Speed control of DC Motor based on an adaptive feed forward neural IMC controller

被引：0

作者：

Zaineb, Ben Mabrouk ^{[1
]}

Aicha, Abid ^{[1
]}

Mouna, Ben Hamed

Lassaad, Sbita

机构：

[1] Natl Engn Sch Gabes, ENIG, Photovolta, Wind,Geothermal Syst Res Unit, Gabes, Tunisia

来源：

2017 INTERNATIONAL CONFERENCE ON GREEN ENERGY & CONVERSION SYSTEMS (GECS) | 2017年

关键词：

Internal Model Controller IMC; Artificial neural network; feed-forward neural network;

D O I：

暂无

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

This paper deals with the performance analysis of a robust neural controller applied to the DC motor for speed control. The robustness is guaranteed by the use of the Internal Model Controller (IMC). The IMC is based on the artificial Neural Network (ANN) principle. This paper proposes an adaptive neural controller methodology in the dc motor control and the results are compared with the performance of the feed-forward neural controller. Simulations results and experimental set up are presented to demonstrate the robustness of the speed controller under a wide range of load of the proposed schemes in a closed loop control. The effective results show that the performance of neural network control dc motor is improved by using adaptive neural network than the feed-forward neural network.

引用

页数：7

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