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研究生:張俊賢
研究生(外文):Chun-Hsien Chang
論文名稱:使用類神經網路之適應性預測控制的設計與應用
論文名稱(外文):The Design and Application of Adaptive Predictive Control Using Neural Networks
指導教授:吳煒吳煒引用關係吳佳儒吳佳儒引用關係
指導教授(外文):Wei WuChia-Ju Wu
學位類別:碩士
校院名稱:國立雲林科技大學
系所名稱:電機工程系碩士班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2003
畢業學年度:91
語文別:中文
論文頁數:69
中文關鍵詞:預測控制類神經網路動態倒傳遞
外文關鍵詞:Neural NetworksDynamic BackpropagationPredictive Control
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本論文根據傳統模式預測控制的概念,利用類神經網路強大的建模能力,訓練一個類神經網路,用來當作預測模式,並搭配最佳化的運算,建立一個實用型的類神經網路預測控制(NNPC)架構。另外為了能線上即時減少預測模式和真實系統間的誤差,及提高預測的準確性。我們使用動態倒傳遞(DBP)的演算規則修正權重值,使整個控制架構成為具適應性之類神經網路預測控制(ANNPC)。並將二種控制方法分別應用的單變數及多變數系統中,並測試二種控制方法的性能與韌性。
In this thesis, we use neural networks, which have strong ability of identification, to replace the predictive model based on the traditional model predictive control. Then we collocate with optimal operation to establish a neural network predictive control (NNPC) structure. On the other hand, in order to reduce the error between the predictive model and true system immediately and increase the accuracy of prediction, we use the dynamic backpropagation (DBP) learning algorithm to adjust the weights of neural network during the on-line procedure. The whole control structure becomes a adaptive neural network predictive control (ANNPC). We also use two kinds of control method to control a single input single output (SISO) system and a multi-input multi-output (MIMO) system. Through the simulation, we get the performance and tenacity of two control methods.
中文摘要…………………………………………………………………………i
英文摘要………………………………………………………………………..ii
致謝…………………………………………………………………………….iii
目錄…………………………………………………………………………..iv
圖表目錄……………………………………………………………………….vi

第一章 緒論………………………………………………………..………… 1
1.1 研究動機與目的…………………………………………………….1
1.2 研究方法…………………………………………………………….2
1.3 論文架構…………………………………………………………….3
第二章 基於類神經網路的預測控制…………………………………….. 5
2.1 前言…………………………………………………………………..5
2.2 關於類神經網路………..…………………………………………..6
2.2.1 類神經網路的架構……………………………………………6
2.2.2 類神經網路的優缺點…………………………………………9
2.3 使用類神經網路做系統鑑別…………………………………….10
2.4 Levenberg-Marquardt演算法…………………………………….13
2.5 預測控制…………………………………………………………...15
2.5.1 預測控制的概念………….………………………………….15
2.5.2 基於類神經網路的預測器………………………………….16
2.5.3 類神經網路預測控制………….……………………………17
2.6 模擬測試…………………………………………………………..19
2.6.1 系統架構與開迴路測試…………………………………….19
2.6.2 系統鑑別與驗證……………………………………………..21
2.6.3 類神經網路預測控制……………………………………....23
第三章 具適應性之類神經網路預測控制…………………………….…..28
3.1 前言…………………………………………………………………28
3.2 動態倒傳遞(DBP)…………………………………………………30
3.3 學習率………………………………………………………………33
3.4 模擬測試……………………..…………………………………….34
3.5 能量參數( )對系統的影響………..………………….………..41
3.6 取樣速度的測試…………………..………………………………46
第四章 多變數系統的應用………………………………………………..48
4.1 多變數系統…..……………………………………………………48
4.2 NNPC應用於MIMO系統….………………………..…………49
4.2.1 控制方法……………….…………………………………….49
4.2.2 模擬測試……………….…………………………………….50
4.3 ANNPC應用於MIMO系統….……………………..…………56
4.3.1 控制方法……………….…………………………………….56
4.3.2 模擬測試……………….…………………………………….57
第五章 結論與展望…….…………………………………………………..64
參考文獻………………………………………………………………………. 66
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