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Reducing induction motor identified parameters using a nonlinear Lasso method
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DOI：10.1016/j.epsr.2012.01.011.png)
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Abstract
En 中文
Reliable induction motor modeling is critical in power system planning and operation. This paper considers the identifiability of induction motor parameters, with a particular emphasis placed on using subset selection and shrinkage methods to allow the identification methods to focus on the most significant parameters. The proposed approach is validated using experimental data and the results found are compared to those of a recently proposed method based on sensitivity analysis. (C) 2012 Elsevier B.V. All rights reserved.
Keywords:
Nonlinear system identification
Induction motor
Term selection methods
Journal
IF:
4.2
Papers:
1.1W
Citations:
2.2W
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