Event-Triggered Control for Robust Exponential Synchronization of Inertial Memristive Neural Networks Under Parameter Disturbance

Wei Yao, Chunhua Wang, Yichuang Sun, Shuqing Gong, Hairong Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Synchronization of memristive neural networks (MNNs) by using network control scheme has been widely and deeply studied. However, these researches are usually restricted to traditional continuous-time control methods for synchronization of the first-order MNNs. In this paper, we study the robust exponential synchronization of inertial memristive neural networks (IMNNs) with time-varying delays and parameter disturbance via event-triggered control (ETC) scheme. First, the delayed IMNNs with parameter disturbance are changed into first-order MNNs with parameter disturbance by constructing proper variable substitutions. Next, a kind of state feedback controller is designed to the response IMNN with parameter disturbance. Based on feedback controller, some ETC methods are provided to largely decrease the update times of controller. Then, some sufficient conditions are provided to realize robust exponential synchronization of delayed IMNNs with parameter disturbance via ETC scheme. Moreover, the Zeno behavior will not happen in all ETC conditions shown in this paper. Finally, numerical simulations are given to verify the advantages of the obtained results such as anti-interference performance and good reliability.
Original languageEnglish
Pages (from-to)67-80
Number of pages14
JournalNeural Networks
Volume164
Early online date26 Apr 2023
DOIs
Publication statusPublished - 4 May 2023

Keywords

  • Event-triggered control
  • Inertial memristive neural networks
  • Parameter disturbance
  • Robust exponential synchronization

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