Volume 2, Issue 2, June 2017, Page: 61-65
Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm
Shukurillo Usmonov, Department of Electro Technical, Electro Mechanical and Electro Technology, Faculty of Elector Engineering, Ferghana Polytechnic Institute (FerPI), Fergana, Uzbekistan
Received: Jan. 31, 2017;       Accepted: Feb. 21, 2017;       Published: Mar. 9, 2017
DOI: 10.11648/j.mlr.20170202.13      View  1212      Downloads  43
Abstract
In the terms of limited resources and rise of energy prices, one of the most priority directions of modern research is increasing the energy efficiency of electric drives, which are widely used in industrial enterprises. The present methods of minimizing losses are designed for stationary modes. Little attention is paid to the development of algorithms of reducing losses in transition modes. Owing to high complexity of multivariate dynamic processes of optimal control laws, it is advisable to carry out with the help of stochastic optimization techniques. The particularity of the proposed method of optimization is multiple simulation of the used drive in order to find the start-up characteristics, where minimum of energy losses is provided. Automation of search was performed with the help of developed program, which contains the genetic algorithm module and linking module with the electric drive model in Matlab/Simulink environment. The program allows you to select the parameters of the genetic algorithm and control process of optimization.
Keywords
Frequency-Controlling Drive, Energy Save, Optimization, Genetic Algorithm
To cite this article
Shukurillo Usmonov, Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm, Machine Learning Research. Vol. 2, No. 2, 2017, pp. 61-65. doi: 10.11648/j.mlr.20170202.13
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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