Nội dung được dịch bởi AI, chỉ mang tính chất tham khảo
Đồng bộ hóa an toàn và nhận diện cho các mạng phức phân số với nhiều kết nối trọng số dưới các cuộc tấn công từ chối dịch vụ
Tóm tắt
Bài báo này đề cập đến vấn đề đồng bộ hóa an toàn và nhận diện cấu trúc cho các mạng phức phân số (FCNs) với nhiều kết nối trọng số dưới các cuộc tấn công từ chối dịch vụ (DoS), trong đó các cuộc tấn công DoS diễn ra trong các kênh từ bộ điều khiển đến bộ chấp hành. Đầu tiên, một bộ theo dõi cấu trúc thích nghi được thiết kế nhằm thực hiện mục tiêu đồng bộ hóa an toàn và nhận diện cấu trúc. Thứ hai, bằng cách sử dụng lý thuyết ổn định Lyapunov và nguyên lý so sánh, các điều kiện đồng bộ hóa an toàn được đạt được. Dưới sự giám sát của bộ theo dõi đã thiết kế, việc nhận diện cấu trúc cũng có thể được thực hiện. Cuối cùng, một mô phỏng số được cung cấp để minh chứng cho tính hiệu quả của kế hoạch đề xuất và tính hợp lệ của các kết quả lý thuyết.
Từ khóa
#đồng bộ hóa an toàn #nhận diện cấu trúc #mạng phức phân số #tấn công từ chối dịch vụ #kết nối trọng sốTài liệu tham khảo
An XL, Zhang L, Li YZ, Zhang JG (2014) Synchronization analysis of complex networks with multi-weights and its application in public traffic network. Physica A: Stat Mech Appl 412:149–156
An XL, Li YZ, Zhang L, Zhang JG, Ma CX (2015) The research on multi-links complex networks and its application in urban public traffic. ICIC Express Lett Part B Appl Int J Res Surv 6:1613–1618
Chen X, Zhang J, Ma T (2016) Parameter estimation and topology identification of uncertain general fractional-order complex dynamical networks with time delay. IEEE/CAA J Autom Sin 9(3):295–303
Chen B, Ho DWC, Hu G, Yu L (2018) Secure fusion estimation for bandwidth constrained cyber-physical systems under replay attacks. IEEE Trans Cybern 48(6):1862–1876
Cortes J (2008) Discontinuous dynamical systems. IEEE Control Syst Magn 28(3):36–73
DeLellis P, di Bernardo M, Russo G (2011) On QUAD. Lipschitz, and contracting vector fields for consensus and synchronization of networks, IEEE Transactions on Circuits and Systems I. 58(3):576–583
Ding D, Wang Z, Ho DWC, Wei G (2017) Observer-based eventtriggering consensus control for multiagent systems with lossy sensors and cyber-attacks. IEEE Trans Cybern 47(8):1936–1947
Ding D, Wang Z, Han QL, Wei G (2018) Security control for discrete-time stochastic nonlinear systems subject to deception attacks. IEEE Trans Syst Man Cybern Syst 48(99):779–789
Fan YH, Mei J, Liu HM, Fan YL, Liu FX, Zhang YJ (2020) Fast synchronization of complex networks via a periodically intermittent sliding mode control. Neural Process Lett 51:1331–1352
Gu Y, Yu Y, Wang H (2017) Synchronization-based parameter estimation of fractional-order neural networks. Phys A 483:351–361
Li RH, Wu HQ, Cao JD (2022) Impulsive exponential synchronization of fractional-order complex dynamical networks with derivative couplings via feedback control based on discrete time state observations. Acta Mathematica Scientia. 42B(2):737–754
Liu D, Ye D (2020) Pinning-observer-based secure synchronization control for complex dynamical networks subject to DoS attacks. IEEE Trans Circ Syst 67(12):5394–5404
Liu H, Li Y, Li ZY, Lu JA (2021) Topology identification of multilink complex dynamical networks via adaptive observers incorporating chaotic exosignals. IEEE Trans Cybern 99:267–281
Lu AY, Yang GH (2018) Input-to-state stabilizing control for cyberphysical systems with multiple transmission channels under denial of service. IEEE Trans Autom Control 63(6):1813–1820
Mannel A, Norelys, Javier A (2015) Using general quadratic Lyapunov functions to prove Lyapunov uniform stability for fractional order systems. Commun Nonlinear Sci Numer Simul 22(3):650–659
Mei J, Jiang M, Wang J (2013) Finite-time structure identification and synchronization of drive-response systems with uncertain parameter. Commun Nonlinear Sci Numer Simul 18(4):999–1015
Mirollo R, Strogatz S (1990) Synchronizayion of pulse-coupled biological oscillators. SIAM J Appl Math 50:1645–1662
