NDLI: Parameter Estimation Optimization Based on Genetic Algorithm Applied to DC Motor

Content Provider	IEEE Xplore Digital Library
Author	Lankarany, M. Rezazade, A.
Copyright Year	2007
Description	Author affiliation: Shahid Beheshti Univ. of Iran, Tehran (Lankarany, M.; Rezazade, A.)
Abstract	Thin paper proposed the application of genetic algorithm optimization in estimating the parameters of dynamic state of DC motor. LSE estimation is considered as a convenient method for parameter estimation, in comparison with this proposed method. Despite of LSE estimation that is based on the linearity of error function due to parameters, GA method can easily identify unknown parameters by minimizing the sum of squared errors. GA is imported in comparison with conventional optimization methods because of its power in searching entire solution space with more probability of finding the global optimum. Also the model can be nonlinear with respect to parameters, and in this identification free noise system is assumed and transient excitation is considered instead of persistent excitation. Finally comparison between LSE and GA optimization is presented to indicate robustness and resolution of GA identification method in parameter estimation.
Starting Page	1
Ending Page	6
File Size	439366
Page Count	6
File Format	PDF
ISBN	142440892X
DOI	10.1109/ICEE.2007.4287313
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-11
Publisher Place	Pakistan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parameter estimation Optimization methods DC motors Parametric statistics System identification Least squares approximation State estimation Biological cells Genetic algorithms Recursive estimation
Content Type	Text
Resource Type	Article

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