ニューラルネットワークによるファジィ制御器の学習について

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タイトル ( jpn )
ニューラルネットワークによるファジィ制御器の学習について
タイトル ( eng )
On Learning of Fuzzy Contoller with Neural Network
作成者
水上 孝一
普家 浩文
寄与者 国立情報学研究所
収録物名
広島大学総合科学部紀要. IV, 理系編
Memoirs of the Faculty of Integrated Arts and Sciences, Hiroshima University. IV, Science reports
21
開始ページ 81
終了ページ 91
抄録
The fuzzy controller (FC) consists of two parts. First one is the control rule part which is referred to as linguistic rules. And it is written in the form of 'If∿THEN∿'. Second one is fuzzy reasoning which derives the reasoning value from the control rules. So it is easy for us to understand FC. However, there are two problems. First one is how to make the control rules. We usually take the rules from an expert. But it is not easy. Because all rules which the extpert has are not linguistic rules. The neural network has ability of learning. So many people expect that it is useful to get the control rules identified from the expert. And several researchers study with respect to it. Horikawa, one of them, presents a fuzzy controller using a neural network. The controller can automaticaly identify the control rules and tune the membership functions utilizing control data of the expert. The controller uses the rules written in the form of 'IF∿THEN y=f', where 'f' is constant. However, when FC uses this rules, it needs many rules. In this paper, we present a new fuzzy controller with a neural network which uses the rules written 'IF∿THEN y=f(・)', where f(・) is a linear function. Because when FC uses this rule, it need not many rules. In order to demonstrate the effectiveness of this FC, we simulate by using a computer to control a first order delayed system with a dead time. And we compare this controller with Horikawa's controller.
著者キーワード
Neural Network
Fuzzy Controller
Learning
Control Rules
NDC分類
電気工学 [ 540 ]
言語
日本語
資源タイプ 紀要論文
出版者
広島大学総合科学部
発行日 1995-12-28
出版タイプ Version of Record(出版社版。早期公開を含む)
アクセス権 オープンアクセス
日付
[作成日] 2006-03-21
収録物識別子
[ISSN] 1340-8364
[NCID] AN10435936