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dc.contributorTsai Ching-Chihen_US
dc.contributor.authorCoulibaly, Souleymaneen_US
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dc.description.abstract本論文提出對於全方位球型驅動載具的系統設計,數學建模和運動控制的方法和技術。全方位球型驅動載具是藉由四顆馬達驅動的反向球鼠驅動機構的球形機器人為基礎。此外,它包含一個數位信號處理器(DSP),一個雙軸傾角傳感器(傾斜儀),一個速率陀螺儀,兩個針對X-Z平面和Y-Z平面的PD控制器來達成自我平衡和速度控制。為了往一方向移動, 坐在上面的騎乘者必須稍微向前或往後傾斜自身來改變他的傾角。系統載具的用處是讓人們,老人或行動不便者人乘坐短距離位移(亦可在家裡,在醫院,在企業...等)。此功能的硬體實現是利用四個大功率伺服馬達與他們的驅動器,以反向球鼠驅動為本論文提出對於全方位球型驅動載具的系統設計,數學建模和運動控制的方法和技術。全方位球型驅動載具是藉由四顆馬達驅動的反向球鼠驅動機構的球形機器人為基礎。此外,它包含一個數位信號處理器(DSP),一個雙軸傾角傳感器(傾斜儀),一個速率陀螺儀,兩個針對X-Z平面和Y-Z平面的PD控制器來達成自我平衡和速度控制。為了往一方向移動, 坐在上面的騎乘者必須稍微向前或往後傾斜自身來改變他的傾角。系統載具的用處是讓人們,老人或行動不便者人乘坐短距離位移(亦可在家裡,在醫院,在企業...等)。此功能的硬體實現是利用四個大功率伺服馬達與他們的驅動器,以反向球鼠驅動為基礎的球型車輪運動和平台。 系統軟體的實現是根據由雙軸向的傾斜儀和陀螺儀的角速度傳感計量測出騎乘者的身體傾斜角。藉由DSP單晶片控制器(TMS320F28335)的操作,雙PD控制法則,PWM控制信號被發送到四個直流伺服馬達經由驅動器。線性化模型的自身平衡和速度控制器將被設計藉由LQR方法達成。非線性適應模型是被設計使用模糊小波CMAC。同時騎乘者的重量以及摩擦力的補償項是被考慮進去以達成高效能的全方位球型驅動載具。模擬及實驗結果是用來闡述提出的控制系統是能夠提供適當的控制行為來達成自身平衡以及速度控制。zh_TW
dc.description.abstractThis thesis presents methodologies and techniques for system design, mathematical modeling and motion control of an Omnidirectional Ball-driven Vehicle. The objective of the vehicle is designed to allow people, elderly or disabled to ride for short distance displacement (in home, in hospital, in enterprise…). The Omnidirectional Ball-driven Vehicle works on the base of a ball robot with an inverse mouse-ball driving mechanism actuated by four motors. The proposed control system is equipped with one digital signal processor (DSP), one dual-axis inclinometer (tilt), one rate gyroscope, two PD controllers for X-Z and Y-Z planes to achieve self-balancing and speed control. To move the vehicle in any direction, the rider, sitting on it, must tilt himself slightly to change his appropriate inclination. The hardware implementation of this vehicle is the use of four high-power servo motors with their drivers, an inverse mouse-driven based ball-type wheel motion and a platform. The system software is realized and coded by standard C language according to the rider’s tilt angle which is measured by the dual-axial inclinometer and gyro angular velocity sensing. The operation is performed by the DSP single-chip controller (TMS320F28335); after executing the double-PD control laws, the PWM control signals are sent to the four DC servo motors via the drivers. With the linearized model, both self-balancing and speed controllers are designed using LQR approach. The nonlinear adaptive self-balancing controller is also designed using the wavelet fuzzy CMAC. Moreover, the rider’s weight and the friction compensation term are taken into account in order to get high-efficiency and high-performance control of the omnidirectional ball-driven vehicle. In particular, the friction compensation term can also be done by the wavelet fuzzy CMAC. Simulations and experimental results are conducted to indicate that the proposed control system is capable of providing appropriate control actions to satisfactorily achieve self-balancing and speed control.en_US
