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

B. Zaineb, A. Aicha, B. Mouna, S. Lassâad
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引用次数: 12

Abstract

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 feedforward 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.
基于自适应前馈神经IMC控制器的直流电机速度控制
本文研究了一种用于直流电机速度控制的鲁棒神经控制器的性能分析。采用内模控制器(IMC)保证了系统的鲁棒性。IMC基于人工神经网络(ANN)原理。本文提出了一种用于直流电机控制的自适应神经控制器方法,并与前馈神经控制器的性能进行了比较。仿真结果和实验结果表明,所提出的速度控制器在闭环控制的大范围负载下具有鲁棒性。实验结果表明,采用自适应神经网络比采用前馈神经网络能更好地控制直流电动机。
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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