Real-time implementation of an on-line trained neural network controller for power electronics converters

Research output: Journal article publicationConference articleAcademic researchpeer-review

12 Citations (Scopus)

Abstract

Since power electronics converters behave nonlinear, conventional control strategies such as PID are incapable of obtaining good dynamical performance. This paper addresses to implement on-line trained neural networks for power electronics converters. A PWM boost converter is used for exemplification. Real-time implementation of the neutral networks is accomplished by using a powerful digital signal processor. The converter is operated as a power amplifier and a power regulator. Both computer simulation and experimental results show that good dynamical performance can be obtained.

Original languageEnglish
Pages (from-to)321-327
Number of pages7
JournalPESC Record - IEEE Annual Power Electronics Specialists Conference
Volume1
Publication statusPublished - 1994
EventProceedings of the 1994 25th Annual IEEE Power Electronics Specialists Conference. Part 2 (of 2) - Taipei, Taiwan
Duration: 20 Jun 199424 Jun 1994

ASJC Scopus subject areas

  • Modelling and Simulation
  • Condensed Matter Physics
  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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