DocumentCode :
1665581
Title :
Autonomous Self Commissioning Method for Speed Sensorless Controlled Induction Machines
Author :
Wolbank, T.M. ; Vogelsberger, M.A. ; Stumberger, R. ; Mohagheghi, S. ; Habetler, T.G. ; Harley, R.G.
Author_Institution :
Vienna Univ. of Technol., Vienna
fYear :
2007
Firstpage :
1179
Lastpage :
1185
Abstract :
Speed sensorless control of ac machines at zero speed so far is only possible using signal injection methods. Especially when applied to induction machines the spatial saturation leads to a dependence of the resulting control signals on the flux/load level. Usually this dependence has to be identified on a special test stand during a commissioning procedure for each type of induction machine. In this paper an autonomous commissioning method based on a neural network approach is proposed that does neither depend on a speed sensor present as a reference nor on a load dynamometer coupled to the machine and guaranteeing constant speed. The training data for the neural network is obtained using only acceleration and deceleration measurements of the uncoupled machine. The reliability of the proposed autonomous commissioning method is proven by measurement results. When comparing the resulting sensorless control performance, the proposed commissioning method reaches the same level of performance as a manual identification using load dynamometer as well as speed sensor.
Keywords :
angular velocity control; asynchronous machines; control engineering computing; electric machine analysis computing; machine control; neural nets; reliability; ac machines; autonomous self commissioning method; flux-load level; load dynamometer coupled; neural network approach; signal injection methods; speed sensorless controlled induction machines; Acceleration; Accelerometers; Anisotropic magnetoresistance; Frequency estimation; Induction machines; Mechanical sensors; Neural networks; Sensorless control; Shafts; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industry Applications Conference, 2007. 42nd IAS Annual Meeting. Conference Record of the 2007 IEEE
Conference_Location :
New Orleans, LA
ISSN :
0197-2618
Print_ISBN :
978-1-4244-1259-4
Electronic_ISBN :
0197-2618
Type :
conf
DOI :
10.1109/07IAS.2007.185
Filename :
4347934
Link To Document :
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