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Veeraragavan, Gokulakrishnan, Radhakrishnan, Srinivasan. (1402). Boundary controller design for stabilization of stochastic nonlinear reaction-diffusion systems with time-varying delays. سامانه مدیریت نشریات علمی, 12(2), 196-206. doi: 10.22034/cmde.2023.50986.2124
Gokulakrishnan Veeraragavan; Srinivasan Radhakrishnan. "Boundary controller design for stabilization of stochastic nonlinear reaction-diffusion systems with time-varying delays". سامانه مدیریت نشریات علمی, 12, 2, 1402, 196-206. doi: 10.22034/cmde.2023.50986.2124
Veeraragavan, Gokulakrishnan, Radhakrishnan, Srinivasan. (1402). 'Boundary controller design for stabilization of stochastic nonlinear reaction-diffusion systems with time-varying delays', سامانه مدیریت نشریات علمی, 12(2), pp. 196-206. doi: 10.22034/cmde.2023.50986.2124
Veeraragavan, Gokulakrishnan, Radhakrishnan, Srinivasan. Boundary controller design for stabilization of stochastic nonlinear reaction-diffusion systems with time-varying delays. سامانه مدیریت نشریات علمی, 1402; 12(2): 196-206. doi: 10.22034/cmde.2023.50986.2124

Boundary controller design for stabilization of stochastic nonlinear reaction-diffusion systems with time-varying delays

Computational Methods for Differential Equations
مقاله 1، دوره 12، شماره 2، خرداد 2024، صفحه 196-206    اصل مقاله (335.66 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22034/cmde.2023.50986.2124
نویسندگان
Gokulakrishnan Veeraragavan؛ Srinivasan Radhakrishnan*
Department of Mathematics, SRM Institute of Science and Technology, Ramapuram Campus, Chennai - 600 089, Tamilnadu, India.
چکیده
This paper is focused on studying the stabilization problems of stochastic nonlinear reaction-diffusion systems (SNRDSs) with time-varying delays via boundary control. Firstly, the boundary controller was designed to stabilization for SNRDSs. By utilizing the Lyapunov functional method, Ito’s differential formula, Wirtinger’s inequality, Gronwall inequality, and LMIs, sufficient conditions are derived to guarantee the finite-time stability (FTS) of proposed systems. Secondly, the basic expressions of the control gain matrices are designed for the boundary controller. Finally, numerical examples are presented to verify the efficiency and superiority of the proposed stabilization criterion. 
کلیدواژه‌ها
Stochastic nonlinear systems؛ Reaction-diffusion terms؛ Boundary control؛ Time-varying delays
مراجع
  • [1] C. Aouiti and H. Jallouli, State feedback controllers based finite-time and fixed-time stabilisation of high order BAM with reaction-diffusion term, International Journal of Systems Science, 52(5) (2021), 905-927.
  • [2] P. Balasubramaniam and C. Vidhya, Global asymptotic stability of stochastic BAM neural networks with distributed delays and reaction-diffusion terms, Journal of Computational and Applied Mathematics, 234(12) (2010), 3458-3466.
  • [3] T. Chen, S. Peng, Y. Hong, and G. Mai, Finite-time stability and stabilization of impulsive stochastic delayed neural networks with Rous and Rons, IEEE Access, 8 (2020), 87133-87141.
  • [4] P. Cheng, F. Deng, and F. Yao, Almost sure exponential stability and stochastic stabilization of stochastic differential systems with impulsive effects, Nonlinear Analysis: Hybrid Systems, 30 (2018), 106-117.
  • [5] K. Ding, Q. Zhu, and L. Liu, Extended dissipativity stabilization and synchronization of uncertain stochastic reaction-diffusion neural networks via intermittent non-fragile control, Journal of the Franklin Institute, 356(18) (2019), 11690-11715.
  • [6] T. Dong, A. Wang, H. Zhu, and X. Liao, Event-triggered synchronization for reaction-diffusion complex networks via random sampling, Physica A: Statistical Mechanics and its Applications, 495 (2018), 454-462.
