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研究生:侯文棋
論文名稱:巨大時間延遲程序之PID控制器調諧
論文名稱(外文):Tuning PID Controllers for Processes with Large Time Delay
指導教授:黃琦聰
學位類別:碩士
校院名稱:東海大學
系所名稱:化學工程學系
學門:工程學門
學類:化學工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:66
中文關鍵詞:巨大時間延遲程序PID控制器調諧最適化控制
外文關鍵詞:Large Time Delay ProcessesTuning PID ControllerOptimum Control
相關次數:
  • 被引用被引用:1
  • 點閱點閱:251
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本研究主要為探討巨大時間延遲程序之PID控制器調諧。研究中,乃利用MATLAB的Optimization Tool及SIMULINK軟體,針對巨大時間延遲程序做最適化控制器參數之調諧;採用一階加時間延遲程序模式,並根據最小誤差積分值做為目標函數,分別在設定點階梯變化及干擾階梯變化下,針對不同的無因次程序時間延遲常數,搜索出PID控制器之最適化控制器調諧值。然後再將這些調諧關係值繪製成調諧關係圖,並基於非線性最小平方法 做曲線擬合以獲得調諧關係方程式。爾後,經由這些調諧關係圖或方程式便可獲得PID控制器之最佳調諧值。最後,再經由電腦模擬並與文獻上之方法做比較,證明本研究之調諧法具有相當好的控制效益及強韌性。

A calculation method of PID controller tuning for the large time delay processes is presented in this study. Optimum PID controller tuning data based on the first-order-plus-time-delay process models and minimum IAE criterion were obtained via the MATLAB and the SIMULINK software tools. These data were then draw into charts and correlated into sample equations by a nonlinear least-squares method. Thus, PID controller tuning based on the models can easily be obtained by charts or by the calculation of these correlated equations. Simulation results have demonstrated that the proposed tuning method can provide better performance and robustness for process with large time delay.

中文摘要 III
英文摘要 IV
誌 謝 V
目 錄 VI
表 目 錄 VII
圖 目 錄 IX
符號說明 XIII
第 一 章 緒論 1
第 二 章 文獻回顧 3
第 三 章 控制系統之MATLAB電腦模擬 9
第 四 章 PID控制器之最適調諧 15
第 五 章 控制效益與強韌性之探討 37
第 六 章 結論 60
參考文獻 61
附 錄 63
簡 歷 66

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Huang, C.-T.; Lin, Y.-S. Tuning PID controller for open-loop unstable process with time delay. Chem. Eng. Comm. 1995, 133, 11-30.
Huang, C.-T.; Chou, C.-J.; Wang, J.-L. Tuning of PID controllers based on the second-order model by calculation. J. Chin. Inst. Chem. Eng. 1996, 27, 107-120.
Huang, C.-T.; Chou, C.-J.; Chen, L.-Z. An Automatic PID controller tuning method by frequency response techniques. Can. J. Chem. Eng. 1997, 75, 596-604.
Huang, C.-T.; Lin, M.-Y.; Huang, M.-C. Tuning PID controllers for processes with inverse response using artificial neural networks. J. Chin. Inst. Chem. Eng. 1999, 30, 223-232.
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