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研究生:閻惠民
研究生(外文):Hui-MinYen
論文名稱:電驅動受約束機械系統之智慧型追蹤控制設計
論文名稱(外文):Intelligent Tracking Control Design for a Class of Electrically Driven Constrained Mechanical Systems
指導教授:李祖聖張永昌張永昌引用關係
指導教授(外文):Tzuu-Hseng S. LiTzuu-Hseng S. Li
學位類別:博士
校院名稱:國立成功大學
系所名稱:電機工程學系碩博士班
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:2012
畢業學年度:101
語文別:英文
論文頁數:109
中文關鍵詞:適應控制受約束機械系統電驅動強健控制
外文關鍵詞:adaptive controlconstrained mechanical systemselectrically drivenrobust control
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  • 下載下載:33
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本論文主要探討電驅動受約束機械系統之智慧型追蹤控制設計。首先,針對受非完整約束與完整約束機械系統分別設計出以類神經網路及模糊邏輯系統為基礎的強健追蹤控制設計,這一類電驅動受約束機械系統存在著設備不確定、未模式化時變擾動及外在雜訊干擾。本論文利用類神經網路及模糊邏輯系統的近似特性來學習機械系統與電路系統中的未知的動態特性,以避免計算系統複雜的遞迴矩陣,並藉由觀測器來估測系統的速度信號,因此控制器只需量測馬達電流及機械系統的輸出位置來做為回授訊號。此外因外在雜訊干擾所造成的追蹤誤差可利用可變結構控制設計來降低其影響。藉由步階設計技術及李亞普諾夫穩定性理論分析,所設計出之控制器可以保證系統所有信號都是有界的並能使得追蹤誤差能盡可能的小。本論文所設計之控制技術亦延伸應用至具有彈性關節之機械系統,能達到更寬廣的應用。最後,電腦模擬結果驗證出所提出智慧型追蹤控制設計可以有效的控制電驅動受約束機械系統及具有彈性關節之機械臂系統,並能完成軌跡追蹤之任務。
This dissertation proposes an intelligent tracking control design for a class of electrically driven constrained mechanical systems. Firstly, we address the problem of designing an intelligent motion tracking control for nonholonomic and holonomic mechanical systems actuated by direct current motors. This class of electrically driven mechanical systems may be perturbed by plant uncertainties, unmodeled time-varying perturbations, and external disturbances. Neural network systems and fuzzy logic systems are employed to approximate the behaviors of uncertain mechanical and electrical dynamics. A reduced-order observer is constructed to estimate the velocity signals. Only the measurements of link position and armature current are required for feedback signals. The effect of external disturbance on the tracking error is efficiently eliminated by an additional variable structure control technique. Using backstepping technique and Lyapunov stability theorem, the intelligent tracking controller is developed such that all the states and signals of the closed-loop system are bounded and the tracking error can be made as small as possible. Moreover, the tracking control schemes developed in this study can be extended to handle a broader class of nonlinear electrically driven flexible-joint mechanical systems. Finally, simulation results are presented to demonstrate the effectiveness and tracking performance of the proposed control schemes.
Abstract in Chinese I
Abstract in English II
Acknowledgement in Chinese III
Contents IV
List of Acronyms VI
Nomenclature VII
List of Figures IX
List of Table XII
Chapter 1 Introduction 1
1.1 Preliminary 1
1.2 Dissertation contributions 6
1.3 Dissertation organization 7
Chapter 2 Adaptive Neural Network-Based Tracking Control for a Class of Electrically Driven Nonholonomic Mechanical Systems 8
2.1 Introduction 8
2.2 Model description and problem formulation 9
2.2.1 Description of nonholonomic systems 9
2.2.2 Problem formulation 14
2.2.3 Description of neural network systems 15
2.3 Adaptive neural network-based tracking control design 16
2.4 Simulation results 24
2.5 Summary 34
Chapter 3 Adaptive Fuzzy-Based Tracking Control for a Class of Electrically Driven Holonomic Mechanical Systems 35
3.1 Introduction 35
3.2 Model description and problem formulation 36
3.2.1 Description of constrained robot systems 36
3.2.2 Description of fuzzy logic systems 40
3.2.3 Problem formulation 41
3.3 Adaptive fuzzy-based tracking control design 42
3.4 Simulation results 50
3.5 Summary 56
Chapter 4 Adaptive Neural Network-Based Tracking Control for Electrically Driven Flexible Joint Robots 58
4.1 Introduction 58
4.2 Model description and problem formulation. 59
4.2.1 Model description 59
4.2.2 Problem formulation 61
4.3 Design of adaptive tracking controller 62
4.4 Simulation results 69
4.5 Summary 76
Chapter 5 Conclusions 77
5.1 Conclusions 77
5.2 Recommendations for further work 78
Bibliography 79
Appendix 90

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