The Design and Application of a Self-organized Fuzzy System

碩士 === 華梵大學 === 機電工程研究所 === 89 === The adjustment of the premise and consequent part of fuzzy if-then rules is the most important issue in fuzzy learning problem. This thesis presents a method combing self-organization and least square estimation to automatically adjust the parameters of a fuzzy sys...

Full description

Bibliographic Details
Main Authors: Chun-Te Hsu, 徐俊德
Other Authors: Chiang-Ju Chien
Format: Others
Language:en_US
Published: 2001
Online Access:http://ndltd.ncl.edu.tw/handle/68104486411680192588
id ndltd-TW-089HCHT0657007
record_format oai_dc
spelling ndltd-TW-089HCHT06570072015-10-13T12:43:59Z http://ndltd.ncl.edu.tw/handle/68104486411680192588 The Design and Application of a Self-organized Fuzzy System 自組式模糊系統的設計與應用 Chun-Te Hsu 徐俊德 碩士 華梵大學 機電工程研究所 89 The adjustment of the premise and consequent part of fuzzy if-then rules is the most important issue in fuzzy learning problem. This thesis presents a method combing self-organization and least square estimation to automatically adjust the parameters of a fuzzy system from training pattern. In chapter 2, we perform this method by using a feed-forward Tagagi-Sugeno-type fuzzy network on a typical plant of an inverted pendulum, and demonstrate the better convergent rate and average learning error when compared with some other traditional networks. In chapter 3, the proposed method is applied to a recurrent Tagagi-Sugeno-type fuzzy network, and the comparisons between the performance of using feed-forward and recurrent Tagagi-Sugeno-type fuzzy network are widely studied by an example of identification for a nonlinear system. Finally, the merits and the drawbacks of the proposed hybrid method will be discussed for different kinds of learning objects, and we also cite the thought on the direction of application for the future. Chiang-Ju Chien 簡江儒 2001 學位論文 ; thesis 77 en_US
collection NDLTD
language en_US
format Others
sources NDLTD
description 碩士 === 華梵大學 === 機電工程研究所 === 89 === The adjustment of the premise and consequent part of fuzzy if-then rules is the most important issue in fuzzy learning problem. This thesis presents a method combing self-organization and least square estimation to automatically adjust the parameters of a fuzzy system from training pattern. In chapter 2, we perform this method by using a feed-forward Tagagi-Sugeno-type fuzzy network on a typical plant of an inverted pendulum, and demonstrate the better convergent rate and average learning error when compared with some other traditional networks. In chapter 3, the proposed method is applied to a recurrent Tagagi-Sugeno-type fuzzy network, and the comparisons between the performance of using feed-forward and recurrent Tagagi-Sugeno-type fuzzy network are widely studied by an example of identification for a nonlinear system. Finally, the merits and the drawbacks of the proposed hybrid method will be discussed for different kinds of learning objects, and we also cite the thought on the direction of application for the future.
author2 Chiang-Ju Chien
author_facet Chiang-Ju Chien
Chun-Te Hsu
徐俊德
author Chun-Te Hsu
徐俊德
spellingShingle Chun-Te Hsu
徐俊德
The Design and Application of a Self-organized Fuzzy System
author_sort Chun-Te Hsu
title The Design and Application of a Self-organized Fuzzy System
title_short The Design and Application of a Self-organized Fuzzy System
title_full The Design and Application of a Self-organized Fuzzy System
title_fullStr The Design and Application of a Self-organized Fuzzy System
title_full_unstemmed The Design and Application of a Self-organized Fuzzy System
title_sort design and application of a self-organized fuzzy system
publishDate 2001
url http://ndltd.ncl.edu.tw/handle/68104486411680192588
work_keys_str_mv AT chuntehsu thedesignandapplicationofaselforganizedfuzzysystem
AT xújùndé thedesignandapplicationofaselforganizedfuzzysystem
AT chuntehsu zìzǔshìmóhúxìtǒngdeshèjìyǔyīngyòng
AT xújùndé zìzǔshìmóhúxìtǒngdeshèjìyǔyīngyòng
AT chuntehsu designandapplicationofaselforganizedfuzzysystem
AT xújùndé designandapplicationofaselforganizedfuzzysystem
_version_ 1716865154174418944