Event-triggered fast finite-time adaptive neural prescribed tracking control for non-affine stochastic nonlinear systems with deception attacks

References

• Bai, W., Liu, P. X. P., & Wang, H. Q. (2022). Adaptive fixed-time fuzzy control for nonlinear systems with actuator faults. International Journal of Adaptive Control and Signal Processing, 36(4), 762–784. https://doi.org/10.1002/acs.3369
   Web of Science ®Google Scholar
• Bhat, S. P., & Bernstein, D. S. (1998). Continuous finite-time stabilization of the translational and rotational double integrators. Transactions on Automatic Control, 43(5), 678–682. https://doi.org/10.1109/9.668834
   Web of Science ®Google Scholar
• Bhat, S. P., & Bernstein, D. S. (2000). Finite-time stability of continuous autonomous systems. SIAM Journal on Control and Optimizaiton, 38(3), 751–766. https://doi.org/10.1137/S0363012997321358
   Web of Science ®Google Scholar
• Chen, M., Wang, H. Q., & Liu, X. P. (2021a). Adaptive fuzzy practical fixed-time tracking control of nonlinear systems. IEEE Transactions on Fuzzy Systems, 29(3), 664–673. https://doi.org/10.1109/TFUZZ.2019.2959972
   Web of Science ®Google Scholar
• Chen, M., Wang, H. Q., & Liu, X. P. (2021b). Adaptive practical fixed-time tracking control with prescribed boundary constraints. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(4), 1716–1726. https://doi.org/10.1109/TCSI.2021.3051076
   Web of Science ®Google Scholar
• Deng, H., & Kristic, M. (1997). Stochastic nonlinear stabilization – I: A backstepping design. Systems and Control Letters, 32(3), 143–150. https://doi.org/10.1016/S0167-6911(97)00068-6
   Web of Science ®Google Scholar
• Ding, D. R., Han, Q. L., Xiang, Y., Ge, X. H., & Zhang, X. M. (2018). A survey on security control and attack detection for industrial cyber-physical systems. Neurocomputing, 275, 1674–1683. https://doi.org/10.1016/j.neucom.2017.10.009
   Web of Science ®Google Scholar
• Dong, X., Chen, G., & Chen, L. (1997). Adaptive control of the uncertain duffing oscillator. International Journal of Bifurcation and Chaos, 7(7), 1651–1658. https://doi.org/10.1142/S0218127497001278
   Web of Science ®Google Scholar
• Garcia, E., & Antsaklis, P. J. (2011). Model-based event-triggered control with time-varying network delays. In 2011 50th IEEE Conference on Decision and Control and European Control Conference (pp. 1650–1655). IEEE Press.
   Google Scholar
• He, W. L., Gao, X. Y., Zhong, W. M., & Qian, F. (2018). Secure impulsive synchronization control of multi-agent systems under deception attacks. Information Science, 459, 354–368. https://doi.org/10.1016/j.ins.2018.04.020
   Web of Science ®Google Scholar
• Lee, J., Jin, M. L., Kashiri, N., Caldwell, D. G., & Tsagarakis, N. G. (2018). Inversion-free force tracking control of piezoelectric actuatorsusing fast finite-time integral terminal sliding-mode. Mechatronics, 57, 39–50. https://doi.org/10.1016/j.mechatronics.2018.11.005
   Web of Science ®Google Scholar
• Li, B. M., Xia, J. W., Zhang, H. S., Shen, H., & Wang, Z. (2020). Event-triggered adaptive fuzzy tracking control for stochastic nonlinear systems. Franklin Institute, 357(14), 9505–9522. https://doi.org/10.1016/j.jfranklin.2020.07.023
   Web of Science ®Google Scholar
• Li, C. Y., Tong, S. C., & Wang, W. (2011). Fuzzy adaptive high-gain-based observer backstepping control for SISO nonlinear systems. Information Science, 181(11), 2405–2421. https://doi.org/10.1016/j.ins.2011.01.040
   Web of Science ®Google Scholar
• Li, S., Ahn, C. K., & Xiang, Z. R. (2019). Sampled-data adaptive output feedback fuzzy stabilization for switched nonlinear systems with asynchronous switching. IEEE Transactions on Fuzzy System, 27(1), 200–205. https://doi.org/10.1109/TFUZZ.2018.2881660
   Web of Science ®Google Scholar
• Liu, H. T., Zhang, T., & Tian, X. H. (2016). Continuous output-feedback finite-time control for a class of second-order nonlinear systems with disturbances. International Journal of Robust and Nonlinear Control, 26(2), 218–234. https://doi.org/10.1002/rnc.3305
   Web of Science ®Google Scholar
• Liu, L., Sun, H., Ma, L., Zhang, J., & Bo, Y. (2021). Quasi-consensus control for a class of time-varying stochastic nonlinear time-delay multiagent systems subject to deception attacks. IEEE Transactions on Systems Man and Cybernetics: Systems, 51(11), 6863–6873. https://doi.org/10.1109/TSMC.2020.2964826
   Web of Science ®Google Scholar
• Liu, S., Wei, G. L., Ding, D. R., & Mao, J. Y. (2017). Kalman-type recursive filtering for stochastic nonlinear time-delay systems with randomly occurring deception attacks. In 2017 36th Chinese Control Conference (pp. 5264–5269). IEEE Press.
