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Fuzzy adaptive single neuron NN control of brushless DC motor

机译:无刷直流电动机的模糊自适应单神经元神经网络控制

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摘要

Inherently, the brushless DC motor (BLDCM) is a nonlinear plant. So, it is hard to get a good performance by using the conventional PI controller for the speed control of BLDCM. In this paper, a fuzzy adaptive single neuron neural networks (NN) controller for BLDCM is developed. The fuzzy logic system (FLS) is adopted to adjust the parameter K of single neuron NN controller online. By this way, performance of the system can be improved. Performances of the proposed fuzzy adaptive single neuron NN controller are compared with the performances of conventional PI controller and normal single neuron NN controller. The experimental results demonstrate that a good control performance is achieved. The using of fuzzy adaptive single neuron NN makes the drive system robust, accurate, and insensitive to parameter variations.
机译:本质上,无刷直流电动机(BLDCM)是非线性设备。因此,使用传统的PI控制器进行BLDCM的速度控制很难获得良好的性能。本文开发了一种用于BLDCM的模糊自适应单神经元神经网络(NN)控制器。采用模糊逻辑系统(FLS)在线调节单个神经元NN控制器的参数K。通过这种方式,可以改善系统的性能。将提出的模糊自适应单神经元NN控制器的性能与常规PI控制器和普通单神经元NN控制器的性能进行了比较。实验结果表明获得了良好的控制性能。模糊自适应单神经元NN的使用使驱动系统鲁棒,准确且对参数变化不敏感。

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