Abstract
In this paper, the fixed-time synchronization analysis is addressed for a class of discontinuous neutral-type neural networks. The focus is mainly on the design of useful control laws such that the constructed error system converges to zero in a fixed time. The major difficulty is to cope with the discontinuous neuron activations, D operators, time-varying discrete, and distributed delays simultaneously. To accomplish the target, a new and effective framework is firstly established. By means of functional differential inclusions theory, inequality technique and Lyapunov–Krasovskii functional, novel discontinuous feedback controllers are designed and some new verifiable algebraic criteria are derived to design the control gains. In contrast to the existed results on the neutral-type neural networks, the theoretical results of this paper are more general and rigorous. Finally, numerical examples and simulations are presented to illustrate the correctness of the main results.
Acknowledgements
The authors thank the anonymous reviewers for their insightful suggestions which improved this work significantly. This work was jointly supported by the National Natural Science Foundation of China (61773217, 12001011), the Natural Science Foundation of Anhui Povince (2008085QA14).
-
Author contribution: All authors read and approved the manuscript.
-
Research funding: None declared.
-
Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
[1] A. Polyakov, “Nonlinear feedback design for fixed-time stabilization of linear control systems,” IEEE Trans. Automat. Contr., vol. 57, no. 8, pp. 2106–2110, 2012. https://doi.org/10.1109/tac.2011.2179869.Search in Google Scholar
[2] J. Cao and R. Li, “Fixed-time synchronization of delayed memristor-based recurrent neural networks,” Sci. China Inf. Sci., vol. 60, no. 3, 2017, Art no. 032201. https://doi.org/10.1007/s11432-016-0555-2.Search in Google Scholar
[3] C. Chen, L. Li, H. Peng, J. Kurths, and Y. Yang, “Fixed-time synchronization of hybrid coupled networks with time-varying delays,” Chaos, Solit. Fractals, vol. 108, pp. 49–56, 2018. https://doi.org/10.1016/j.chaos.2018.01.027.Search in Google Scholar
[4] C. Chen, L. Li, H. Peng, and Y. Yang, “Fixed-time synchronization of memristor-based BAM neural networks with time-varying discrete delay,” Neural Network., vol. 96, pp. 47–54, 2017. https://doi.org/10.1016/j.neunet.2017.08.012.Search in Google Scholar PubMed
[5] R. Li, J. Cao, A. Alsaedi, and F. Alsaadi, “Exponential and fixed-time synchronization of Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms,” Appl. Math. Comput., vol. 313, pp. 37–51, 2017. https://doi.org/10.1016/j.amc.2017.05.073.Search in Google Scholar
[6] Y. Wan, J. Cao, G. Wen, and W. Yu, “Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks,” Neural Network., vol. 73, pp. 86–94, 2016. https://doi.org/10.1016/j.neunet.2015.10.009.Search in Google Scholar PubMed
[7] M. Zheng, L. Li, H. Peng, et al.., “Fixed-time synchronization of memristor-based fuzzy cellular neural network with time-varying delay,” J. Franklin Inst., vol. 355, no. 14, pp. 6780–6809, 2018. https://doi.org/10.1016/j.jfranklin.2018.06.041.Search in Google Scholar
[8] C. Aouiti, E. A. Assali, J. Cao, and A. Alsaedi, “Global exponential convergence of neutral-type competitive neural networks with multi-proportional delays, distributed delays and time-varying delay in leakage delays,” Int. J. Syst. Sci., vol. 49, pp. 2202–2214, 2018. https://doi.org/10.1080/00207721.2018.1496297.Search in Google Scholar
[9] C. Aouiti, E. A. Assali, and I. B. Gharbia, “Existence and exponential stability of piecewise pseudo almost periodic solution of neutral-type inertial neural networks with mixed delay and impulsive perturbations,” Neurocomputing, vol. 357, pp. 292–309, 2019. https://doi.org/10.1016/j.neucom.2019.04.077.Search in Google Scholar
[10] C. Aouiti, I. B. Gharbia, J. Cao, and A. Alsaedi, “Dynamics of impulsive neutral-type BAM neural networks,” J. Franklin Inst., vol. 356, no. 4, pp. 2294–2324, 2019. https://doi.org/10.1016/j.jfranklin.2019.01.028.Search in Google Scholar
[11] M. Zheng, Z. Wang, L. Li, H. Peng, et al.., “Finite-time generalized projective lag synchronization criteria for neutral-type neural networks with delay,” Chaos, Solit. Fractals, vol. 107, pp. 195–203, 2018. https://doi.org/10.1016/j.chaos.2018.01.009.Search in Google Scholar