   Google Scholar
• Liu, Z., Wang, J. H., Philip Chen, C. L., & Zhang, Y. (2018). Event trigger fuzzy adaptive compensation control of uncertain stochastic nonlinear systems with actuator failures. IEEE Transactions on Fuzzy Systems, 26(6), 3770–3781. https://doi.org/10.1109/TFUZZ.2018.2848909
   Web of Science ®Google Scholar
• Ma, H., Li, H. Y., R. Q. Lu, & Huang, T. W. (2020). Adaptive event-triggered control for a class of nonlinear systems with periodic disturbances. Science China Information Sciences, 63(5), 1–15. https://doi.org/10.1007/s11432-019-2680-1
   Web of Science ®Google Scholar
• Meng, W. C., Yang, Q. M., Si, J., & Sun, Y. X. (2016). Adaptive neural control of a class of output-constrained nonaffine systems. IEEE Transactions on Cybernetics, 46(1), 85–95. https://doi.org/10.1109/TCYB.2015.2394797
   PubMed Web of Science ®Google Scholar
• Nersesov, S. G., Haddad, W. M., & Hui, Q. (2008). Finite-time stabilization of nonlinear dynamical systems via control vector Lyapunov finctions. Journal Franklin Institute, 345(7), 819–837. https://doi.org/10.1016/j.jfranklin.2008.04.015
   Web of Science ®Google Scholar
• Nersesov, S. G., Nataraj, C., & Avis, J. M. (2009). Design of finite-time stabilizing controllers for nonlinear dynamical systems. International Journal of Robust and Nonlinear Control: IFAC-Affiliated Journal, 19(8), 900–918. https://doi.org/10.1002/rnc.1359
   Web of Science ®Google Scholar
• Peng, Z. H., Wang, J., & Wang, D. (2018). Distributed maneuvering of autonomous surface vehicles based on neurodynamic optimization and fuzzy approximation. IEEE Transactions on Control Systems Technology, 26(3), 1083–1090. https://doi.org/10.1109/TCST.2017.2699167
   Web of Science ®Google Scholar
• Qian, C. J., & Lin, W. (2001). Non-Lipschitz continuous stabilizers for nonlinear systems with uncontrollable unstable linearizattion. Systems and Control Letters, 42(3), 185–200. https://doi.org/10.1016/S0167-6911(00)00089-X
   Web of Science ®Google Scholar
• Ren, P., & Wang, F. (2022). Fast finite-time adaptive fuzzy control for quantized stochastic uncertain nonlinear systems. International Journal of Adaptive Control and Signal Processing, 36(6), 1460–1479. https://doi.org/10.1002/acs.3405
   Web of Science ®Google Scholar
• Salmanpour, Y., Mehdi-Arefi, M., Khayatian, A., & Kaynak, O. (2022). Event-Triggered fuzzy adaptive leader-following tracking control of nonaffine multiagent systems with finite-time output constraint and input saturation. IEEE Transactions on Fuzzy Systems, 30(4), 933–944. https://doi.org/10.1109/TFUZZ.2021.3050847
   Web of Science ®Google Scholar
• Shen, B., Wang, Z. D., Wang, D., & Li, Q. (2020). State-Saturated recursive filter design for stochastic time-V arying nonlinear complex networks under deception attacks. IEEE Transactions on Neural Networks and Learning Systems, 31(10), 3788–3800. https://doi.org/10.1109/TNNLS.2019.2946290
   PubMed Web of Science ®Google Scholar
• Shen, H., Li, F., Wu, G. Z., Park, J. H., & Sreeram, S. (2018). Fuzzy-model-based nonfragile control for nonlinear singularly perturbed systems with semi-markov jump parameters. IEEE Transactions on Fuzzy Systems, 26(6), 3428–3439. https://doi.org/10.1109/TFUZZ.2018.2832614
   Web of Science ®Google Scholar
• Shiriaev, A. S., Ludvigsen, H., Egeland, H., & Fradkov, A. L. (1999). Swinging up of non-affine in control pendulum. Proceedings of the 1999 American Control Conference, 6, 4039–4044. https://doi.org/10.1109/TNNLS.2019.2946290
   Google Scholar
• Sui, S., Philip-Chen, C. L., & Tong, S. C. (2019). Fuzzy adaptive finite-time control design for nontriangular stochastic nonlinear systems. IEEE Transactions on Fuzzy Systems, 27(1), 172–184. https://doi.org/10.1109/TFUZZ.2018.2882167
