DocumentCode :
581487
Title :
Enhanced discrete time model for AC induction machine model predictive control
Author :
Vaclavek, Pavel ; Blaha, Petr
Author_Institution :
Fac. of Electr. Eng. & Commun., Brno Univ. of Technol., Brno, Czech Republic
fYear :
2012
fDate :
25-28 Oct. 2012
Firstpage :
5043
Lastpage :
5048
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 :
constraint handling; discrete time systems; induction motor drives; machine vector control; predictive control; reliability; AC induction machine model predictive control; AC induction motor drive; constraint handling; construction reliability; controller hardware; discrete time model enhancement; motion control application; prediction horizon length; vector control method; Computational modeling; Europe; Induction motors; Lead; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Conference_Location :
Montreal, QC
ISSN :
1553-572X
Print_ISBN :
978-1-4673-2419-9
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2012.6389564
Filename :
6389564
Link To Document :
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