[12] X. Yang, Z. Cheng, X. Li, and T. Ma, “Exponential synchronization of coupled neutral-type neural networks with mixed delays via quantized output control,” J. Franklin Inst., vol. 356, no. 15, pp. 8138–8153, 2019. https://doi.org/10.1016/j.jfranklin.2019.07.006.Search in Google Scholar
[13] J. Hale, Theory of Functional Differential Equations, New York, Springer, 1977.10.1007/978-1-4612-9892-2Search in Google Scholar
[14] F. C. Kong and R. Sakthivel, “Delay-dependent criteria for general decay synchronization of discontinuous fuzzy neutral-type neural networks with time-varying delays,” Int. J. Robust Nonlinear Control, vol. 30, pp. 4503–4530, 2020. https://doi.org/10.1002/rnc.5000.Search in Google Scholar
[15] N. Ozcan, “New conditions for global stability of neutral-type delayed Cohen-Grossberg neural networks,” Neural Network., vol. 106, pp. 1–7, 2018. https://doi.org/10.1016/j.neunet.2018.06.009.Search in Google Scholar PubMed
[16] K. Wang and Y. L. Zhu, “Stability of almost periodic solution for a generalized neutral-type neural networks with delays,” Neurocomputing, vol. 73, pp. 3300–3307, 2010. https://doi.org/10.1016/j.neucom.2010.05.017.Search in Google Scholar
[17] F. C. Kong, Q. X. Zhu, K. Wang, and J. J. Nieto, “Stability analysis of almost periodic solutions of discontinuous BAM neural networks with hybrid time-varying delays and D operator,” J. Franklin Inst., vol. 356, no. 18, pp. 11605–11637, 2019. https://doi.org/10.1016/j.jfranklin.2019.09.030.Search in Google Scholar
[18] F. C. Kong, Q. X. Zhu, R. Sakthivel, and A. Mohammadzadeh, “Fixed-time synchronization analysis for discontinuous fuzzy inertial neural networks with parameter uncertainties,” Neurocomputing, vol. 422, pp. 295–313, 2021. https://doi.org/10.1016/j.neucom.2020.09.014.Search in Google Scholar
[19] L. Wang, Z. Zeng, J. Hu, and X. Wang, “Controller design for global fixed-time synchronization of delayed neural networks with discontinuous activations,” Neural Network., vol. 87, pp. 122–131, 2017. https://doi.org/10.1016/j.neunet.2016.12.006.Search in Google Scholar PubMed
[20] C. Yang and L. Huang, “Finite-time synchronization of coupled time-delayed neural networks with discontinuous activations,” Neurocomputing, vol. 249, pp. 64–71, 2017. https://doi.org/10.1016/j.neucom.2017.03.017.Search in Google Scholar
[21] Z. Cai and L. Huang, “Generalized Lyapunov approach for functional differential inclusions,” Automatica, vol. 113, p. 108740, 2019. https://doi.org/10.1016/j.automatica.2019.108740.Search in Google Scholar
[22] A. F. Filippov and F. M. Arscott, Differential Equations with Discontinuous Righthand Sides: Control Systems, Dordrecht, Kluwer, Springer, 1988.10.1007/978-94-015-7793-9Search in Google Scholar
[23] F. H. Clarke, Optimization and Nonsmooth Analysis, New York, Wiley, 1983.Search in Google Scholar
[24] C. Hu, J. Yu, Z. Chen, H. Jiang, and T. Huang, “Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks,” Neural Network., vol. 89, pp. 74–83, 2017. https://doi.org/10.1016/j.neunet.2017.02.001.Search in Google Scholar PubMed
[25] H. K. Khalil and J. W. Grizzle, Nonlinear Systems, Upper Saddle River, Prentice-Hall, 2002.Search in Google Scholar
[26] F. C. Kong, Z. G. Luo, and X. P. Wang, “Piecewise pseudo almost periodic solutions of generalized neutral-type neural networks with impulses and delays,” Neural Process. Lett., vol. 48, no. 3, pp. 1611–1631, 2018. https://doi.org/10.1007/s11063-017-9758-4.Search in Google Scholar
[27] C. J. Xu and P. L. Li, “On anti-periodic solutions for neutral shunting inhibitory cellular neural networks with time-varying delays and D operator,” Neurocomputing, vol. 275, pp. 377–382, 2018. https://doi.org/10.1016/j.neucom.2017.08.030.Search in Google Scholar
© 2021 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Original Research Articles
- Frequency responses for induced neural transmembrane potential by electromagnetic waves (1 kHz to 1 GHz)
- Investigating existence results for fractional evolution inclusions with order r ∈ (1, 2) in Banach space
- Optimal control of non-instantaneous impulsive second-order stochastic McKean–Vlasov evolution system with Clarke subdifferential