   Web of Science ®Google Scholar
• Sui, S., Philip-Chen, C. L., Tong, S. C., & Feng, S. (2020). Finite-time adaptive quantized control of stochastic nonlinear systems with input quantization: a broad learning system based identification method. IEEE Transactions on Industrial Electronics, 67(10), 8555–8565. https://doi.org/10.1109/TIE.2019.2947844
   Web of Science ®Google Scholar
• Sun, J. L., Yi, J. Q., & Pu, Z. Q. (2022). Fixed-Time adaptive fuzzy control for uncertain nonstrict-feedback systems with time-varying constraints and input saturations. IEEE Transactions on Fuzzy Systems, 30(4), 1114–1128. https://doi.org/10.1109/TFUZZ.2021.3052610
   Web of Science ®Google Scholar
• Sun, W., Su, S. F., Wu, Y. Q., & Xia, J. W. (2021). Novel adaptive fuzzy control for output constrained stochastic nonstrict feedback nonlinear systems. IEEE Transactions on Fuzzy Systems, 29(5), 1188–1197. https://doi.org/10.1109/TFUZZ.2020.2969909
   Web of Science ®Google Scholar
• Sun, Y. M., Chen, B., Lin, C., Wang, H. H., & Zhou, S. (2016). Adaptive neural control for a class of stochastic nonlinear systems by backstepping approach. Information Sciences, 369, 748–764. https://doi.org/10.1016/j.ins.2016.06.010
   Web of Science ®Google Scholar
• Tabuada, P. (2007). Event-triggered real-time scheduling of stabilizing control tasks. IEEE Transactions on Automatic Control, 52(9), 1680–1685. https://doi.org/10.1109/TAC.2007.904277
   Web of Science ®Google Scholar
• Wang, C. L., & Lin, Y. (2015). Decentralized adaptive tracking control for a class of interconnected nonlinear time-varying systems. Automatica, 54, 16–24. https://doi.org/10.1016/j.automatica.2015.01.041
   Web of Science ®Google Scholar
• Wang, F., Chen, B., Sun, Y. M., Gao, Y. L., & Lin, C. (2020). Finite-time fuzzy control of stochastic nonlinear systems. IEEE Transactions on Cybernetics, 50(6), 2617–2626. https://doi.org/10.1109/TCYB.2019.2925573
   Web of Science ®Google Scholar
• Wang, F., Liu, Z., Zhang, Y., & Philip-Chen, C. L. (2019). Adaptive finite-time control of stochastic nonlinear systems with actuator failures. Fuzzy Sets and Systems, 374, 170–183. https://doi.org/10.1016/j.fss.2018.12.005
   Web of Science ®Google Scholar
• Wang, F., You, Z., Liu, Z., & Philip-Chen, C. L. (2022). A fast finite-time neural network control of stochastic nonlinear systems. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2022.3143655
   Google Scholar
• Wang, H. Q., Liu, P. X. P., Bao, J. L., Xie, X. J., & Li, S. (2019). Adaptive neural output-feedback decentralized control for large-scale nonlinear systems with stochastic disturbances. IEEE Transactions on Neural Networks and Learning Systems, 31(3), 972–983. https://doi.org/10.1109/TNNLS.2019.2912082
   PubMed Web of Science ®Google Scholar
• Wang, H. Q., Shan, L. C., Zhao, X. D., & Li, T. S. (2021). Direct adaptive fuzzy tracking control of non-affine stochastic nonlinear time-delay systems. International Journal of Fuzzy Systems, 23(2), 309–321. https://doi.org/10.1007/s40815-020-00925-7
   Web of Science ®Google Scholar
• Wang, L. B., Wang, H. Q., & Liu, P. X. P. (2021). Adaptive fuzzy finite-time control of stochastic nonlinear systems with actuator faults. Nonlinear Dynamics, 104(1), 523–536. https://doi.org/10.1007/s11071-021-06309-2
   Web of Science ®Google Scholar
• Wang, W., & Li, Y. M. (2023). Distributed fuzzy optimal consensus control of state-constrained nonlinear strict-Feedback systems. IEEE Transactions on Cybernetics, 53(5), 2914–2929. https://doi.org/10.1109/TCYB.2021.3140104.
