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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 顏家鈺(Jia-Yush Yen) | |
| dc.contributor.author | Shu-Hung Liu | en |
| dc.contributor.author | 劉書宏 | zh_TW |
| dc.date.accessioned | 2021-06-08T04:31:31Z | - |
| dc.date.copyright | 2009-10-28 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-10-16 | |
| dc.identifier.citation | [1] R. C. Smith, Smart material systems, Society for Industrial and Applied Mathematics, Philadelphia, 2005.
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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/22871 | - |
| dc.description.abstract | 本論文旨在對形狀記憶合金致動器進行控制，並對一個以形狀記憶合金為致動器的六足仿生機器人進行導航。我們深入研究形狀記憶合金致動器的自我感應特性，此特性源自形狀記憶合金致動器於致動過程中所產生的電阻變化。我們提出了一套方法來量測以脈波寬度調變進行驅動的形狀記憶合金致動器其自感應特性曲線，對此特性曲線進行建模後，不需額外安裝感測器，即可控制形狀記憶合金的長度。此外，針對形狀記憶合金致動器的遲滯現象，我們研發了一個反遲滯補償器以進行補償，並且提出了一個切換控制器架構，此控制器可於前饋反遲滯補償器及自感應回授PID控制器間進行切換。實驗結果證明此切換控制器的性能較PID回授控制器優越。我們製做了一台以形狀記憶合金為致動器的六足仿生機器人SMABOT IV，利用感測器融合技術估測機器人的姿態，所使用的感測器融合技術包含離散時間Kalman濾波器以及離散時間H∞濾波器。離散時間Kalman濾波器針對估測誤差的變異量進行最小化，而離散時間H∞濾波器則是針對最大誤差進行最小化。透過Allan變異量分析對感測器的雜訊進行識別並用以設計離散時間Kalman濾波器，使得離散時間Kalman濾波器擁有較佳的估測性能。將所估測的機器人姿態配合腳步測程法所得之里程加以運算進而估測機器人的位移。 | zh_TW |
| dc.description.abstract | The major aim of the study is to control the SMA actuator, and implement the navigation of a shape memory alloy (SMA)-based hexapod biomimetic robot. We investigate the self-sensing property of the SMA actuator, which is due to the electric resistance variation during its actuating process. A procedure for obtaining the self-sensing characteristic curve of the SMA actuator driving by PWM signal is proposed. By modeling the self-sensing characteristic curve, we can control the displacement of the SMA actuator without using additional sensors. In addition, an inverse hysteresis compensator of the SMA actuator is developed to compensate its hysteresis phenomenon. We proposed a switching controller to control the displacement of the SMA actuator, which consists of a feedforward inverse hysteresis compensator and a PID feedback controller with self-sensing feedback. The experimental results indicate that the switch controller provides better tracking performance than the PID-controller. An SMA-based hexapod biomimetic robot, SMABOT IV, is built, and sensor fusion algorithms are used to estimate its attitude, which include a discrete-time Kalman filter that minimizes the estimation error variance, and a discrete-time H∞ filter that minimizes the worst-case estimation error. After identifying the noise characteristics of the sensors using Allan variance analysis, the Kalman filter provides the better performance. The displacement of the SMABOT IV is then estimated by incorporating the attitude data with the legged odometry. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-08T04:31:31Z (GMT). No. of bitstreams: 1 ntu-98-F91522807-1.pdf: 7924393 bytes, checksum: 0619468c58d3f76c2eb1fa0b2afde306 (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 口試委員會審定書 i
