Comparison between linear- and nonlinear-feedback control for a synchronous reluctance machine

Anton H. Tamas, Claudia S. Martis, Simon Wiedemann, Ralph M. Kennel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a performance comparison of feedback linearization and field oriented control for a synchronous reluctance machine. In order to represent realistic drive performance and dynamics, look-up tables of the machine inductances as a function of currents are used to include saturation effect. Additionally, a trained neural network was implemented to take the nonlinear behavior of the voltage source inverter into consideration. For a fair comparison between both methods, a genetic algorithm has been used for optimization of the controller settings. A linear model of the synchronous reluctance machine has been obtained after the nonlinearities are canceled through the feedback linearization where the dynamics of the machine are dictated by a reference plant model.

Original languageEnglish
Title of host publicationProceedings - 2017 IEEE International Symposium on Industrial Electronics, ISIE 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages244-251
Number of pages8
ISBN (Electronic)9781509014125
DOIs
StatePublished - 3 Aug 2017
Event26th IEEE International Symposium on Industrial Electronics, ISIE 2017 - Edinburgh, Scotland, United Kingdom
Duration: 18 Jun 201721 Jun 2017

Publication series

NameIEEE International Symposium on Industrial Electronics

Conference

Conference26th IEEE International Symposium on Industrial Electronics, ISIE 2017
Country/TerritoryUnited Kingdom
CityEdinburgh, Scotland
Period18/06/1721/06/17

Keywords

  • Feedback Linearization
  • Field Oriented Control
  • Genetic Algorithm
  • Machine Modelling
  • Machine Testing
  • Neural Network
  • Synchronous Reluctance Machine

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