  • [7] A. M. Elaiw, A. D. Hobiny, and A. D. Al Agha, Global dynamics of reaction-diffusion oncolytic M1-virotherapy with immune response, Applied Mathematics and Computation, 367 (2020), 124758.
  • [8] N. Espitia, I. Karafyllis, and M. Krstic, Event-triggered boundary control of constant-parameter reaction-diffusion PDEs: A small-gain approach, Automatica, 128 (2021), 109562.
  • [9] X. Fan, X. Zhang, L. Wu, and M. Shi, Finite-time stability analysis of reaction-diffusion genetic regulatory networks with time-varying delays, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 14(4) (2017), 868-879.
  • [10] X. X. Han, K. N. Wu, and X. Ding, Finite-time stabilization for stochastic reaction-diffusion systems with Markovian switching via boundary control, Applied Mathematics and Computation, 385 (2020), 125422.
  • [11] X. X. Han, K. N. Wu, X. Ding, and B. Yang, Boundary control of stochastic reaction-diffusion systems with Markovian switching, International Journal of Robust Nonlinear Control, 30(10) (2020), 4129-4148.
  • [12] R. Kumar and S. Das, Exponential stability of inertial BAM neural network with time-varying impulses and mixed time-varying delays via matrix measure approach, Communications in Nonlinear Science and Numerical Simulation, 81 (2019), 105016.
  • [13] S. Lakshmanan, M. Prakash, R. Rakkiyappan, and J. H. Young, Adaptive synchronization of reaction-diffusion neural networks and its application to secure communication, IEEE Transactions on Cybernetics, 50(3) (2020), 911-922.
  • [14] X. Li, R. Rakkiyappan, and P. Balasubramaniam, Existence and global stability analysis of equilibrium of fuzzy cellular neural networks with time delay in the leakage term under impulsive perturbations, Journal of Franklian Institute, 348(2) (2011), 135-155.
  • [15] Z. Li and R. Xu, Global asymptotic stability of stochastic reaction-diffusion neural networks with time delays in the leakage terms, Communications in Nonlinear Science and Numerical Simulation, 17(4) (2012), 1681-1689.
  • [16] H. Lin and F. Wang, Global dynamics of a nonlocal reaction-diffusion system modeling the west nile virus transmission, Nonlinear Analysis: Real World Applications, 46 (2019), 352-373.
  • [17] X. Z. Liu, K. N. Wu, and Z. T. Li, Exponential stabilization of reaction-diffusion systems via intermittent boundary control, IEEE Transactions on Automatic Control, 67(6) (2022), 3036-3042.
  • [18] X. Z. Liu, K. N. Wu, and W. Zhang, Intermittent boundary stabilization of stochastic reaction-diffusion CohenGrossberg neural networks, Neural Networks, 131 (2020), 1-13.
  • [19] X. Z. Liu, K. N. Wu, and W. Zhang, Mean square finite-time boundary stabilisation and H∞ boundary control for stochastic reaction-diffusion systems, International Journal of System Science, 50(7) (2019), 1388-1398.
  • [20] B. Priya, M. Syed Ali, G. K. Thakur, S. Sanober, and B. Dhupia, pth moment exponential stability of memristor Cohen-Grossberg BAM neural networks with time-varying delays and reaction-diffusion, Chinese Journal of Physics, 74 (2021), 184-194.
  • [21] X. Song, J. Man, S. Song, Y. Zhang, and Z. Ning, Finite/fixed-time synchronization for Markovian complex-valued memristive neural networks with reaction-diffusion terms and its application, Neurocomputing, 414 (2020), 131142.
  • [22] X. Song, M. Wang, J. H. Park, and S. Song, Spatial-L∞-norm-based finite-time bounded control for semilinear parabolic PDE systems with applications to chemical-reaction processes, IEEE Transactions on Cybernetics, 52(1) (2022), 178-191.
  • [23] X. Song, Q. Zhang, S. Song, and C. K. Ahn, Sampled-data-based event-triggered fuzzy control for PDE systems under cyber-attacks, IEEE Transactions on Fuzzy Systems, 30(7) (2022), 2693-2705.