- Generalized forms of fractional Euler and Runge–Kutta methods using non-uniform grid
- Controllability of coupled fractional integrodifferential equations
- A new generalized approach to study the existence of solutions of nonlinear fractional boundary value problems
- Rational soliton solutions in the nonlocal coupled complex modified Korteweg–de Vries equations
- Buoyancy driven flow characteristics inside a cavity equiped with diamond elliptic array
- Analysis and numerical effects of time-delayed rabies epidemic model with diffusion
- Two occurrences of fractional actions in nonlinear dynamics
- Multiwave interaction solutions for a (3 + 1)-dimensional B-type Kadomtsev–Petviashvili equation in fluid dynamics
- Effects of mixed time delays and D operators on fixed-time synchronization of discontinuous neutral-type neural networks
- Solvability and stability of nonlinear hybrid ∆-difference equations of fractional-order
- Weak and strong boundedness for p-adic fractional Hausdorff operator and its commutator
- Simulation and modeling of different cell shapes for closed-cell LM-13 alloy foam for compressive behavior
- Pandemic management by a spatio–temporal mathematical model
- Adaptive ADI difference solution of quenching problems based on the 3D convection–reaction–diffusion equation
- Null controllability of Hilfer fractional stochastic integrodifferential equations with noninstantaneous impulsive and Poisson jump
- Application of modified Mickens iteration procedure to a pendulum and the motion of a mass attached to a stretched elastic wire
- Modeling the spatiotemporal intracellular calcium dynamics in nerve cell with strong memory effects
- Switched coupled system of nonlinear impulsive Langevin equations involving Hilfer fractional-order derivatives
- Improving the dynamic behavior of the plate under supersonic air flow by using nonlinear energy sink
Articles in the same Issue
- Frontmatter
- Original Research Articles
- Frequency responses for induced neural transmembrane potential by electromagnetic waves (1 kHz to 1 GHz)
- Investigating existence results for fractional evolution inclusions with order r ∈ (1, 2) in Banach space
- Optimal control of non-instantaneous impulsive second-order stochastic McKean–Vlasov evolution system with Clarke subdifferential
- Generalized forms of fractional Euler and Runge–Kutta methods using non-uniform grid
- Controllability of coupled fractional integrodifferential equations
- A new generalized approach to study the existence of solutions of nonlinear fractional boundary value problems
- Rational soliton solutions in the nonlocal coupled complex modified Korteweg–de Vries equations
- Buoyancy driven flow characteristics inside a cavity equiped with diamond elliptic array
- Analysis and numerical effects of time-delayed rabies epidemic model with diffusion
- Two occurrences of fractional actions in nonlinear dynamics
- Multiwave interaction solutions for a (3 + 1)-dimensional B-type Kadomtsev–Petviashvili equation in fluid dynamics
- Effects of mixed time delays and D operators on fixed-time synchronization of discontinuous neutral-type neural networks
- Solvability and stability of nonlinear hybrid ∆-difference equations of fractional-order
- Weak and strong boundedness for p-adic fractional Hausdorff operator and its commutator
- Simulation and modeling of different cell shapes for closed-cell LM-13 alloy foam for compressive behavior
- Pandemic management by a spatio–temporal mathematical model
- Adaptive ADI difference solution of quenching problems based on the 3D convection–reaction–diffusion equation
- Null controllability of Hilfer fractional stochastic integrodifferential equations with noninstantaneous impulsive and Poisson jump
- Application of modified Mickens iteration procedure to a pendulum and the motion of a mass attached to a stretched elastic wire
- Modeling the spatiotemporal intracellular calcium dynamics in nerve cell with strong memory effects
- Switched coupled system of nonlinear impulsive Langevin equations involving Hilfer fractional-order derivatives
- Improving the dynamic behavior of the plate under supersonic air flow by using nonlinear energy sink