Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm

Shukurillo Usmonov

doi:doi:10.11648/j.mlr.20170202.13

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Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm

Shukurillo Usmonov

Published in Machine Learning Research (Volume 2, Issue 2)

Received: 31 January 2017 Accepted: 21 February 2017 Published: 9 March 2017

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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.

Published in	Machine Learning Research (Volume 2, Issue 2)
DOI	10.11648/j.mlr.20170202.13
Page(s)	61-65
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Frequency-Controlling Drive, Energy Save, Optimization, Genetic Algorithm

References

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[3]	I. J. Braslavsky. The optimization of star-up process in the system "Real network -PCH-AD" /I. YA. Braslavsky, AV Kostylёv, D. V. Tsibanov // Electric drives of AC: The works of the International scientific and technical fifteenth conference / Ural Federal University of the first President of Russia B. N. Yeltsin. Ekaterinburg, 2012. p 175-178.
[4]	Minakov I. A. Comparative analysis of some methods of random search and optimization // Bulletin of Samara Scientific Center of the Russian Academy of Sciences. 1999. №2. S.286-293.
[5]	Shonin O. B. Minimizing energy losses at the start of VFD based genetic optimization algorithm / Shonin O. B. Pron'ko V. S. // Notes Mining Institute. Volume 216, Saint-Petersburg 2015.
[6]	Krishnan R. Electric motor drives modeling, analysis and control. Upper Saddle River, NJ: Prenrice-Hall, 2001. 626p.
[7]	Herrera F., Lozano M., Sanchez A. M. Hybrid Crossover Operators for Real-Coded Genetic Algorithms: An Experimental Study. Soft Comput. 2005. N 9 (4), p. 280-298.
[8]	Thanga Raj C., Srivastava S. P., Pramod Agarwal. Energy Efficient Control of Three-Phase Induction Motor – A Review. International Journal of Computer and Electrical Engineering. 2009. Vol. 1. N 1, p. 61-71.
[9]	Anoufriev IE, Smirnov AB, Smirnova EN MATLAB 7.-SPb: BHV-Petersburg, 2005-1104: il.
[10]	Aripov N. M., Usmonov SH. YU. The development of energy-saving variable frequency induction motor with the fan load. Electrics. 2011. №4. from. 33-39.

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APA Style

Shukurillo Usmonov. (2017). Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm. Machine Learning Research, 2(2), 61-65. https://doi.org/10.11648/j.mlr.20170202.13

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ACS Style

Shukurillo Usmonov. Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm. Mach. Learn. Res. 2017, 2(2), 61-65. doi: 10.11648/j.mlr.20170202.13

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AMA Style

Shukurillo Usmonov. Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm. Mach Learn Res. 2017;2(2):61-65. doi: 10.11648/j.mlr.20170202.13

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@article{10.11648/j.mlr.20170202.13,
  author = {Shukurillo Usmonov},
  title = {Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm},
  journal = {Machine Learning Research},
  volume = {2},
  number = {2},
  pages = {61-65},
  doi = {10.11648/j.mlr.20170202.13},
  url = {https://doi.org/10.11648/j.mlr.20170202.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20170202.13},
  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.},
 year = {2017}
}

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TY  - JOUR
T1  - Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm
AU  - Shukurillo Usmonov
Y1  - 2017/03/09
PY  - 2017
N1  - https://doi.org/10.11648/j.mlr.20170202.13
DO  - 10.11648/j.mlr.20170202.13
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 61
EP  - 65
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20170202.13
AB  - 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.
VL  - 2
IS  - 2
ER  -

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Author Information

Shukurillo Usmonov

Department of Electro Technical, Electro Mechanical and Electro Technology, Faculty of Elector Engineering, Ferghana Polytechnic Institute (FerPI), Fergana, Uzbekistan

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APA Style

Shukurillo Usmonov. (2017). Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm. Machine Learning Research, 2(2), 61-65. https://doi.org/10.11648/j.mlr.20170202.13

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ACS Style

Shukurillo Usmonov. Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm. Mach. Learn. Res. 2017, 2(2), 61-65. doi: 10.11648/j.mlr.20170202.13

Copy | Download

AMA Style

Shukurillo Usmonov. Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm. Mach Learn Res. 2017;2(2):61-65. doi: 10.11648/j.mlr.20170202.13

Copy | Download

@article{10.11648/j.mlr.20170202.13,
  author = {Shukurillo Usmonov},
  title = {Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm},
  journal = {Machine Learning Research},
  volume = {2},
  number = {2},
  pages = {61-65},
  doi = {10.11648/j.mlr.20170202.13},
  url = {https://doi.org/10.11648/j.mlr.20170202.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20170202.13},
  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.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Optimization of the Launching Process in the Electric Drive with the Help of Genetic Algorithm
AU  - Shukurillo Usmonov
Y1  - 2017/03/09
PY  - 2017
N1  - https://doi.org/10.11648/j.mlr.20170202.13
DO  - 10.11648/j.mlr.20170202.13
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 61
EP  - 65
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20170202.13
AB  - 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.
VL  - 2
IS  - 2
ER  -

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