Mathematical Model of an Electromechanical Object Synthesized as Modified Recurrent Neural Networks

被引：0
|
作者：
Orlovskyi, Ihor [1 ]
机构：
[1] UTP Univ Sci & Technol, Dept Power Elect Elect Machines & Drives, Bydgoszcz, Poland
来源：
2017 INTERNATIONAL CONFERENCE ON MODERN ELECTRICAL AND ENERGY SYSTEMS (MEES) | 2017年
关键词：
electromechanical system; recurrent neural network; mathematical model;
D O I：
暂无
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Modified recurrent neural networks (MRNN) for the synthesis of linear and nonlinear mathematical models of electromechanical objects are presented. Methods have been developed for the synthesis of these networks, which use known data on the mathematical model of the object and methods for calculating and training neural networks based on the data of the object's operating mode. The proposed method has been verified for the DC-series motor models. The models with high accuracy with a small number of training periods have been confirmed.
引用
收藏
页码：292 / 295
页数：4
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