致謝 iii 摘要 v Abstract vii Contents ix List of Figures xiii List of Tables xxv List of Symbols xxvii List of Acronyms xxxii Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Literature review 3 1.2.1 Modeling and control of SMA actuator 3 1.2.2 Biomimetic robot 11 1.2.3 Inertial navigation 15 1.3 Contributions 16 1.4 Thesis structure 19 Chapter 2 Shape memory alloy actuator 21 2.1 Shape memory alloy 22 2.1.1 Temperature-induced phase transformations 24 2.1.2 Stress-induced phase transformations 25 2.1.3 Shape memory effect 29 2.2 SMA actuator 31 2.3 SMA actuator test platform 37 2.4 Driving the SMA actuator 43 2.5 Self-sensing property of SMA actuator 48 2.5.1 Electric resistance variation of the SMA actuator 49 2.5.2 Self-sensing characteristic curve 54 2.6 Summary 62 Chapter 3 Modeling of SMA actuator 64 3.1 Strain-temperature hysteresis modeling 67 3.1.1 What is hysteresis? 67 3.1.2 Duhem differential model 68 3.1.3 Strain-temperature hysteresis modeling of SMA actuator 72 3.2 Inverse strain-temperature hysteresis modeling of SMA actuator 86 3.3 Thermal dynamics modeling of SMA actuator 92 3.4 Elastic potential energy model 97 3.5 PWM duty ratio generator 99 3.6 Modeling of self-sensing characteristic curve 101 3.7 Summary 120 Chapter 4 Displacement control of SMA actuator 123 4.1 PID-controller with self-sensing feedback 124 4.2 Feedforward inverse hysteresis compensator 131 4.3 Switching controller 137 4.4 Summary 145 Chapter 5 SMA-based hexapod robots 147 5.1 SMABOT I 148 5.2 SMABOT II 150 5.3 SMABOT III 154 5.4 Gait for SMABOTs 156 5.5 SMABOT IV 159 5.5.1 Design concept of the SMABOT IV 159 5.5.2 Fabrication of the SMABOT IV 164 5.6 Turning of SMABOT IV 173 5.7 Summary 175 Chapter 6 Navigation of the SMABOT IV 177 6.1 Definition of coordinate frames 179 6.2 Sensors 181 6.2.1 Accelerometer 181 6.2.2 Gyroscope 187 6.2.3 Inertial measurement unit 187 6.2.4 Step touch sensor 195 6.2.5 Electric compass sensor 200 6.3 Kalman filter 208 6.3.1 How it come to be called a filter 209 6.3.2 Discrete-time Kalman filter algorithm 210 6.4 Allan variance analysis 211 6.4.1 Methodology 212 6.4.2 Representation of noise terms in Allan variance 214 6.4.3 Testing results 216 6.5 Discrete-time H∞ filter 224 6.6 Sensor fusion for the attitude of SMABOT IV 225 6.6.1 Attitude model 225 6.6.2 Experimental results 232 6.7 Legged odometry 239 6.8 Displacement of SMABOT IV 241 6.9 Summary 243 Chapter 7 Conclusions and future work 245 7.1 Conclusions 245 7.2 Future work 250 Appendix A Tables for calculating the convection heat-transfer coefficient 253 Appendix B Ziegler-Nichols tuning of PID-controller 256 Appendix C Derivation of discrete-time Kalman filter 258 Appendix D Representation of noise terms in Allan variance 263 Appendix E Derivative rule for inverses 269 References 270 | |
| dc.language.iso | en | |
| dc.title | 形狀記憶合金致動器的建模、控制及其在六足仿生機器人上之應用 | zh_TW |
| dc.title | Modeling and Control of Shape Memory Alloy Actuator and its Application to a Hexapod Biomimetic Robot | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-1 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 胡竹生(Jwu-Sheng Hu),譚俊豪(Jiun-Hau Tarn),陳永耀(Yung-Yaw Chen),連豊力(Feng-Li Lian),陳明新(Min-Shin Chen),林沛群(Pei-Chun Lin) | |
| dc.subject.keyword | 形狀記憶合金致動器,自感應,反遲滯補償器,六足仿生機器人,感測器融合,離散時間Kalman濾波器,離散時間H∞濾波器,Allan變異量分析,導航, | zh_TW |
| dc.subject.keyword | shape memory alloy (SMA) actuator,self-sensing,inverse hysteresis compensator,hexapod biomimetic robot,sensor fusion,discrete-time Kalman filter,discrete-time H∞ filter,Allan variance analysis,navigation, | en |
| dc.relation.page | 278 | |
| dc.rights.note | 未授權 | |
| dc.date.accepted | 2009-10-19 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
| 顯示於系所單位： | 機械工程學系 | |
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