Prescribed performance synchronization of neural networks with impulsive effects

Zhining Wang, Aili Fan, Youming Lei, Yating Wang, Lin Du

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this paper, the prescribed performance synchronization problem is addressed for a class of neural networks with impulsive effects. According to the prescribed performance control principle and the Lyapunov’s second stability theorem, a preset performance control protocol is designed. For neural networks with impulsive effects, the proposed control scheme can not only guarantee the steady-state performance of synchronization errors, but also ensure the transient performance of the synchronization process. This improves the performance of the neural networks effectively. Finally, a numerical simulation is given to illustrate the effectiveness and feasibility of the proposed control scheme.

Original languageEnglish
Pages (from-to)12587-12593
Number of pages7
JournalSoft Computing
Volume27
Issue number17
DOIs
StatePublished - Sep 2023

Keywords

  • Impulsive effects
  • Neural networks
  • Prescribed performance
  • Synchronization

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