Finite-time synchronization of nonidentical neural networks with time-varying delay based on integral sliding mode control

被引：0
|
作者：
Xiong J.-J. [1 ,2 ]
Zhang G.-B. [1 ,2 ]
机构：
[1] School of Automation, Southeast University, Nanjing
[2] Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education, Southeast University, Nanjing
来源：
Kongzhi yu Juece/Control and Decision | 2019年 / 34卷 / 07期
关键词：
Delayed neural networks; Finite-time synchronization; Integral sliding mode control; Lyapunov method;
D O I：
10.13195/j.kzyjc.2017.1689
中图分类号：
学科分类号：
摘要：
The finite-time synchronization problem of a class of nonidentical neural networks with time-varying delay is studied. Firstly, by using the drive-response concept to derive an error system, a suitable integral sliding mode manifold is constructed by applying the synchronization error. If the state trajectories of the error system are driven onto the sliding mode surface, the synchronization error will thereafter converge to zero in finite time. Then, by combining the bounded conditions on neuron activation functions, a proper sliding mode controller is designed. Based on the designed controller and the Lyapunov stability theory, the state trajectories of the error system can be driven onto the sliding mode surface, such that the finite-time synchronization of nonidentical neural networks with time-varying delay can be performed. Finally, numerical simulation results verify the effectiveness of the proposed method. © 2019, Editorial Office of Control and Decision. All right reserved.
引用
收藏
页码：1559 / 1564
页数：5
相关论文
共 29 条
  • [1] Cao J.D., Chen G.R., Li P., Global synchronization in an array of delayed neural networks with hybrid coupling, IEEE Trans on Systems, Man, and Cybernetics-Part B: Cybernetics, 38, 2, pp. 488-498, (2008)
  • [2] Li T., Song A.G., Fei S.M., Synchronization control of chaotic neural networks with time-varying and distributed delays, Nonlinear Analysis, 71, 5, pp. 2372-2384, (2009)
  • [3] Lam H.K., Chaotic synchronization using output/full state-feedback polynomial controller, IET Control Theory and Applications, 4, 11, pp. 2285-2292, (2010)
  • [4] Gan Q., Synchronization of chaotic neural networks with unknown parameters and random time-varying delays based on adaptive sampled-data control and parameter identification, IET Control Theory and Applications, 6, 10, pp. 1508-1515, (2012)
  • [5] Rakkiyappan R., Dharani S., Cao J.D., Synchronization of neural networks with control packet loss and time-varying delay via stochastic sampled-data controller, IEEE Trans on Neural Networks and Learning Systems, 26, 12, pp. 3215-3226, (2015)
  • [6] Gan Q.T., Xu R., Kang X.B., Synchronization of unknown chaotic delayed competitive neural networks with different time scales based on adaptive control and parameter identification, Nonlinear Dynamics, 67, 3, pp. 1893-1902, (2012)
  • [7] Wang L.M., Shen Y., Yin Q., Adaptive synchronization of memrisor-based neural networks with time-varying delays, IEEE Trans on Neural Networks and Learning Systems, 26, 9, pp. 2033-2042, (2015)
  • [8] Li J.M., He C., Zhang W.Y., Adaptive synchronization of delayed reaction-diffusion neural networks with unknown non-identical time-varying coupling strengths, Neurocomputing, 219, pp. 144-153, (2017)
  • [9] Li X.D., Song S.J., Research on synchronization of chaotic delayed neural networks with stochastic perturbation using impulsive control method, Communications in Nonlinear Science and Numerical Simulation, 19, 10, pp. 3892-3900, (2014)
  • [10] Chen W.H., Lu X.M., Zheng W.X., Impulsive stabilization and impulsive synchronization of discrete-time delayed neural networks, IEEE Trans on Neural Networks and Learning Systems, 26, 4, pp. 734-748, (2015)
123