首页 | 本学科首页   官方微博 | 高级检索  
     检索      

用于机器手控制的动态模糊神经网络
引用本文:崔超,袁杰,郑晓东,何鹏.用于机器手控制的动态模糊神经网络[J].北京理工大学学报,2007,27(12):1094-1097.
作者姓名:崔超  袁杰  郑晓东  何鹏
作者单位:齐齐哈尔大学,应用技术学院,黑龙江,齐齐哈尔,161006;中央民族大学,数学与计算科学学院,北京,100081
摘    要:为解决模糊控制中存在的区域界定问题,将神经网络与模糊控制相结合,提出了一种新的模糊逻辑与神经网络相结合的动态模糊神经网络机器人控制方案(DFNN),并利用采样数据在线动态构造模糊神经系统.仿真结果表明,DFNN系统地很好地克服机器人系统中存在的非线性、不确定性、强耦合等因素的影响,控制效果好,为工业机器人控制提供了一种新的解决方案.

关 键 词:自适应模糊模型  机器人  模糊神经网络
文章编号:1001-0645(2007)12-1094-04
收稿时间:2007-06-28

Fuzzy Neural Network Controller for Robotic Manipulators
CUI Chao,YUAN Jie,ZHENG Xiao-dong and HE Peng.Fuzzy Neural Network Controller for Robotic Manipulators[J].Journal of Beijing Institute of Technology(Natural Science Edition),2007,27(12):1094-1097.
Authors:CUI Chao  YUAN Jie  ZHENG Xiao-dong and HE Peng
Institution:School of Applied Science and Technology,Qiqihaer University,Qiqihaer,Heilongjiang 161006,China;School of Mathematics and Computer Science,Central University for Nationalities,Beijing 100081,China;School of Applied Science and Technology,Qiqihaer University,Qiqihaer,Heilongjiang 161006,China;School of Applied Science and Technology,Qiqihaer University,Qiqihaer,Heilongjiang 161006,China
Abstract:General defining variables of dynamic fuzzy control systems for robotic manipulators are available within limited ranges. However, it is impossible to tackle with jobs above a limited range. Some clues to solve fuzzy control systems, after analysis, puts forward a new of means control combines nervous net with fuzzy control for robotic manipulators. Random information are gathered to design the fuzzy system. Final simulation results indicate that the DFNN model has fine intelligence performance when applied to robotic control, being able to overcome the effect of some factors, such as nonlinearity, uncertainty, strong coupling existing in robot systems.
Keywords:adaptive fuzzy model  robot  fuzzy neural network
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《北京理工大学学报》浏览原始摘要信息
点击此处可从《北京理工大学学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号