Fuzzy adaptive single neuron NN control of brushless DC motor

被引：7
|
作者：
Xiu, Jie [1 ]
Wang, Shiyu [2 ]
Xiu, Yan [3 ]
机构：
[1] Tianjin Univ, Sch Elect Engn & Automat, Tianjin 300072, Peoples R China
[2] Tianjin Univ, Sch Mech Engn, Tianjin 300072, Peoples R China
[3] Tianjin Inst Urban Construct, Dept Fundamental Subject, Tianjin 300384, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2013年 / 22卷 / 3-4期
基金：
中国国家自然科学基金;
关键词：
Brushless DC motor; Fuzzy logic system; Neural networks; Fuzzy adaptive single neuron neural networks controller;
D O I：
10.1007/s00521-011-0717-0
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码：607 / 613
页数：7
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