NDLI: Effective identification of induction motor parameters based on fewer measurements

Content Provider	IEEE Xplore Digital Library
Author	Huang, K.S. Wu, Q.H. Turner, D.R.
Copyright Year	1986
Abstract	This paper applies genetic algorithms (GAs) to the problem of parameter identification for field orientation control (FOC) induction motors. Kron's two-axis dynamic model in per-unit system is given, and the model's parameters are estimated by a GA using the motor's dynamic response to a direct on line start. Results with different levels of measurement noise are presented for the model both in the per-unit system and in actual values. For comparison, the results of a simple random search (SRS) method under the same condition are also given. The results show that the parameter identification accuracy, the convergence speed and the practicality of the algorithm have been improved significantly by use of the model in the per-unit system. The results also show that fewer measurements are required to identify the induction motor parameters accurately.
Sponsorship	IEEE Power Engineering Society
Starting Page	55
Ending Page	60
Page Count	6
File Size	137154
File Format	PDF
ISSN	08858969
Volume Number	17
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Induction motors Rotors Parameter estimation Position control Degradation Circuit testing Inductance Q measurement Genetic algorithms Noise measurement
Content Type	Text
Resource Type	Article
Subject	Energy Engineering and Power Technology Electrical and Electronic Engineering

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