   PubMed Web of Science ®Google Scholar
• Wei, B., Tian, E., Liu, J. L., & Zhao, X. (2021). Probabilistic-constrained tracking control for stochastic time-varying systems under deception attacks: A Round-Robin protocol. Franklin Institute, 358(17), 9135–9157. https://doi.org/10.1016/j.jfranklin.2021.09.021
   Web of Science ®Google Scholar
• Xing, L. T., Wen, C. Y., Liu, Z. T., Su, H. Y., & Cai, J. P. (2016). Event-triggered adaptive control for a class of uncertain nonlinear systems. IEEE Transactions on Automatic Control, 62(4), 2071–2076. https://doi.org/10.1109/TAC.2016.2594204
   Web of Science ®Google Scholar
• Yan, H. C., Wang, J. N., Zhang, H., Shen, H., & Zhan, X. S. (2020). Event-based security control for stochastic networked systems subject to attacks. IEEE Transactions on Systems Man and Cybernetics: Systems, 50(11), 4643–4654. https://doi.org/10.1109/TSMC.2018.2856819
   Web of Science ®Google Scholar
• Yang, Y., Huang, J. S., Su, X. J., Wang, K., & Li, G. (2020). Adaptive control of second-order nonlinear systems with injection and deception attacks. IEEE Transactions on Systems Man Cybernetics: Systems, 52(1), 574–581. https://doi.org/10.1109/TSMC.2020.3003801
   Web of Science ®Google Scholar
• Yao, Y. G., Tan, J. Q., Wu, J., & Zhang, X. (2022). A unified fuzzy control approach for stochastic high-order nonlinear systems with or without state constraints. IEEE Transactions on Fuzzy Systems, 30(10), 4530–4540. https://doi.org/10.1109/TFUZZ.2022.3155297
   Web of Science ®Google Scholar
• You, Z., & Wang, F. (2021). Adaptive fast finite-time fuzzy control of stochastic nonlinear systems. IEEE Transactions on Fuzzy Systems, 30(7), 2279–2288. https://doi.org/10.1109/TFUZZ.2021.3078820
   Web of Science ®Google Scholar
• Zhang, L. L., Chen, B., & Lin, C. (2020). Adaptive neural consensus tracking control for a class of 2-order multi-agent systems with nonlinear dynamics. Neuroocomputing, 404, 84–92. https://doi.org/10.1016/j.neucom.2020.05.004
   Web of Science ®Google Scholar
• Zhang, T., Ge, S. S., & Hang, C. C. (2000). Adaptive neural network control for strict feedback nonlinear systems using backstepping design. Automatica, 36(12), 1835–1846. https://doi.org/10.1016/S0005-1098(00)00116-3
   Web of Science ®Google Scholar
• Zhu, Q. D., Liu, Y. C., & Wen, G. X. (2020). Adaptive neural network control for time-varying state constrained nonlinear stochastic systems with input saturation. Information Science, 527, 191–209. https://doi.org/10.1016/j.ins.2020.03.055
   Web of Science ®Google Scholar