臺灣博碩士論文加值系統

現今的機械手臂已經廣泛的運用在各個不同的領域，其系統存在各種不同且非預期的不確定性，如干擾、非線性摩擦、負載等，而為了要有較小的軌跡追蹤誤差，控制器的設計必須考慮到這些不確定性，傳統的控制方法在多連桿機器人動態控制中受到限制，因此控制器的設計是更加困難的。而本文提出一個智慧型的順滑模態控制器來控制六軸機械手臂，利用遞迴式柴比雪夫類神經網路(Recurrent Chebyshev Neural Network Estimator, RCNN)來估測外界干擾及參數不確定性，再加上一個強健性控制器增強系統的強健性。通常PID控制器主要適用於線性的系統上，且動態特性不會隨時間變化的系統，然而機械手臂是非線性系統，手臂各軸動態是互相耦合的，要調整出最佳的參數更是困難。利用傳統的順滑模態控制的強健性，可以準確地追蹤到期望的位置與速度，卻會因為不連續的控制力影響而產生跳切現象(Chattering Phenomenon)。修改傳統的順滑模態控制，使用飽和函數(Saturation Function)可以削弱跳切現象，卻必須捨棄追蹤的準確性，使用這兩種順滑模態控制方式，皆需要得知受外界干擾與無法估測的參數之上界值，而此工作亦是非常困難複雜的且會造成較大的控制力輸出。因此，本論文提出一個智慧型順滑模態控制器來控制非線性動態的六軸機械手臂，在無法獲得外界干擾以及參 數不確定性之上界值，能有效削弱跳切現象且準確地追蹤。最後經由模擬結果驗證本論文所提出的控制器擁有較佳的控制性能。

This study presents an intelligent sliding mode controller (ISMC) to control a 6-DOF manipulator. Here, the recurrent Chebyshev Neural Network Estimator (RCNN) is used to estimate the external disturbances and parameter uncertainties, and a robust controller is further used to enhance the robustness of the proposed controller. The dynamics of the 6-DOF manipulator is a non-linear system and the dynamics of some joints are coupled with other joints. The traditional sliding mode control is often applied in this 6-DOF manipulator to robustly track the desired position and speed. However, the switching force experiences undesirable phenomenon of oscillations having finite frequency and amplitude, which is known as ‘chattering’. The chattering could be eliminated through a continuous approximation of the switching control in a boundary layer around the sliding surface; the saturation function is the typical one. For the above sliding mode control methods, the boundary of external disturbances and parameter uncertainties should be known, this is very difficult in practices. Therefore, an intelligent sliding mode control system which involved RCNN estimator to estimate the unknown external disturbance and parameter uncertainty is proposed to accurately track the position and velocity of the 6-DOF manipulator. The simulation results further verify the control performance of proposed ISMC.

摘 要 i
ABSTRACT ii
致 謝 iii
目 錄 iv
圖目錄 vi
表目錄 ix
第一章 緒論 1
1.1研究背景與目的 1
1.2文獻探討 2
1.3研究方法 3
1.4論文架構 4
第二章 機械手臂運動學與動力學 5
2.1機械手臂運動學 5
2.1.1 Denavit-Hartenberg參數表 5
2.1.2六軸機械手臂之正向運動學 8
2.2機械手臂微分運動學 11
2.3機械手臂動力學 13
第三章 順滑模態控制器設計 16
3.1順滑模態控制理論 16
3.2順滑模態控制器設計 19
3.3智慧型順滑模態控制系統 22
3.3.1智慧型順滑模態控制設計 23
3.3.2智慧型順滑模態控制穩定度證明 26
第四章 六軸機械手臂模擬 28
4.1模擬設計 28
4.1.1命令軌跡設計 29
4.1.2控制器參數及外在干擾設計 30
4.2模擬結果與分析 32
4.2.1不考慮外在干擾以及不確定性參數之模擬 32
4.2.2加入外在干擾之模擬 39
4.2.3加入不確定項參數之模擬 47
4.2.4加入外在干擾及不確定項參數之模擬 53
4.2.5選擇無法抑制外在干擾及不確定項參數之上界值模擬 59
第五章 實驗與系統架構 63
5.1智慧型運動控制卡 64
5.2IMP嵌入式即時作業系統與架構 66
5.3實驗設計 68
5.4實驗結果與分析 69
第六章 結論與未來展望 74
6.1 總結 74
6.2 未來展望 75
參考文獻 76
附 錄A 79
附 錄B 100

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