2, 181-189, (1996)
[31] Vempaty, A.; Ozdemir, O.; Agrawal, K.; Chen, H.; Varshney, P. K., Localization in wireless sensor networks: byzantines and mitigation techniques, IEEE Transactions on Signal Processing, 61, 6, 1495-1508, (2013) · Zbl 1393.90043
[32] Vempaty, A.; Tong, L.; Varshney, P., Distributed inference with Byzantine data: state-of-the-art review on data falsification attacks, IEEE Signal Processing Magazine, 30, 5, 65-75, (2013)
[33] Yang, F.; Dong, H.; Wang, Z.; Ren, W.; Alsaadi, F. E., A new approach to non-fragile state estimation for continuous neural networks with time-delays, Neurocomputing, 197, 205-211, (2016)
[34] Yang, H.; Wang, Z.; Shu, H.; Alsaadi, F. E.; Hayat, T., Almost sure \(H_\infty\) sliding mode control for nonlinear stochastic systems with Markovian switching and time-delays, Neurocomputing, 175, 392-400, (2016)
[35] Yu, Y.; Dong, H.; Wang, Z.; Ren, W.; Alsaadi, F. E., Design of non-fragile state estimators for discrete time-delayed neural networks with parameter uncertainties, Neurocomputing, 182, 18-24, (2016)
[36] Zeng, N.; Wang, Z.; Zhang, H., Inferring nonlinear lateral flow immunoassay state-space models via an unscented Kalman filter, Science China Information Sciences, 59, 11, (2016), Art. No. 112204
[37] Zhang, J.; Blum, R. S.; Lu, X.; Conus, D., Asymptotically optimum distributed estimation in the presence of attacks, IEEE Transactions on Signal Processing, 63, 5, 1086-1101, (2015) · Zbl 1394.94684
[38] Zhu, M.; Martinez, S., On the performance analysis of resilient networked control systems under replay attacks, IEEE Transactions on Automatic Control, 59, 3, (2014) · Zbl 1360.93459
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.