New estimations on fixed-time stabilization of delayed neural networks with event-triggered control

Guodong Zhang

doi:10.24294/pnmai6585

New estimations on fixed-time stabilization of delayed neural networks with event-triggered control

Guodong Zhang

Article ID: 6585
Vol 1, Issue 1, 2024

VIEWS - 39 (Abstract) 3 (PDF)

Abstract

New estimations on settling-time for fixed-time stabilization of nonlinear systems are derived. By using the new proposed results on fixed-time stable and designing proper effective event-triggered control (ETC), fixed-time stabilization (FTS) for a kind of delayed neural networks is investigated. The new estimations on settling-time for fixed-time stabilization can be used to discussed other systems, such as complex networks, multi-agent systems and so on. At last, example simulations are given to corroborate the effectiveness of the derived results.

Keywords

fixed-time stabilization; neural networks; distributed delays; event-triggered contro

Full Text:

PDF

References

1. Wen S, Zeng Z, Huang T, et al. Lag synchronization of switched neural networks via neural activation function and applications in image encryption. IEEE Trans. Neural Netw. Learn. Syst. 2015; 26(7): 1493–1502.

2. Sangiorgio M, Dercole F, Guariso G. Forecasting of noisy chaotic systems with deep neural networks. Chaos, Solitons & Fractals. 2021; 153(111570).

3. Li P, Gao R, Xu C, et al. Exploring the impact of delay on Hopf bifurcation of a type of BAM neural network models concerning three nonidentical delays. Neural Process. Lett. 2023; 55: 11595–11635.

4. Xu C, Zhao Y, Lin J, et al. Bifurcation investigation and control scheme of fractional neural networks owning multiple delays. Comput. Appl. Math. 2024; 43(186).

5. Phat VN, Trinh H. Exponential stabilization of neural networks with various activation functions and mixed timevarying delays. IEEE Trans. Neural Netw. 2010; 21(7): 1180–1184.

6. Wang L, Zeng Z, Zong X, Ge MF. Finite-time stabilization of memristor-based inertial neural networks with discontinuous activations and distributed delays. J. Franklin Inst. 2019; 356: 3628–3643 .

7. Zhang GD, Zeng ZG. Stabilization of second-order memristive neural networks with mixed time delays via nonreduced order. IEEE Trans. Neural Netw. Learn. Syst. 2020; 31(2): 700–706.

8. Polyakov A. Nonlinear feedback design for fixed-time stabilization of linear control systems. IEEE Trans. Autom. Control. 2012; 57: 2106–2110.

9. Hu C, Yu J, Chen Z, et al. Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks. Neural Netw. 2017; 89; 74–83.

10. Chen C, Li L, Peng H, et al. A new fixed-time stability theorem and its application to the synchronization control of memristive neural networks. Neurcomput. 2019; 349: 290–300, .

11. Zhang GD, Cao J. New results on fixed/predefined-time synchronization of delayed fuzzy inertial discontinuous neural networks: non-reduced order approach. Appl. Math. Comput. 2023; 440(127671).

12. Zhang GD, Cao J, Kashkynbayev A. Further results on fixed/preassigned-time projective lag synchronization control of hybrid inertial neural networks with time delays. J. Franklin Inst. 2023; 360: 9950–9973.

13. Wen S, Zeng Z, Chen MZQ, Huang T. Synchronization of switched neural networks with communication delays via the event-triggered control. IEEE Trans. Neural Netw. Learn. Syst. 2017; 28(10): 2334–2343.

14. Guo Z, Gong S, Wen S, Huang T. Event-based synchronization control for memristive neural networks with timevarying delay. IEEE Trans. Cybern. 2019; 49(9): 3268–3277, .

15. Chen J, Chen B, Zeng Z. Synchronization in multiple neural networks with delay and disconnected switching topology via event-triggered impulsive control strategy. IEEE Trans. Ind. Electron. 2021; 63(3): 2491–2500.

16. Zhang GD. Novel results on event-triggered-based fixed-time synchronization and stabilization of discontinuous neural networks with distributed delays. Franklin Open. 2023; 4(100032).

17. Khalil HK, Grizzle JW. Nonlinear Systems. Prentice-Hall Publishing; 2002.

DOI: https://doi.org/10.24294/pnmai6585