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研究生:涂景翔
研究生(外文):Ching-Hsiang Tu
論文名稱:基因演算法控制之線型壓電陶瓷馬達驅動系統
論文名稱(外文):Genetic Algorithm-based Control for Linear-motion Piezoelectric Ceramic Motor Drive System
指導教授:魏榮宗
指導教授(外文):Rong-Jong Wai
學位類別:碩士
校院名稱:元智大學
系所名稱:電機工程學系
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:2005
畢業學年度:93
語文別:英文
中文關鍵詞:線型壓電陶瓷馬達混合式諧振反流器全域滑動模式模糊推理步階迴歸控制技術里亞普諾穩定理論基因演算法
外文關鍵詞:linear-motion piezoelectric ceramic motor (LPCM)hybrid resonant invertertotal sliding-modefuzzy mechanismbackstepping control (BSC) techniqueLyapunov stability theorygenetic algorithm (GA)
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本論文之目的在於針對線型壓電陶瓷馬達,提出一混合式諧振驅動電路,並發展以全域滑動模式及里亞普諾穩定理論為基礎之基因演算法控制系統。本論文所提出之混合式諧振驅動電路,採LC電流源並聯諧振高電壓增益之優點,並利用LLCC諧振之特性,改善波形失真情形,然而因為此馬達之動態特性及其參數為非線性且時變,因此本論文發展以全域滑動模式及里亞普諾穩定理論為基礎之基因演算法控制系統。首先引入具有未知系統參數之非線性方程式和古典牛頓定律來建立線型壓電陶瓷馬達及其驅動電路之模型;再者,採全域滑動模式控制之精神與模糊演化機制來設計一具有指向性之基因演算法控制系統以達到高精度之定位控制,在此控制架構中,基因演算法被用來設計一主控制器,設計過程中不需要特殊限制和詳細系統資訊,而其收斂性可以藉由全域滑動模式間接被保證。然而此方式仍需使用部分系統參數,因此本論文更進一步設計以里亞普諾穩定理論為基礎之基因演算法控制系統,此控制架構採用步階迴歸控制之設計精神,並結合由里亞普諾穩定理論所設計之適應性法則來組成一具有指向性之基因演算法控制系統,其穩定度可以直接由里亞普諾穩定理論證明,且無須系統任何資訊及其他輔助控制器即可達成理想之控制性能。最後本論文利用數值模擬與實作結果佐證所提出驅動電路和控制系統之有效性與強健性。
This thesis presents a total sliding-mode-based genetic algorithm control (TSGAC) system and a Lyapunov-based genetic algorithm control (LGAC) system for a linear-motion piezoelectric ceramic motor (LPCM) driven by a newly designed hybrid resonant inverter. In the hybrid resonant drive system, it has the merits of the high voltage gain from a parallel-resonant current source, and the invariant output characteristic from a two-inductance two-capacitance (LLCC) resonant driving circuit. Since the dynamic characteristics and motor parameters of the LPCM are highly nonlinear and time varying, two novel control systems including TSGAC and LGAC are proposed. First, the motor configuration and driving circuit of an LPCM are introduced, and its hypothetical dynamic model is represented by a nonlinear function with unknown system parameters. Moreover, the TSGAC system is therefore investigated based on direction-based genetic algorithm (GA) with the spirit of total sliding-mode control (TSC) and fuzzy-based evolutionary procedure to achieve high-precision position control under wide operation range. In this control scheme, a GA control system is developed to be the major controller, and the convergence can be indirectly ensured by the concept of TSC without strict constraint and detailed system knowledge. Unfortunately, partial system knowledge is still required in the design process of TSGAC. In addition, an LGAC system via backstepping design technique is constructed from direction-based GA to achieve the positioning control object and reform the shortcoming in the TSGAC system. In this control scheme, adaptation laws derived from Lyapunov stability analyses are utilized to adjust appropriate evolutionary steps, and the system stability can be guaranteed directly without any system information and other auxiliary controllers. Furthermore, the effectiveness of the proposed drive and control system is verified by numerical simulations and experimental results under the possible occurrence of uncertainties.
中文摘要 I
Abstract III
誌謝 V
Contents VI
List of Figures and Tables VIII
Chapter 1 Introduction 1
Chapter 2 Dynamic Characteristic and Driving Circuit of Linear-motion Piezoelectric Ceramic Motor 7
2.1 Overview 7
2.2 Motor configuration 7
2.3 Hybrid resonant drive system 9
2.4 Experimental results of driving circuit 11
2.5 Hypothetical dynamic model 15
2.6 Conclusions 16
Chapter 3 Total Sliding-mode-based Genetic Algorithm Control with Fuzzy-based Evolutionary Procedure 17
3.1 Overview 17
3.2 Total sliding-mode control system 18
3.3 Total sliding-mode-based genetic algorithm control system 22
3.3.1 TSGA control 22
3.3.2 Fuzzy-based evolutionary procedure 27
3.4 Numerical simulations and experimental results 29
3.4.1 Simulation of control systems 29
3.4.2 Experimentation of control systems 34
3.5 Conclusions 42
Chapter 4 Lyapunov-based Genetic Algorithm Control with Backstepping Design Technique 44
4.1 Overview 44
4.2 Backstepping control system 45
4.3 Lyapunov-based genetic algorithm control system 47
4.3.1 Major control design 47
4.3.2 Lyapunov stability analysis 53
4.4 Numerical simulations and experimental results 57
4.4.1 Simulation of control systems 58
4.4.2 Experimentation of control systems 62
4.5 Conclusions 69
Chapter 5 Discussions and Suggestions for Future Research 71
5.1 Discussions 71
5.2 Suggestions for future research 74
References 76
作者簡歷 80
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