Parametric Identification of Control Systems Using Artificial Neural Networks

Parametric Identification of Control Systems Using Artificial Neural Networks

Bibliografski detalji
Parent link:MATEC Web of Conferences
Vol. 37 : Smart Grids 2015.— 2015.— [01064, 4 p.]
Glavni autor: Zakamaldin A. A. Andrey
Autor kompanije: Национальный исследовательский Томский политехнический университет (ТПУ) Энергетический институт (ЭНИН) Кафедра автоматизации теплоэнергетических процессов (АТП)
Daljnji autori: Andyk V. S. Vladimir Sergeevich
Sažetak:Title screen
For the problem of parametric identification of control objects proposed a method based on the use of artificial neural network feedforward type a perceptron. This method allows us to estimate the parameters of the mathematical model of the system with a maximum error of 2.8% and significantly reduce the time of the identification procedure.
Izdano: 2015
Teme:
электронный ресурс
труды учёных ТПУ
параметрическая идентификация
системы управления
искусственные нейронные сети
нейронные сети
Online pristup:http://dx.doi.org/10.1051/matecconf/20153701064
http://earchive.tpu.ru/handle/11683/32674
Format: Elektronički Poglavlje knjige
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=645694
Opis
Sažetak:Title screen
For the problem of parametric identification of control objects proposed a method based on the use of artificial neural network feedforward type a perceptron. This method allows us to estimate the parameters of the mathematical model of the system with a maximum error of 2.8% and significantly reduce the time of the identification procedure.
Digitalni identifikator objekta:10.1051/matecconf/20153701064

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