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系統識別號 U0002-2407200703081400
中文論文名稱 切換式PD-PI控制器之最佳化設計
英文論文名稱 Optimal Design of Switching-Type PD-PI Controller
校院名稱 淡江大學
系所名稱(中) 電機工程學系碩士在職專班
系所名稱(英) Department of Electrical Engineering
學年度 95
學期 2
出版年 96
研究生中文姓名 郭天祐
研究生英文姓名 Tan-Yu Kuo
學號 794350156
學位類別 碩士
語文別 中文
口試日期 2007-07-19
論文頁數 50頁
口試委員 指導教授-翁慶昌
委員-黃志良
委員-許陳鑑
委員-陳珍源
委員-陳慶逸
委員-翁慶昌
中文關鍵字 粒子群最佳化  基因演算法  PID控制  自動電壓調整器 
英文關鍵字 PID control  Genetic Algorithm(GA)  Particle Swarm Optimization(PSO) algorithm  Automatic Voltage Regulator (AVR) 
學科別分類 學科別應用科學電機及電子
中文摘要 本論文提出一個切換式PD-PI控制器(Switching-Type PD-PI Controller, SWPD-PI),此控制結構整合PD可以改善暫態響應與PI控制器可以消除穩態誤差的特性來讓受控系統具有不錯的整體控制性能。在控制參數的選取上,本論文應用基因演算法(Genetic Algorithm, GA)與粒子群最佳化(Particle Swarm Optimization, PSO)演算法等兩種最佳化演算法來選取適當的切換值以及PD與PI的控制參數。在適應函數(fitness function)的選取上,本論文提出一個新的評估系統性能的方式,其使得最佳化演算法更可以找到讓系統整體性能更好之控制參數。最後,本論文將所提的方法應用於自動電壓調整器系統(Automatic Voltage Regulator, AVR)上,從一些結果的比較中可以證實所提方法確實可以讓受控系統具有不錯的整體控制性能。
英文摘要 In this thesis, a switching-type PD-PI controller and a parameter selection method are proposed. The proposed control structure combines the features that PD controller can improve the transient response and PI controller can erase the steady error to let the controlled system with a good performance in the global response. In the parameters selection, two optimal algorithms of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithm are applied to select an appropriate switching value and control parameters in PD and PI controllers so that the controlled system has a good performance. In the selection of the fitness function, a new evaluation method in the system performance is proposed so that GA or PSO algorithm can effectively find a parameter set which lets the controlled system have a better performance. Finally, the proposed method is applied in the automatic voltage regulator. From some simulation and comparison results, we can find that the switching-type PD-PI control structure and the proposed parameter selection method can effectively find a parameter set with a better control performance than the other methods.
論文目次 圖目錄 III
表目錄 V
第一章 緒論 - 1 -
1.1前言 - 1 -
1.2文獻回顧 - 2 -
1.3 論文架構 - 5 -
第二章 最佳化演算法 - 6 -
2.1 基因演算法(GA)的基本理論 - 6 -
2.1.1 基因演算法(GA)概述 - 6 -
2.1.2 基因演算法(GA)的三大運算過程 - 8 -
2.2.3 基因演算法(GA)的特性 - 11 -
2.2 粒子群最佳化演算法 - 12 -
2.2.1 粒子群最佳化演算法概述 - 12 -
2.2.2 粒子群最佳化演算法的計算流程 - 13 -
2.1.3 粒子群最佳化(PSO)演算法特性 - 17 -
第三章 切換式PD-PI控制器原理 - 18 -
3.1 PID閉迴路控制簡介 - 18 -
3.2 PID控制器大事記(年表) - 18 -
3.3 PID閉迴路控制原理 - 20 -
3.4 PID參數調整方法 - 22 -
3.5切換式PD-PI控制器原理說明 - 23 -
3.6控制器系統效能評估 - 25 -
第四章 系統模型介紹 - 27 -
4.1自動電壓調整器系統介紹 - 27 -
4.1.1 線性化之自動電壓調整器系統模型 - 27 -
4.1.2 AVR系統暫態特性評估 - 29 -
第五章 模擬與實驗結果 - 32 -
5.1 AVR系統模擬 - 32 -
5.1.1 PD控制器應用於AVR系統 - 34 -
5.1.2 PI控制器應用於AVR系統 - 35 -
5.1.3 PID控制器應用於AVR系統 - 36 -
5.1.4切換式PD-PI控制器應用於AVR系統 - 38 -
5.1.5 各控制器輸出性能比較 - 42 -
第六章 結論 - 46 -
參考資料 - 47 -
圖目錄
圖2.1、GA演算法流程圖 - 8 -
圖2.2、交配示意圖 - 10 -
圖2.3、突變示意圖 - 11 -
圖2.4、PSO演算法之流程圖 - 16 -
圖3.1、PID控制器的閉迴路控制方塊圖 - 22 -
圖3.2、切換式PD-PI控制器之系統架構圖 - 24 -
圖3.4、步階響應圖 - 26 -
圖4.1、自動電壓調整器之簡化方塊圖 - 27 -
圖4.2、AVR控制系統迴路圖 - 28 -
圖4.3、過阻尼系統 - 31 -
圖5.1、AVR閉迴路控制系統方塊圖 - 32 -
圖5.2、一般控制器系統程式流程圖 - 33 -
圖5.3、PSO演算法為基之PD控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 34 -
圖5.4、PSO演算法為基之PD控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 35 -
圖5.5、PSO演算法為基之PI控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 36 -
圖5.6、PSO演算法為基之PI控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 36 -
圖5.8、PSO演算法為基之PID控制器於AVR系統控制之模擬( 1.5):(a)輸出響應圖;(b)各代之最佳適應值。 - 38 -
圖5.9、PSO演算法為基之切換式PD-PI控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 39 -
圖5.10、PSO演算法為基之切換式PD-PI控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 39 -
圖5.12、GA演算法為基之切換式PD-PI控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 41 -
圖5.13、GA演算法為基之切換式PD-PI控制器於AVR系統控制之模擬( ):(a)輸出響應圖;(b)各代之最佳適應值。 - 42 -


表目錄

表4.1、參數說明表 - 29 -
表5.1、β=1各控制器於AVR系統控制之參數表 - 43 -
表5.2、β=1.5各控制器於AVR系統控制之參數表 - 44 -
表5.3、各控制器於AVR系統控制之系統響應性能比較表 45 -
表5.4、各控制器於AVR系統控制之系統響應性能比較表 45 -


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