Papadimitratos P, Fortelle ADL, Evenssen K, Brignolo R, Cosenza S (2009) Vehicular communication systems: enabling technologies, applications, and future outlook on intelligent transportation. Commun Magz IEEE 47(11):84–95
Peng X, Wu HQ (2020) Non-fragile robust finite-time stabilization and H infinity performance analysis for fractional-order delayed neural networks with discontinuous activations under the asynchronous switching. Neural Comput Appl 32(8):4045–4071
Peng X, Wu HQ, Cao JD (2019) Global nonfragile synchronization in finite time for fractional-order discontinuous neural networks with nonlinear growth activations. IEEE Trans Neural Netw Learn Syst 30(7):2123–2137
Podlubny I (1999) Fractional Differential Equations. Academic, San Diego, CA
Saeedian M, Khalighi M, Azimi-Tafreshi N, Jafari GR, Ausloos M (2017) Memory effects on epidemic evolution: the susceptible-infected-recovered epidemic model. Phys Rev E 95:022409
Shisheh Foroush H, Martnez S (2016) On triggering control of single-input linear systems under pulse-width modulated DoS signals. SIAM J Control Optim 54(6):3084–3105
Si G, Sun Z, Zhang H, Zhang Y (2012) Parameter estimation and topology identification of uncertain fractional order complex networks. Commun Nonlinear Sci Numer Simul 17(12):5158–5171
Strogatz SH (2001) Exploring complex networks. Nature 410:268–276
Wang XH, Wu HQ, Cao JD (2020) Global leader-following consensus in finite time for fractional-order multiagent systems with discontinuous inherent dynamics subject to nonlinear growth. Nonlinear Anal-Hybrid Syst 37:100888
Wang LH, Mo ZK, Han QL (2020) Secure impulsive Synchronization in lipschitz-type multi-agent systems subject to deception attacks. IEEE J Autom Sin 7(5):1326–1334
Wu X (2008) Synchronization-based topology identification of weighted general complex dynamical networks with time-varying coupling delay. Phys A 387(4):997–1008
Wu XJ, Lu HT (2010) Outer synchronization between two different fractional-order general complex dynamical networks. Chin Phys B 19(7):129–140
Wu HY, Wang L, Zhao LH, Wang JL (2012) Topology identification of coupled neural networks with multiple weights. Neurocomputing 457(2):254–264
Xu LZ (2010) Applied inequalities, Shandong Science and Technology Press
Yu D, Righero M, Kocarev L (2006) Estinating topology of networks. Phys Rev Lett 97:31–34
Yu J, Cheng H, Jiang HJ (2012) \(\alpha \)-stability and \(\alpha \)-synchronization for fractional-order neural networks. Neural Netw 35:82–87
Zhang YQ, Wu HQ, Cao JD (2020) Group consensus in finite time for fractional multiagent systems with discontinuous inherent dynamics subject to Holder growth. IEEE Trans Cybern. https://doi.org/10.1109/TCYB.2020.3023704
Zhang TY, Ye D (2020) Distributed secure control against denial-of-service attacks in cyber-physical systems based on K-connected communication topology. IEEE Trans Cybern 50(7):3094–3103
Zhang XM, Han QL, Ge X, Ding L (2020) Resilient control design based on a sampled-date model for a class of networked control systems under denial-of-service attacks. IEEE Trans Cybern 50(8):3616–3626
Zhang YQ, Wu HQ, Cao JD (2021) Global Mittag–Leffler consensus for fractional singularly perturbed multiagent systems with discontinuous inherent dynamics via event-triggered control strategy. J Frankl Inst 358(3):2086–2114
Zhao J, Aziz-Alaoui MA, Bertelle C, Corson N (2016) Sinusoidal disturbance induced topology identification of Hindmarsh–Rose neural networks. Sci Chin Inf Sci 59(11):112205
Zhao W, Wu HQ (2018) Fixed-time synchronization of semi-Markovian jumping neural networks with time-verying delays. Adv Differ Equ 2018 (1):213
Zheng Y, Wu XQ, Fan ZY, Wang W (2022) Identifying topology and system parameters of fractional-order complex dynamical networks. Appl Math Comput 414:126666
Zhu S, Zhou J, Chen G, Lu JA (2019) A new method for topology identification of complex dynamical networks. IEEE Trans Cybern 51(4):2224–2231