Result Details

Enhanced Discrete Time Model for AC Induction Machine Model Predictive Control

VÁCLAVEK, P.; BLAHA, P. Enhanced Discrete Time Model for AC Induction Machine Model Predictive Control. In Proceedings of the IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society. Kanada: IEEE, 2012. p. 5025-5030. ISBN: 978-1-4673-2420-5.
Type
conference paper
Language
English
Authors
Václavek Pavel, prof. Ing., Ph.D., RG-2-02 (CEITEC), UAMT (FEEC)
Blaha Petr, doc. Ing., Ph.D., RG-2-02 (CEITEC), UAMT (FEEC)
Abstract

AC induction motors became very popular for motion control applications due to their simple and reliable construction. Control of drives based on AC induction motors is a quite complex task. In most high-performance applications classical vector control is currently used. While this control method is usually reliable it has some limitations especially in controllers tuning and constraints handling. New control methods like Model Predictive Control become feasible in connection with increasing computational power of controller hardware. The paper deals with enhanced discrete time AC induction machine model which can be used for efficient predictive control implementation. The other objective of the paper is discussion of prediction horizon length on the drive control performance.

Keywords

induction machine, predictive control, model

Published
2012
Pages
5025–5030
Proceedings
Proceedings of the IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Conference
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
ISBN
978-1-4673-2420-5
Publisher
IEEE
Place
Kanada
UT WoS
000316962904152
BibTeX 
@inproceedings{BUT94654,
  author="Pavel {Václavek} and Petr {Blaha}",
  title="Enhanced Discrete Time Model for AC Induction Machine Model Predictive Control",
  booktitle="Proceedings of the IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society",
  year="2012",
  pages="5025--5030",
  publisher="IEEE",
  address="Kanada",
  isbn="978-1-4673-2420-5"
}
Departments
Cybernetics in Material Science (RG-2-02)
Department of Control and Instrumentation (UAMT)
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