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研究生:邱振銘
研究生(外文):chen-ming chiou
論文名稱:類神經網路之線性化及其在識別與控制上之評估
論文名稱(外文):Evaluation of Neural Network Linearization in Identification and Control
指導教授:黃榮興黃榮興引用關係
指導教授(外文):Thong-Shing Hwang
學位類別:碩士
校院名稱:逢甲大學
系所名稱:自動控制工程所
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:2003
畢業學年度:91
語文別:中文
論文頁數:61
中文關鍵詞:PID 控制器類神經網路線性化
外文關鍵詞:LinearizationNeural NetworkPID
相關次數:
  • 被引用被引用:9
  • 點閱點閱:187
  • 評分評分:
  • 下載下載:27
  • 收藏至我的研究室書目清單書目收藏:0
本論文之目的在於將複雜的類神經網路結構,經由線性化轉換為較易理解與分析之轉移函數,並將其應用在系統識別與控制器設計方面,對於目前廣泛應用於工業界之PID 控制器,其參數調整工作常仰賴專業工程師的實際經驗及試誤法,本文首先嘗試建構PID 參數學習網路架構,再利用類神經自動調整PID參數之能力以達成參考模式之追蹤控制。
The purpose of this thesis is to evaluate the possibility of neural network linearization in identification and control. For the system identification, the linearized transfer function is more comprehensive and analyzable than the original neural network model; Further, it can be applied to system control design. Most of industrial PID controller design will depend on experiences of engineer and trial and error
approach to tune controller parameters. In this paper, first, we try to construct the architecture of the PID parameter-learning network. Secondly, the capability of the
auto tuning in neural network is adopted to accomplish the tracking control for the
reference model.
感謝
摘要
ABSTRACT
圖表目錄
第一章緒論
第二章類神經網路理論與架構
第三章類神經網路線性化之探討及其應用
第四章PID 控制器參數學習網路
第五章結論
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類神經網路之線性化及其在識別與控制上之評估
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