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用于机器手控制的在线的自组织模糊神经网络
引用本文:郑晓东,石岩,刘树东,肖新莲. 用于机器手控制的在线的自组织模糊神经网络[J]. 齐齐哈尔大学学报(自然科学版), 2007, 23(2): 57-61
作者姓名:郑晓东  石岩  刘树东  肖新莲
作者单位:齐齐哈尔大学计算机与控制工程学院,黑龙江,齐齐哈尔,161006;齐齐哈尔大学计算机与控制工程学院,黑龙江,齐齐哈尔,161006;齐齐哈尔大学计算机与控制工程学院,黑龙江,齐齐哈尔,161006;齐齐哈尔大学计算机与控制工程学院,黑龙江,齐齐哈尔,161006
摘    要:基于动态自适应方法,本文提出了一种能动态生成自组织模糊神经网络(SOFNN)的新算法,并应用该算法能有效地估计机器手的非线性。本算法能自动划分输入输出空间,自学习调整高斯函数,模糊规则的构造及空间的划分数目是并行调整的。这个SOFNN算法的独特之处是:自组织动态结构、快速的学习能力,良好的鲁棒性。一个两自由度的工业机械手验证了其有效性。

关 键 词:自组织  模糊神经网络  机械手
文章编号:1007-984X(2007)01-0057-05
修稿时间:2006-12-10

An on-line self-organizing fuzzy neural neworks for the control of the robotic manipulators
ZHENG Xiao-dong,SHI Yan,LIU Shu-dong,XIAO Xin-lian. An on-line self-organizing fuzzy neural neworks for the control of the robotic manipulators[J]. Journal of Qiqihar University(Natural Science Edition), 2007, 23(2): 57-61
Authors:ZHENG Xiao-dong  SHI Yan  LIU Shu-dong  XIAO Xin-lian
Affiliation:College of Computer and Control Engineering,Qiqihar University,Heilongjiang Qiqihar 161006,China
Abstract:In this paper,based on the dynamic adaptation method a new algorithm for creating a self-organizing fuzzy neural networks(SOFNN),which is implemented to estimate to estimate the uncertainty of the robotic manipulators.The SOFNN can partition the input-output space dynamically,self-learn the Gaussian-type membership functions.Both the number of partitions and their corresponding fuzzy rule configuration are simultaneously and concurrently adaptively.The unique feature of this SOFNN is that it has dynamic self-organizing structure,fast learning speed,good generalization,which is demonstrated on simulation of a two-link robotic manipulators.
Keywords:self-organizing  fuzzy-neural networks  robotic manipulators
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