Neural Network Control of a Frequency-Regulated Electric Drive of a Main Electric Locomotive

Autor:	Yurij Kutovoj, Ihor Obruch, Tatiana Kunchenko, Yaroslav Kyrylenko
Rok vydání:	2020
Předmět:	Nonlinear system Artificial neural network Computer science Electric locomotive Genetic algorithm Process (computing) Control engineering Transient (oscillation) Realization (systems) Induction motor
Zdroj:	2020 IEEE Problems of Automated Electrodrive. Theory and Practice (PAEP).
DOI:	10.1109/paep49887.2020.9240880
Popis:	The paper presents the results of the development and investigations of an intelligent control system for an electric drive (ED) of the main-line electric locomotive DS3. It is shown that the use of methods of genetic algorithms for training and structural optimization of neural systems makes it possible to synthesize the control law excluding the self-oscillating process arising from the nonlinearity of the “friction pair” type load. The developed systems have a single easily realizable feedback on the speed of the motor which does not create difficulties in physical realization.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::eddabf1b952cff67b972cbf387d764f6 https://doi.org/10.1109/paep49887.2020.9240880 Zobrazit plný text záznamu