Abstract
In this paper, a non-fragile fuzzy control method is proposed to solve the common parameter uncertainty phenomenon in complex networks and the security threat caused by network attacks. A T-S fuzzy discrete complex network model following piecewise homogeneous Markov process is constructed on the basis of the study of Markov jump models with aligned times. The combined effects of spoofing attacks and denial of service attacks are considered when processing controller signals. By analyzing the Lyapunov-Krasovskii functional with dual modal correlation, we establish sufficient conditions for finite time boundedness of the synchronization error system, and then verify the controller’s effectiveness in the attacked Lorenz chaotic system.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jin, M., Chao, C.: Distributed adaptive security consensus control for a class of multi-agent systems under network decay and intermittent attacks. Inf. Sci. Int. J. 547(1) (2021). https://doi.org/10.1016/j.ins.2020.08.013
Sakthivel, R., Kwon, O.-M., Park, M.J., Choi, S.-G., Sakthivel, R.: Robust asynchronous filtering for discrete-time t-s fuzzy complex dynamical networks against deception attacks. IEEE Trans. Fuzzy Syst. 30(8), 3257–3269 (2022). https://doi.org/10.1109/TFUZZ.2021.3111453
Liu, J., Yin, T., Cao, J., Yue, D., Karimi, H.R.: Security control for t-s fuzzy systems with adaptive event-triggered mechanism and multiple cyber-attacks. IEEE Trans. Syst. Man Cybern. Syst. PP(99), 1–11 (2020). https://doi.org/10.1109/TSMC.2019.2963143
Yuan, H., Xia, Y., Yang, H.: Resilient state estimation of cyber-physical system with multichannel transmission under dos attack. IEEE Trans. Syst. Man Cybern. Syst. PP(99), 1–12 (2020). https://doi.org/10.1109/TSMC.2020.2964586
Ding, D., Wang, Z., Han, Q.L., Wei, G.: Security control for discrete-time stochastic nonlinear systems subject to deception attacks. IEEE Trans. Syst. Man Cybern. Syst. (2016). https://doi.org/10.1109/TSMC.2016.2616544
Zhao, N., Shi, P., Xing, W., Lim, C.P.: Resilient adaptive event-triggered fuzzy tracking control and filtering for nonlinear networked systems under denial-of-service attacks. IEEE Trans. Fuzzy Syst. 30(8), 3191–3201 (2022). https://doi.org/10.1109/TFUZZ.2021.3106674
Song, J., Shan, J.: Particle filtering for a class of cyber-physical systems under round-robin protocol subject to randomly occurring deception attacks. Inf. Sci. Int. J. 544(1) (2021). https://doi.org/10.1016/j.ins.2020.07.047
Zhang, D., Liu, L., Feng, G.: Consensus of heterogeneous linear multiagent systems subject to aperiodic sampled-data and DoS attack. IEEE Trans. Cybern. PP(99), 1–11 (2018). https://doi.org/10.1109/TCYB.2018.2806387
Peng, H., Zhang, Y., Lei, J., Lin, M.: \(H \infty \) asynchronous synchronisation control for Markovian coupled delayed neural networks with missing information. Int. J. Syst. Sci. 53 (2022). https://doi.org/10.1080/00207721.2021.1998719
Dong, S., Liu, M.: Adaptive fuzzy asynchronous control for nonhomogeneous Markov jump power systems under hybrid attacks. IEEE Trans. Fuzzy Syst. 31(3), 1009–1019 (2023). https://doi.org/10.1109/TFUZZ.2022.3193805
Deng, Y., Mo, Z., Lu, H.: Robust \(H \infty \) state estimation for a class of complex networks with dynamic event-triggered scheme against hybrid attacks (2021). https://doi.org/10.1088/1674-1056/ac0ee9
Xue, M., Yan, H., Zhang, H., Li, Z., Chen, S., Chen, C.: Event-triggered guaranteed cost controller design for t-s fuzzy Markovian jump systems with partly unknown transition probabilities. IEEE Trans. Fuzzy Syst. 29(5), 1052–1064 (2021). https://doi.org/10.1109/TFUZZ.2020.2968866
