臺灣博碩士論文加值系統

反覆式學習控制ILC(Iterative Learning Control)，是經由反覆的操作過程中學習系統未知的資訊，作為下次控制修正的經驗，因此ILC控制器能在有限的學習次數下，將系統的跟隨誤差收斂至一個微小的範圍內。本論文所探討的是以改良式全閉迴路控制系統搭配反覆式學習控制器之理論與實際應用上的問題，運用P和PD-型態的學習控制法則，對於控制龍門平台定位做反覆軌跡的追蹤，並比較系統在半閉開迴路控制系統與改良式全閉迴路控制系統控制下誤差實際收斂的效果，將可確保將系統保持在一定的誤差範圍內，使系統不致於發散。

The iterative learning control (ILC) is designed to improve the system performance by iterative operations and it is used to modify the contour tracking error of a gantry stage by PD-type learning algorithm. For the contouring control of the gantry stage, there are two categories in the closed-loop control architecture and they are semi-closed loop control and fully-closed loop control. Semi-closed loop control only uses the encoder feedback of the motors and there exists gap problems due to the ball-screw mechanism. Fully-closed loop control uses the position feedback of the stage and it can compensate the gap problem. In this thesis, the iterative learning control (ILC) is integrated with the fully-closed-loop control to achieve precision tracking tasks. Besides, P-type learning and PD-typed learning algorithms are applied to achieve the repetitive tracking tasks and compare the resulting error from the semi-closed loop control. From the experimental results, it can be validated that the PD-type learning control is the best one and eliminate the gap problem successfully.

封面內頁
簽名頁
授權書 iii
中文摘要 iv
英文摘要 v
誌謝 vi
目錄 vii
圖目錄 ix
表目錄 xiv
符號說明 ixv

第一章 緒論 1
1.1 前言 1
1.2 文獻回顧 2
1.3 本文內容 4
第二章 精密定位平台建構 5
2.1 龍門平台 5
2.2 雷射光學尺 7
2.3 Next MoveES控制器 9
2.4 驅動器硬體設備 13
2.5 保護裝置之設計 13
第三章 任務導向運動規劃法 16
3.1 程式介面簡介 16
3.2 改良式全閉迴路控制 20
3.3 半閉迴路控制結果 23
3.4 限制修正精度規劃法 27
3.5 限制修正時間規劃法 34
3.6 限制修正次數規劃法 40
第四章 反覆式學習控制系統 48
4.1 何謂學習控制 48
4.2 反覆式學習控制系統之二維表示式 50
4.3 反覆式學習與PID控制器設計 52
第五章 實驗結果 56
5.1 單軸定位實驗 56
5.2 雙軸循圓實驗 72
第六章 結論 91
參考文獻 92
附錄一 94

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