Event-Based Impulsive Control of Continuous-Time Dynamic Systems and Its Application to Synchronization of Memristive Neural Networks

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

Detail(s)

Original languageEnglish
Article number8013106
Pages (from-to)3599-3609
Number of pages11
Journal / PublicationIEEE Transactions on Neural Networks and Learning Systems
Volume29
Issue number8
Online published18 Aug 2017
Publication statusPublished - Aug 2018

Abstract

This paper investigates exponential stabilization of continuous-time dynamic systems (CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants are determined by certain state-dependent triggering condition. The global exponential stability criteria via EIC are derived for nonlinear and linear CDSs, respectively. It is also shown that there is no Zeno-behavior for the concerned closed loop control system. In addition, the developed event-based impulsive scheme is applied to the synchronization problem of master and slave memristive neural networks. Furthermore, a self-triggered impulsive control scheme is developed to avoid continuous communication between the master system and slave system. Finally, two numerical simulation examples are presented to illustrate the effectiveness of the proposed event-based impulsive controllers.

Research Area(s)

  • Synchronization, Zeno-behavior, Event-based impulsive control (EIC), exponential stability, memristive neural networks

Citation Format(s)

Event-Based Impulsive Control of Continuous-Time Dynamic Systems and Its Application to Synchronization of Memristive Neural Networks. / Zhu, Wei; Wang, Dandan; Liu, Lu et al.
In: IEEE Transactions on Neural Networks and Learning Systems, Vol. 29, No. 8, 8013106, 08.2018, p. 3599-3609.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review