A Real-Valued GA-Based Approach to Extracting Control Fuzzy Rules
學年 84
學期 2
發表日期 1996-04-12
作品名稱 A Real-Valued GA-Based Approach to Extracting Control Fuzzy Rules
作品名稱（其他語言）
著者 Su, Mu-Chun; Chang, Hsiao-Te; Yu, Hua-Chiao
作品所屬單位 淡江大學電機工程學系
出版者
會議名稱 一九九六自動控制研討會暨兩岸機電及控制技術交流學術研討會=1996 Automatic Control Conference
會議地點 臺北縣, 臺灣
摘要 In this paper, we present a neuro-fuzzy approach to design a controller directly from numerical data. The proposed neuro-fuzzy system is implemented as a two-layer Fuzzy Degraded HyperEllipsoidal Composite Neural Network(FDHECNN). We used a real-valued genetic algorithm to adjust weights of the composite neural networks. After sufficient training, the synaptic weights of the trained FDHECNN can be utilized to extract a set of fuzzy if-then rules. The performance of a trained FDHECNN is shown to be computationally identical to a fuzzy logic controller. The effectiveness and feasibility of the neuro-fuzzy system are tested on the truck backer-upper control problem.
關鍵字 遺傳演算法;模糊邏輯控制器;神經-模糊系統;專家系統;Genetic Algorithm;Fuzzy Logic Controller;Neuro-Fuzzy System;Expert System
語言 en
收錄於
會議性質 兩岸
校內研討會地點 淡水校園
研討會時間 19960412~19960413
通訊作者
國別 TWN
公開徵稿 Y
出版型式 紙本
出處 一九九六自動控制研討會暨兩岸機電及控制技術交流學術研討會論文集=Proceedings of 1996 Automatic Control Conference，頁289-294
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