| 自学习模糊逻辑推理网络及模糊控制器的构成 |
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| 引用本文： | 张新学,王桂增,大町真一郎,阿曾弘具.自学习模糊逻辑推理网络及模糊控制器的构成[J].自动化学报,1999,25(5):687-691. |
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| 作者姓名： | 张新学 王桂增 大町真一郎 阿曾弘具 |
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| 作者单位： | 1.清华大学自动化系,北京; |
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| 基金项目： | 国家自然科学基金,留学生回国启动基金 |
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| 摘 要： | 提出了一种自学习模糊逻辑推理网络和自学习模糊控制器的构成方法.这种方法是
把RCE(Restricted Coulomb Energy)模型进行扩展.使其能够进行模糊逻辑推理,并用于构
成基于RCE模型的自学习模糊控制器RLFC(RCE—based Learning Fuzzy controller).这种
方法有以下特点:a)学习速度高.追加学习容易;b)网络的信息处理工作单元的个数由自学习
决定,通用性好;c)不存在局部极小点问题.自学习模糊控制器RLFC可以直接把熟练者的操
作知识转换成模糊控制规则,自动构成模糊控制器.数值仿真实验表明其效果良好.
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| 关 键 词： | 自学习网络 模糊控制 RCE模型 |
| 收稿时间： | 1998-2-18 |
FORMATION OF A LEARNING FUZZY LOGIC REASONING NETWORK AND A FUZZY CONTROLLER |
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| ZHANG Xinxue,WANG Guizeng,Omachi Shin′ichiro,Aso Hirotomoz.FORMATION OF A LEARNING FUZZY LOGIC REASONING NETWORK AND A FUZZY CONTROLLER[J].Acta Automatica Sinica,1999,25(5):687-691. |
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| Authors: | ZHANG Xinxue WANG Guizeng Omachi Shin′ichiro Aso Hirotomoz |
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| Affiliation: | 1.Department of Automation,Tsinghua University,Beijing;Faculty of Engineering,Tohoku University,Japan |
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| Abstract: | This paper presents an RLFC(RCE\|based learning fuzzy controller) which is capable of extracting expert knowledge automatically.The RLFC is an extended RCE(Restricted coulomb energy) model,hence it needs few iterations in learning and is easy for additional learning when control objects are changed.Moreover,the RLFC is capable of dealing with fuzzy sets and produces fuzzy control rules in a self\|organizing way from operational patterns of experts.The effectiveness of RLFC is shown by numerical simulation results. |
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| Keywords: | Learning network fuzzy control RCE model |
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