Zhang, L.: \(H \infty \) estimation for discrete-time piecewise homogeneous Markov jump linear systems. Automatica 45(11), 2570–2576 (2009). https://doi.org/10.1016/j.automatica.2009.07.004
Hou, N., Dong, H., Wang, Z., Ren, W., Alsaadi, F.E.: Non-fragile state estimation for discrete Markovian jumping neural networks. Neurocomputing 179(C), 238–245 (2016). https://doi.org/10.1016/j.neucom.2015.11.089
Shen, H., Hu, X., Wang, J., Cao, J., Qian, W.: Non-fragile \(H \infty \) synchronization for Markov jump singularly perturbed coupled neural networks subject to double-layer switching regulation. IEEE Trans. Neural Netw. Learn. Syst. 34(5), 2682–2692 (2023). https://doi.org/10.1109/TNNLS.2021.3107607
Qiu, Y., Hua, C., Wang, Y.: Nonfragile sampled-data control of t-s fuzzy systems with time delay. IEEE Trans. Fuzzy Syst. 30(8), 3202–3210 (2022). https://doi.org/10.1109/TFUZZ.2021.3107748
Adhira, B., Nagamani, G., Dafik, D.: Non-fragile extended dissipative synchronization control of delayed uncertain discrete-time neural networks. Commun. Nonlinear Sci. Numer. Simul. 116, 106820 (2022). https://doi.org/10.1016/j.cnsns.2022.106820
Fan, S., Yan, H., Zhang, H., Shen, H., Shi, K.: Dynamic event-based nonfragile dissipative state estimation for quantized complex networks with fading measurements and its application. IEEE Trans. Circ. Syst. I. Regul. Pap. Publ. IEEE Circ. Syst. Soc. (2), 68 (2021). https://doi.org/10.1109/TCSI.2020.3036626
Liu, J., Yin, T., Cao, J., Yue, D., Karimi, H.R.: Security control for t-s fuzzy systems with adaptive event-triggered mechanism and multiple cyber-attacks. IEEE Trans. Syst. Man Cybern. Syst. PP(99), 1–11 (2020). https://doi.org/10.1109/TSMC.2019.2963143
Nesheli, M.M., Ceder, A.A., Gonzalez, V.A.: Real-time public transport operational tactics using synchronized transfers to eliminate vehicle bunching 3220–3229 (2016). https://doi.org/10.1109/TITS.2016.2542268
Sang, H., Zhao, J.: Finite-time \(H \infty \) estimator design for switched discrete time delayed neural networks with event-triggered strategy. IEEE Trans. Cybern. PP(99), 1–13 (2020). https://doi.org/10.1109/TCYB.2020.2992518
Park, P., Ko, J.W., Jeong, C.: Reciprocally convex approach to stability of systems with time-varying delays. Automatica (2011). https://doi.org/10.1016/j.automatica.2010.10.014
Wang, J., Xia, J., Shen, H., Xing, M., Park, J.H.: \(H \infty \) synchronization for fuzzy Markov jump chaotic systems with piecewise-constant transition probabilities subject to PDT switching rule. IEEE Trans. Fuzzy Syst. 1–1 (2020). https://doi.org/10.1109/TFUZZ.2020.3012761
Acknowledgements
This work was supported by National Natural Science Foundation of China under Grant 62263005, Guangxi Natural Science Foundation under Grant 2020GXNSFDA238029, Laboratory of AI and Information Processing (Hechi University), Education Department of Guangxi Zhuang Autonomous Region under Grant 2022GXZDSY004, Innovation Project of Guangxi Graduate Education YCSW2023298, Innovation Project of GUET Graduate Education under Grant 2023YCXS124.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Wu, X., Zhang, B., Zhang, Y., Zhang, Y. (2023). Finite-Time H \(\infty \) Synchronization Control of Piecewise Homogeneous Markov Jumping T-S Fuzzy Discrete Complex Networks Subject to Hybrid Attacks and Uncertainty. In: Jia, Y., Zhang, W., Fu, Y., Wang, J. (eds) Proceedings of 2023 Chinese Intelligent Systems Conference. CISC 2023. Lecture Notes in Electrical Engineering, vol 1089. Springer, Singapore. https://doi.org/10.1007/978-981-99-6847-3_24
Download citation
DOI: https://doi.org/10.1007/978-981-99-6847-3_24
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6846-6
Online ISBN: 978-981-99-6847-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)