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山东大学学报(工学版) ›› 2010, Vol. 40 ›› Issue (2): 28-33.

• 控制科学与工程 • 上一篇    下一篇

基于模糊神经网络的移动机器人自适应行为设计

李贻斌1,李彩虹1,2,宋勇1   

  1. 1. 山东大学控制科学与工程学院, 山东 济南 250061; 2. 山东理工大学计算机科学与技术学院, 山东 淄博 255049
  • 收稿日期:2009-09-10 出版日期:2010-04-16 发布日期:2009-09-10
  • 作者简介:李贻斌(1960-),男,山东聊城人,教授,博士,主要研究方向为移动机器人,机器人控制等.E-mail: liyb@sdu.edu.cn
  • 基金资助:

    国家自然科学基金资助项目(60675044);山东省自然科学基金资助项目(Z2007G02,Y2007G52)

Adaptive behavior design based on FNN for the mobile robot

LI Yi-bin1, LI Cai-hong1,2, SONG Yong1   

  1. 1. School of Control Science and Engineering, Shandong University, Jinan 250061, China;
    2. School of Computer Science and Technology, Shandong University of Technology, Zibo 255049, China
  • Received:2009-09-10 Online:2010-04-16 Published:2009-09-10

关键词: 移动机器人, 模糊神经网络, 适应行为, 模糊控制规则

Abstract:

The fuzzy neural network (FNN) controller was formed by combining the fuzzy control and the neural networks. The fuzzy rules were collected automatically by reinforcement Q-Learning (QL) on-line beforehand. The rules were  implicitly stored in the FNN after the off-line training. In control applications, the complex search and inference of the rules were unnecessary, and the best adaptive behavior could be produced in the output without looking up the table. The simulation results show that because all training samples are from the trained fuzzy rules, the output is almost the same as the result of the training rules.
 

Key words: mobile robot, fuzzy neural network, adaptive behavior; , fuzzy control rules

[1] 严宣辉, 肖国宝*. 基于定长实数路径编码机制的移动机器人路径规划[J]. 山东大学学报(工学版), 2012, 42(1): 59-65.
[2] 田国会,张涛涛*,吴皓,薛英花,周风余. 基于分布式导航信息的大范围环境机器人导航[J]. 山东大学学报(工学版), 2011, 41(1): 24-31.
[3] 牛君,李贻斌,宋锐 . 一种基于激光信息的移动机器人两步自定位方法[J]. 山东大学学报(工学版), 2007, 37(3): 46-50 .
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