Stabilization Control of an Inverted Pendulum by Complex-valued Neuro-Fuzzy Learning Algorithm

被引：0

作者：

Arai, Jin ^{[1
]}

Hata, Ryusuke ^{[1
]}

Murase, Kazuyuki ^{[1
]}

机构：

[1] Univ Fukui, Grad Sch Engn, Fukui, Japan

来源：

2014 JOINT 7TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 15TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS) | 2014年

关键词：

Neuro-fuzzy; Fuzzy; Neural networks; Complex-valued neural networks; Inverted pendulum;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

As an automatic generation method of the fuzzy rules, the complex-valued neuro-fuzzy (CVNF) learning algorithm has been suggested. That is a method expanded the conventional neuro-fuzzy (NF) learning algorithm into the complex domain. The purpose of this study is to verify the effectiveness of the CVNF by performing the stabilization control of an inverted pendulum using CVNF, and comparing it with NF. As a result, the control of the inverted pendulum was possible in CVNF with higher precision than in NF.

引用

页码：649 / 654

页数：6

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