dc.description.tableofcontentsContents Acknowledgements i 中文摘要…. ii Abstract….. iii Contents….. iv List of Figures vii List of Tables x List of Acronyms xii Chapter 1 Introduction 1 1.1 Introduction 1 1.2 Literature Review 2 1.3 Motivation and Objectives 6 1.4 Main Contributions 8 1.5 Thesis Organization 9 Chapter 2 System Design and Implementation 10 2.1 Introduction 10 2.2 System Structure and Mechatronic Design 10 2.2.1 System Description of the Ball-Driven Vehicle 10 2.2.2 Mechatronic Design 12 2.3 Description of Key Components 13 2.3.1 Digital Signal Processor 15 2.3.2 Dual-axis Tilt Sensor 17 2.3.3 Dual-axis Gyroscope IDG500 21 2.3.4 Motors and Drivers 28 2.3.5 Power Supply circuit 30 2.4 Control System and Architecture 31 2.5 Experimental Results and Discussion 34 2.6 Chapter Concluding Remarks 35 Chapter 3 Mathematical Modeling 36 3.1 Introduction 36 3.2 Mathematical Modeling 37 3.2.1 Vehicle Dynamics in the x-z Plane 38 3.2.2 Vehicle Dynamics in the y-z Plane 46 3.3 Parameters Calculations 48 3.4 Chapter Concluding Remarks 49 Chapter 4 Self-Balancing Controller Design Using LQR Approach and Backstepping with WFCMAC 50 4.1 Introduction 50 4.2 Linearized Model 51 4.3 Adaptive Linearized Self-Balancing Controller Design Using LQR Approach. 54 4.3.1 Introduction 54 4.3.2 State Feedback 54 4.3.3 Linear Quadratic Regulator (LQR) Controller Design 56 4.3.4 Adaptive Friction Compensation 58 4.4 Adaptive Nonlinear Self-Balancing Controller Design Using Backstepping and Wavelet Fuzzy CMAC 59 4.4.1 Introduction 59 4.4.2 Review on Wavelet Fuzzy CMAC 60 4.4.3 Backstepping Control Using Wavelet Fuzzy CMAC 69 4.5 Simulations Results and Discussions. 74 4.5.1 Determination of the Values of some Parameters 74 4.5.2 Simulations Results for the Adaptive LQR controller 75 4.5.3 Simulations Results of the Adaptive Nonlinear Self-Balancing Controller Using Backstepping with Wavelet FCMAC 78 4.6 Chapter Concluding Remarks. 81 Chapter 5 Speed Controller Design Using LQR and Wavelet Fuzzy CMAC 82 5.1 Introduction 82 5.2 Perturbed Linearized Model 83 5.3 Adaptive Linearized Speed Control Using LQR Approach 85 5.3.1 Introduction 85 5.3.2 State Feedback 85 5.3.3 Linear Quadratic Regulator (LQR) Controller Design 87 5.3.4 Adaptive Friction Compensation 89 5.4 Adaptive Linear Speed Controller Design Using LQR with Wavelet Fuzzy CMAC 91 5.5 Simulations Results and Discussions 95 5.5.1 Simulations Results for the Adaptive LQR Speed Controller 95 5.5.2 Simulations Results for the Adaptive Speed Controller Model via LQR with Wavelet FCMAC 98 5.6 Chapter Concluding Remarks 102 Chapter 6 Conclusions and Future Work 103 6.1 Conclusions 103 6.2 Future Work 104 References 105zh_TW
dc.subjectOmnidirectional Ball-Driven Vehicleen_US
dc.subjectLinear quadratic regulatoren_US
dc.subjectFuzzy CMACen_US
dc.subjectWavelet fuzzy CMACen_US
dc.titleSystem Design and Control of an Omnidirectional Ball-Driven Vehicleen_US
dc.typeThesis and Dissertationzh_TW
item.openairetypeThesis and Dissertation-
item.fulltextwith fulltext-
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