基于人工神经网络的异步电动机直接转矩控制采用MRAS和神经PID控制器进行速度控制

2015 IEEE Electrical Power and Energy Conference (EPEC) Pub Date : 2015-10-01 DOI:10.1109/EPEC.2015.7379970

M. L. Zegai, M. Bendjebbar, K. Belhadri, M. Doumbia, B. Hamane, P. M. Koumba

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引用次数: 13

摘要

这篇文章讨论了利用人工神经网络(ANN)来提高感应电机(IM)直接转矩控制(DTC)系统性能的建议。采用模型参考自适应系统(MRAS)方法对转子转速进行估计和调节。采用Matlab/Simulink设计了DTC的整体结构。利用神经工具箱设计了神经控制器，并与传统的直接转矩控制系统进行了性能比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Direct torque control of Induction Motor based on artificial neural networks speed control using MRAS and neural PID controller

This contribution deals with the proposal of direct torque control (DTC) for Induction Motor (IM) with the use of artificial neural networks (ANN) to increase the system's performance. Model Reference Adaptive System (MRAS) method is used for the estimation and regulation of rotor's speed. The whole structure of DTC is designed by Matlab/Simulink. The neural controller is designed using neural Toolbox, and the system's performance is compared with conventional DTC.

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2015 IEEE Electrical Power and Energy Conference (EPEC)

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