文献类型：期刊文献

中文题名：基于进化神经网络的BLDCM调速控制

英文题名：Speed adjusting control of BLDCM based on evolutionary neural networks

作者：宗磊[1];王行愚[1];邹俊忠[1]

机构：[1]华东理工大学信息科学与工程学院,上海200237

年份：2007

卷号：43

期号：8

起止页码：190

中文期刊名：计算机工程与应用

外文期刊名：Computer Engineering and Applications

收录：CSTPCD;;北大核心:【北大核心2004】；CSCD:【CSCD2011_2012】；

基金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.60543005/F0301);高等院校博士学科点专项科研基金(the China Specialized Research Fund for the Doctoral Program of Higher Education under Grant No.20040251010)

语种：中文

中文关键词：无刷直流电机;进化神经网络;遗传算法;BP网络;速度控制

外文关键词：BLDCM ;evolutionary neural network ; genetic algorithm ; BP network ; speed control

摘要：针对标准BP算法存在全局搜索能力弱和易陷入局部极小点等缺点,将遗传算法与BP神经网络相结合,构造了一种新的进化神经网络GA-BP算法,并将该算法应用于无刷直流电机调速系统的控制,仿真结果表明,与传统的PI控制系统相比,该算法得出的电机控制曲线几乎无超调,与基于BP算法的速度控制系统相比较,具有收敛速度快、不易陷入局部极小的优点。
Focusing on some disadvantages in standard BP algorithm,such as low convergence rate,easily falling into local minimum point and weak global search capability, Genetic algorithm is used to optimal the connection weight of BP algorithm in this paper,and construct a GA-BP algorithm of evolutionary neural network,and the algorithm is applied to the control of BLDCM speed adjusting system.The results of simulations show that contrast to the traditional PI control system it has the advantage of no surplus regulation.Contrast to BP algorithm, it has a high convergence rate and not easilv falling into local minimum point.