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研究生:簡達鴻
研究生(外文):Da-Hong Jian
論文名稱:基於模糊類神經網路與改良式通訊干擾估測器之時間延遲補償系統
論文名稱(外文):A Time Delay Compensation System Based on Fuzzy Neural Networks and Improved Communication Disturbance Observer
指導教授:李俊賢李俊賢引用關係
指導教授(外文):Jin-Shyan Lee
口試委員:黃正民徐勝均賴建良
口試日期:2012-07-24
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
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:2012
畢業學年度:100
語文別:中文
論文頁數:76
中文關鍵詞:網路控制系統時間延遲補償通訊干擾估測模糊控制類神經網路
外文關鍵詞:NCSTime Delay CompensationCDOBFuzzy ControlNeural Networks
相關次數:
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近年來,由於網際網路的蓬勃發展,加上受控系統日趨複雜化,無論在工業以及學術上,傳統控制已無法滿足所需的控制性能,於是網路控制系統(networked control system, NCS)這方面的研究逐漸受到重視。然而在實際控制系統中,特別是透過網路來進行控制,時間延遲是一項急需解決的問題,過大的時間延遲會破壞整個系統的穩定性與性能指標,造成系統難以分析與設計。
因此,本論文提出一套時間延遲補償方法,以通訊干擾估測(communication disturbance observer, CDOB)架構為基礎,搭配模糊理論與類神經網路演算法,有效改善時間延遲對系統的影響。首先,利用模糊控制器取代傳統控制器進行設計,並與改良式CDOB架構作結合,針對CDOB架構中低通濾波器進行探討,隨著干擾訊號頻率的改變,模糊控制器可適應濾波器各種頻率之變化。系統建模部分則使用類神經網路之倒傳遞方法,透過不斷的訓練以及調整權重值,讓估測與實際的系統更為接近,使得建模的誤差降低,進而改善系統響應的穩態誤差。本文所提出的控制方法經由模擬結果得知,可以有效的應用在具有時間延遲之網路控制系統。


In recent years, due to the development of the Internet, the controlled systems
have become more complex. In industry and academia, traditional control has been
unable to satisfy the requirement of the control performance, so the research on
networked control system (NCS) is important increasingly. However, in the actual
control system, especially controlled over the Internet, the time delay is an
urgent problem. If the time delay is too long, the stability and performance of the
whole system will be destroyed, and then it is difficult to analyze and design the
systems.

Therefore, this paper proposes a set of time delay compensation method, based
on the architecture of communication disturbance observers (CDOB) with fuzzy theory and neural networks algorithm, and results show that it can improve the time delay system effectively. First, it replaces the traditional controller with fuzzy controller, combined with improved CDOB architecture, to study the effect of the low-pass filter in CDOB architecture. When the frequency of the disturbance signal changes, the fuzzy controller can be adapted to it. System modeling utilizes back propagation method in neural networks, by continuously training and the adjustment of weight value, the estimation is more close to the actual system, and therefore we can reduce the modeling error and improve the steady state error of the system response. From the simulation results, the proposed method in this paper can be effectively applied to the networked control systems with time delay.


目錄

中文摘要.........................................................................................................................i
英文摘要........................................................................................................................ii
誌謝...............................................................................................................................iv
目錄................................................................................................................................v
表目錄.........................................................................................................................viii
圖目錄...........................................................................................................................ix
第一章 緒論................................................................................................................1
1.1 研究背景.........................................................................................................1
1.2 研究動機與目的.............................................................................................1
1.3 文獻回顧.........................................................................................................2
1.4 研究方法.........................................................................................................3
1.5 研究貢獻.........................................................................................................3
1.6 論文架構.........................................................................................................4
第二章 背景知識與相關研究....................................................................................5
2.1 網路控制系統.................................................................................................5
2.1.1 基本概念..............................................................................................5
2.1.2 網路控制系統架構..............................................................................6
2.1.3 研究領域與範圍..................................................................................8
2.2 時間延遲系統.................................................................................................9
2.2.1 網路控制延遲......................................................................................9
2.2.2 時間延遲分析....................................................................................10
2.3史密斯預估器 (Smith Predictor)..................................................................12
2.4通訊干擾估測 (CDOB)................................................................................13
2.4.1 發展原因與基本概念........................................................................13
2.4.2 網路干擾............................................................................................14
2.4.3 CDOB系統架構.................................................................................16
2.4.4 現有文獻中之改良型CDOB............................................................20
2.4.4.1 Low Pass Filter(LPF)-CDOB型..............................................20
2.4.4.2 Integration(I)-CDOB型...........................................................22
2.4.4.3 Estimated Input Delay(EID)-CDOB型...................................24
2.4.4.4 Reduced Error (RE)-CDOB型................................................25
第三章 模糊控制器設計與類神經網路..................................................................27
3.1 模糊理論介紹...............................................................................................27
3.1.1 模糊理論之歷史背景........................................................................27
3.1.2 模糊理論之分類與應用....................................................................28
3.2 模糊邏輯控制器...........................................................................................28
3.3 類神經網路之介紹.......................................................................................37
3.3.1 類神經理論........................................................................................37
3.3.2 類神經網路架構................................................................................38
3.3.3 類神經網路學習演算法....................................................................39
3.4 倒傳遞演算法...............................................................................................40
第四章 改良式CDOB之時間延遲補償系統.........................................................42
4.1 本文提出之改良式CDOB (FN-CDOB)......................................................42
4.1.1 系統架構............................................................................................42
4.1.2 類神經網路之系統鑑別....................................................................43
4.1.3 模糊控制器之設計............................................................................46
4.2 結合模糊類神經與CDOB架構之演算法流程..........................................51
4.2.1 系統流程圖........................................................................................51
4.2.2 演算法流程........................................................................................53
第五章 模擬結果與分析..........................................................................................55
5.1 類神經網路之系統建模...............................................................................55
5.2 二階時延系統之模擬與比較.......................................................................56
5.2.1與CDOB & LPF-CDOB之比較.........................................................56
5.2.2與I-CDOB之比較...............................................................................58
5.2.3與EID-CDOB之比較.........................................................................60
5.2.4與RE-CDOB之比較..........................................................................61
5.2.5模擬結果分析.....................................................................................63
5.3 高階時延系統之模擬...................................................................................67
5.3.1 系統描述............................................................................................67
5.3.2 模擬結果............................................................................................68
第六章 結論與未來研究..........................................................................................72
6.1 結論...............................................................................................................72
6.2 未來研究.......................................................................................................73
參考文獻......................................................................................................................74


參考文獻

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