  • [24] M. Syed Ali, L. Palanisamy, J. Yogambigai, and L. Wang, Passivity-based synchronization of Markovian jump complex dynamical networks with time-varying delays, parameter uncertainties, reaction-diffusion terms, and sampled-data control, Journal of Computational and Applied Mathematics, 352 (2019), 79-92.
  • [25] M. Syed Ali, S. Saravanan, and L. Palanisamy, Stochastic finite-time stability of reaction-diffusion CohenGrossberg neural networks with time-varying delays, Chinese Journal of Physics, 57 (2019), 314-328.
  • [26] M. Syed Ali, R. Vadivel, and R. Saravanakumar, Event-triggered state estimation for Markovian jumping impulsive neural networks with interval time-varying delays, International Journal of Control, 92(2) (2019), 270-290.
  • [27] M. Syed Ali and J. Yogambigai, Finite-time robust stochastic synchronization of uncertain Markovian complex dynamical networks with mixed time-varying delays and reaction-diffusion terms via impulsive control, Journal of the Franklin Institute, 354(5) (2017), 2415-2436.
  • [28] M. Syed Ali, J. Yogambigai, and O. M. Kwon, Finite-time robust passive control for a class of switched reactiondiffusion stochastic complex dynamical networks with coupling delays and impulsive control, International Journal of Systems Science, 49(4) (2018), 718-735.
  • [29] J. Tan, C. Li, and T. Huang, The stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms, Cognitive Neurodynamics, 9 (2015), 213-220.
  • [30] G. K. Thakur, M. Syed Ali, B. Priya, V. Gokulakrishnan, and S. Asma Kauser, Impulsive effects on stochastic bidirectional associative memory neural networks with reaction-diffusion and leakage delays, International Journal of Computer Mathematics, 99(8) (2021), 1669-1686.
  • [31] J. Wang and H. Wu, Passivity of delayed reaction-diffusion networks with application to a food web model, Applied Mathematics and Computation, 219(24) (2013), 11311-11326.
  • [32] J. L. Wang, X. Zhang, H. Wu, T. Huang, and Q. Wang, Finite-time passivity and synchronization of coupled reaction-diffusion neural networks with multiple weights, IEEE Transactions on Cybernetics, 49(9) (2019), 33853397.
  • [33] T. Wei, L. Wang, and Y. Wang, Existence, uniqueness and stability of mild solutions to stochastic reactiondiffusion Cohen-Grossberg neural networks with delays and Wiener processes, Neurocomputing, 239 (2017), 19-27.
  • [34] K. N. Wu, M. Y. Na, L. Wang, X. Ding, and B. Wu, Finite-time stability of impulsive reaction-diffusion systems with and without time delay, Applied Mathematics and Computation, 363 (2019), 124591.
  • [35] K. N. Wu, M. Z. Ren, and X. Z. Liu, Exponential input-to-state stability of stochastic delay reaction-diffusion neural networks, Neurocomputing, 412 (2020), 399-405.
  • [36] K. Wu, H. Sun, P. Shi, and C. C. Lim, Finite-time boundary stabilization of reaction-diffusion systems, International Journal of Robust Nonlinear Control, 28(5) (2018), 1641-1652.
  • [37] K. Wu, H. Sun, B. Yang, and C. C. Lim, Finite-time boundary control for delay reaction-diffusion systems, Applied Mathematics and Computation, 329 (2018), 52-63.
  • [38] Q. Zhu, Stabilization of stochastic nonlinear delay systems with exogenous disturbances and the event-triggerd feedback control, IEEE Transactions on Automatic Control, 64(9) (2019), 3764-3771.
  • [39] Q. Zhu, X. Li, and X. Yang, Exponential stability for stochastic reaction-diffusion BAM neural networks with time-varying and distributed delays, Applied Mathematics and Computation, 217(13) (2011), 6078-6091.
  • [40] Q. Zhu, R. Rakkiyappan, and A. Chandrasekar, Stochastic stability of Markovian jump BAM neural networks with leakage delays and impulse control, Neurocomputing, 136 (2014), 136-151.
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