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研究生:黃威龍
研究生(外文):Wei-Long Huang
論文名稱:類神經網路軟體於系統識別與控制之研究
論文名稱(外文):Development of an Artificial Neural Network Software for System Identification and Control
指導教授:楊世銘楊世銘引用關係
指導教授(外文):Shih-Ming Yang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:航空太空工程學系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:1999
畢業學年度:87
語文別:英文
論文頁數:79
中文關鍵詞:類神經網路
外文關鍵詞:Artificial Neural NetworkNeural Network
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摘要
類神經網路軟體於系統識別與控制之研究
研究生:黃威龍
指導教授:楊世銘
倒傳遞類神經網路是目前學習模式中最具代表性,應用最普遍的類神經網路。但是倒傳遞網路有需要長時間訓練以及容易收斂於局部最小值的缺點。為了改善這些缺點,本文提出擬牛頓學習法和基因演算學習法,並將此結合於類神經網路軟體(VIBNN)中。此研究主旨在發展一套整合性類神經網路視窗軟體,以改善倒傳遞類神經網路的學習效率和精度。本文另提出兩步驟訓練法,其結合擬牛頓法以及基因演算法之優點。本文應用VIBNN於系統識別和振動控制,結果顯示VIBNN可以成功應用於這些問題上。
Development of an Artificial Neural Network Software
for System Identification and Control
Abstract
It is known that backpropagation network requires long training time and is easily stuck in local minimum. To improve these disadvantages, the combination of neural network, quasi-Newton algorithm and genetic algorithm is integrated in the neural network software VIBNN. The purpose of this thesis is mainly to provide an integrated software for improving the training efficiency and accuracy of backpropagation network. A two-stage training algorithm is developed which includes the advantages of quasi-Newton algorithm and of genetic algorithm. Applications of the neural network software to system identification and vibration suppression in this thesis have been very successfully.
Table of Contents
Abstrac … …………………………………………………… i
Table of Contents ……………………………………………… ii
Chapter 1 Introduction
1.1 Motivation …… ………………………………………… 1
1.2 Literature Review …………………………………………… 2
1.2.1 Backpropagation Algorithm ……… …………….……. 2
1.2.2 Neural Network with Genetic Algorithm………………... 3
1.2.3 Neural Network for System Identification and Control .…. 4
1.3 Outline ……………………………………………………. 5
Chapter 2 Artificial Neural Networks
2.1 Introduction ………………………………………………. 6
2.2 Neural Network ………………………………… ………... 7
2.2.1 Feedforward Network with Backpropagation Algorithm … 8
2.2.2 Feedforward Network with Quasi-Newton Algorithm . 11
2.2.3 Feedforward Network with Genetic Algorithm …… 13
Chapter 3 System Identification Using Neural Networks
3.1 Introduction ………… ……………………………… 23
3.2 Introduction to VIBNN ……………… ……………… 25
3.3 Examples of System Identification …………………… 27
3.4 The Two-Stage Training Algorithm …………………… 32
3.5 Conclusion ………………………………………… . 33
Chapter 4 Controller Design by Using Neural Network
4.1 Introduction ……………………………………… .. 52
4.2 Linear Reference Model ……………………………… 52
4.3 VIBNN for Neural Controller………….. …………… 53
4.4 Examples of Controller Design by VIBNN …………… 54
4.5 Comparison of VIBNN with Other Softwares ………… 56
4.6 Conclusion………………………………………… 57
Chapter 5 Summary and Conclusions ……………………… 75
References ………………………………………………… 76
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