Practical synchronization of neural networks with delayed impulses and external disturbance via hybrid control.

Journal: Neural networks : the official journal of the International Neural Network Society
Published Date:

Abstract

This paper studies the problem of practical synchronization for delayed neural networks via hybrid-driven impulsive control in which delayed impulses and external disturbance are taken into account. Firstly, a switching method which establishes the relationship between error signals and a threshold function is introduced, which determines whether time-driven control or event-driven control is activated. Secondly, the effects of delayed impulses and external disturbance on impulsive systems are considered, and the corresponding comparison lemma is proposed. Thirdly, whenever the norm of the initial value of the error system state is less than or greater than the initial value of the threshold function, under the proposed hybrid-driven impulsive control scheme, the practical synchronization of the delayed neural networks with delayed impulses and external disturbance can be achieved by synchronizing impulses. Moreover, the Zeno behavior can be excluded under the proposed hybrid-driven impulsive control. Finally, two numerical examples are presented to verify the effectiveness of the theoretical results.

Authors

  • Shiyu Dong
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China. Electronic address: dsy_shiyu@163.com.
  • Xinzhi Liu
    Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1. Electronic address: xzliu@uwaterloo.ca.
  • Shouming Zhong
    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China; Key Laboratory for Neuroinformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China.
  • Kaibo Shi
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China. Electronic address: skbs111@163.com.
  • Hong Zhu
    Co-Innovation Center for the Sustainable Forestry in Southern China; Cerasus Research Center; College of Biology and the Environment, Nanjing Forestry University, Nanjing, China.