Binary variational genetic programming for the problem of synthesis of control system

The paper describes a novel numerical symbolic regression method. It's called complete binary variational genetic programming. We use it for synthesis of optimal control. This method performs better than genetic programming at crossover, reduces the search area and speeds up search algorithm by using small variations. The efficiency of the new method is proven on the given example of control system synthesis for mobile robot. © 2017 IEEE.

Издательство
Institute of Electrical and Electronics Engineers Inc.
Язык
Английский
Страницы
186-191
Статус
Опубликовано
Год
2018
Организации
  • 1 Federal Research Centre 'Computer Science and Control', Russian Academy of Sciences, Academy of Engineering, RUDN University, Moscow, Russian Federation
  • 2 Academy of Engineering, RUDN University, Moscow, Russian Federation
Ключевые слова
genetic programming; optimal control; symbolic regression; synthesis of control
Дата создания
19.10.2018
Дата изменения
19.10.2018
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/6576/
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