Five phase multi-layer drive with fault tolerant neuro-fuzzy features for safety critical applications

Alessio Di Tullio, Marco Tursini, Francesco Parasiliti, Kan Akatsu

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

This article presents a method for control of a multiphase motor drive based on the use of a cognitive network that is capable of modelling nonlinearities of the system in fault conditions. To obtain a faithful model of the drive, a neural network (trained with the results of simulated faults) is used in the control algorithm in order to predict the system performance and adapt the control. A new multiphase motor with variable characteristics, particularly suited to applications in which a very wide variability of the speed range is required, will be described and presented in its structure. The technique to remedy failure adopted for this drive will be presented and described in its characteristics. The effectiveness of the control technique lastly will be highlighted by simulations that put it in comparison with classical solutions that employ PID controllers.

本文言語English
ホスト出版物のタイトル2017 20th International Conference on Electrical Machines and Systems, ICEMS 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781538632468
DOI
出版ステータスPublished - 2017 10 2
イベント20th International Conference on Electrical Machines and Systems, ICEMS 2017 - Sydney, Australia
継続期間: 2017 8 112017 8 14

Other

Other20th International Conference on Electrical Machines and Systems, ICEMS 2017
CountryAustralia
CitySydney
Period17/8/1117/8/14

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Control and Optimization

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