Оригинал (Original)
Автори: Костов, И. Й., Кирилов К., Цветков Ж.
Заглавие: ИЗПОЛЗВАНЕ НА ГЕНЕТИЧЕН АЛГОРИТЪМ ЗА НАМИРАНЕ ПАРАМЕТРИТЕ НА ЗАМЕСТВАЩАТА СХЕМА НА АСИНХРОНEН ДВИГАТЕЛ
Ключови думи: генетичен алгоритъм, целева функция, еквивалентна заместваща схема на АД

Абстракт: Разгледано е приложението на генетични алгоритми и целеви функции за идентификация на асинхронни двигатели (АД). Разработен е генетичен алгоритъм за определяне на параметри на заместващата схема на АД. Изследвано е влиянието на параметри на алгоритъма върху качеството на идентификационния процес. Алгоритмът е разработен за целите на управлението на АД. Ефективността на изследването е потвърдена чрез симулация.

Библиография

  1. Banan K., Sharifian M. и Mohammadi J., 2005, Induction Motor Efficiency Estimation using Genetic Algorithm, World Academy of Science, Engineering and Technology, том Vol.3, стр. стр. 2007
  2. Keki Burjorjee, 2000, A Vectorized Implementation of a Genetic Algorithm in Matlab, Brandeis University, Waltham, 2000, <Computer Science Department>, Computer Science Department
  3. Chambers L., 2001, A Hands Book For Practical Genetic Algorithmns, NY, CRC Press
  4. Herrera F., Lozano M. и Sanchez A., 2003, A Taxonomy for the Crossover Operator, e-book, Granada, Department of Computer Science and Artificial Intelligence, University of Granada, <https://www.waset.org/journals/waset/v3/v3-124.pdf>, Дата на последен преглед (Last accessed on): 08.01.2003
  5. Melanie M., 1999, An Introduction to Genetic Algorithms, 5, The MIT Press, A Bradford Book
  6. Michalewicz Z., 1996, Genetic Algoritms + Data Structures = Evolution Programs, NY, Springer-Verlag
  7. T. Phumiphak and C. Chatuthai, 2002, Estimation of Induction Motor Parameters Based on Field Test Coupled with Genetic Algorithm, Int. Conf. Power System Technology 2002 (PowerCon 2002), pp.1199-1203, 2002, <Kunming, China>, Yunnan science
  8. Randy L. Haupt, Sue Ellen Haupt, 2004, Practical Genetic Algorithmns, 2, NY, John Wiley & Sons, Inc
  9. Rothlauf F., 2006, Representations for Genetic and Evolutionary Algorithms, Berlin, Springer-Verlag
  10. Sastry R. и Orriols-Puig, 2007, A Extended Compact Genetic Algorithm in Matlab, University of Illinois, 2007, <University of Illinois at Urbana-Champaign>, University of Illinois at Urbana-Champaign
  11. Sivanandam S. N и Deepa S., 2008, Introduction to Genetic Algorithms, Berlin, Springer-Verlag
  12. Whitley D., 1950, A Genetic Algorithm Tutorial, e-book, Computer Scince Depatment, Colorado State University, <http://www.cs.colostate.edu/~genitor/MiscPubs/tutorial.pdf>, Дата на последен преглед (Last accessed on): 08.01.2013
  13. Yapa N., 2004, Genetic Algorithms in Induction Motor Efficiency Determination, Clarkson University, Clarkson University

Издание

Федерация “Наука и висше образование” – Пловдив Технически университет – София, филиал Пловдив III-та национална научна конференция 2009 за студенти, докторанти и млади научни работници, стр. стр. 99-108, 2009, България, Пловдив, Имеон, ISBN 978-954-9449-25-9

Пълен текст на публикацията

Autors: Kostov, I. J., Kirilov K., Tsvetkova J.
Title: APPLICATION OF OBJECTIVE FUNCTIONS AND GENETIC ALGORITHMS FOR INDUCTION MOTOR
Keywords: genetic algorithms, objective functions, equivalent AC circuit

Abstract: A classification of genetic algorithms (GA) and objective functions of AC motor has been made. It includes a GA for parameter estimation of the equivalent AC circuit. The algorithm parameter impact on the identification process precision has been investigated. This algorithm is aimed at the AC drive control. A computer simulation confirms the effectives of this approach.

References

  1. Banan K., Sharifian M. и Mohammadi J., 2005, Induction Motor Efficiency Estimation using Genetic Algorithm, World Academy of Science, Engineering and Technology, том Vol.3, стр. стр. 2007
  2. Keki Burjorjee, 2000, A Vectorized Implementation of a Genetic Algorithm in Matlab, Brandeis University, Waltham, 2000, <Computer Science Department>, Computer Science Department
  3. Chambers L., 2001, A Hands Book For Practical Genetic Algorithmns, NY, CRC Press
  4. Herrera F., Lozano M. и Sanchez A., 2003, A Taxonomy for the Crossover Operator, e-book, Granada, Department of Computer Science and Artificial Intelligence, University of Granada, <https://www.waset.org/journals/waset/v3/v3-124.pdf>, Дата на последен преглед (Last accessed on): 08.01.2003
  5. Melanie M., 1999, An Introduction to Genetic Algorithms, 5, The MIT Press, A Bradford Book
  6. Michalewicz Z., 1996, Genetic Algoritms + Data Structures = Evolution Programs, NY, Springer-Verlag
  7. T. Phumiphak and C. Chatuthai, 2002, Estimation of Induction Motor Parameters Based on Field Test Coupled with Genetic Algorithm, Int. Conf. Power System Technology 2002 (PowerCon 2002), pp.1199-1203, 2002, <Kunming, China>, Yunnan science
  8. Randy L. Haupt, Sue Ellen Haupt, 2004, Practical Genetic Algorithmns, 2, NY, John Wiley & Sons, Inc
  9. Rothlauf F., 2006, Representations for Genetic and Evolutionary Algorithms, Berlin, Springer-Verlag
  10. Sastry R. и Orriols-Puig, 2007, A Extended Compact Genetic Algorithm in Matlab, University of Illinois, 2007, <University of Illinois at Urbana-Champaign>, University of Illinois at Urbana-Champaign
  11. Sivanandam S. N и Deepa S., 2008, Introduction to Genetic Algorithms, Berlin, Springer-Verlag
  12. Whitley D., 1950, A Genetic Algorithm Tutorial, e-book, Computer Scince Depatment, Colorado State University, <http://www.cs.colostate.edu/~genitor/MiscPubs/tutorial.pdf>, Дата на последен преглед (Last accessed on): 08.01.2013
  13. Yapa N., 2004, Genetic Algorithms in Induction Motor Efficiency Determination, Clarkson University, Clarkson University

Issue

Федерация “Наука и висше образование” – Пловдив Технически университет – София, филиал Пловдив III-та национална научна конференция 2009 за студенти, докторанти и млади научни работници, pp. 99-108, 2009, Bulgaria, Plovdiv, Imeon, ISBN 978-954-9449-25-9

Full text of the publication

Вид: публикация в национален форум