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研究生: 吳啟揚
Wu, Chi-Yang
論文名稱: 利用滑模徑向基函數類神經控制法於磁浮平台動態系統驗證
Verification of Ball and Plate System using SMC Based on RBFNN for Magnetic Suspension Platform
指導教授: 林清一
Lin, Chin E.
學位類別: 碩士
Master
系所名稱: 工學院 - 航空太空工程學系
Department of Aeronautics & Astronautics
論文出版年: 2015
畢業學年度: 103
語文別: 英文
論文頁數: 132
中文關鍵詞: 徑向類神經網路滑模控制球板系統混合式磁浮
外文關鍵詞: Radial Basis Function Neural Networks, Sliding Mode Control, Ball and Plate, Magnetic Suspension
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  • 本論文描述一機電整合系統的發展及驗證過程,此系統包含了一組兩個自由度的球與板系統以及四組混合式磁浮致動器。球板系統的動態數學模型是利用尤拉-拉格朗日(Euler-Lagrange)方程式推導而成,另一方面,磁浮致動器的動態數學模型是結合牛頓第二運動定律及克希荷夫定律(Kirchhoff’s Law)來導出。觸控面板及加速規與陀螺儀被利用來偵測球的位置及板的姿態,並結合微處理控制器及搭配四元數演算法來更新板的姿態。然後,利用提出的徑向類神經滑模控制器以減少滑模控制器的最大超越量、穩定時間以及改善整個系統的穩定表現。最後由微處理控制器產生的控制訊號透過訊號放大器來推動整個系統來進行系統動態驗證。

    This dissertation presents the development and verification of a dynamic mechatronics system for a two degree of freedom ball and plate using four hybrid mode magnetic suspension (MS) actuators. The mathematical model of ball and plate is derived through the Euler-Lagrange method. On the other hand, the model of MS actuator is derived by Newton’s Second Law and Kirchhoff’s Law. Two kinds of sensors, touch panel and MPU6050, are used to detect the ball position and plate posture by applying the quaternion algorithm to update the plate posture with the functions of microcontroller unit (MCU). The proposed control law is a radial basis function neural network sliding mode control (RBFNNSMC) which can reduce system overshoot and shorten the settling time to improve the overall system performance significantly with SMC. Finally, the calculated duty cycle of Pulse Width Modulation (PWM) signals output to this system through the signal amplifier IBT-2 module for system verification.

    ABSTRACT i ABSTRACT IN CHINESE ii 致謝 iii CONTENTS iv LIST OF TABLES viii LIST OF FIGURES ix CHAPTER I INTRODUCTION 1 1.1 Introduction 1 1.2 Literatures Survey 3 1.2.1 The Ball and Plate Literatures Survey 3 1.2.2 Magnetic Suspension System Literatures Survey 4 1.3 Motivation and Idea 5 1.4 Dissertation Outline 5 CHAPTER II DYNAMIC OF THE BALL AND PLATE SYSTEM 7 2.1 Ball and Plate System 7 2.1.1 Development of hybrid mode MS actuator 8 2.2 Dynamic Model Derivation of Ball and Plate 13 2.2.1 The Proposed Assumption 13 2.2.2 Mathematical Model 16 2.2.3 Simplification of Dynamic Equations 24 2.3 Dynamic Model Derivation of Hybrid Mode MS Actuator 26 2.3.1 Electromagnetic Force 26 2.3.2 Dynamic Model of Hybrid Mode MS Actuator 32 2.4 Simulation of Ball and Plate System 35 2.5 Concluding Remarks 38 CHAPTER III HARDWARE OF THE BALL AND PLATE SYSTEM 39 3.1 The Proposed Architecture 39 3.2 MCU STM32F103 41 3.2.1 Architecture 41 3.2.2 System Clock 43 3.2.3 Timer 45 3.2.4 Embedded Emulation 47 3.3 Touch Panel 49 3.3.1 Specification 49 3.3.2 Calibration 50 3.3.3 Position Decoding 51 3.4 MPU6050 54 3.4.1 Introduction 54 3.4.2 Angle Correction 55 3.5 IBT-2 H-bridge module 60 3.5.1 Characteristics 60 3.5.2 Application 62 3.6 Concluding Remarks 63 CHAPTER IV CONTROLLER DESIGN FOR THE BALL AND PLATE SYSTEM 65 4.1 Sliding Mode Controller Design 66 4.1.1 Development of SMC 66 4.1.2 Application of SMC in Ball and Plate System 71 4.1.3 Simulation with MATLAB/Simulink 73 4.1.4 Procedure with MCU 75 4.2 Sliding Mode Controller Based on RBFNN Design 76 4.2.1 Development of Neural Networks 76 4.2.2 Development of Radial Basis Function Neural Networks 78 4.2.3 Application of RBF Neural Networks with SMC in Ball and Plate System 79 4.2.4 Simulation with MATLAB/Simulink 81 4.2.5 Procedure with MCU 84 4.3 Tracking Missions 85 4.4 Concluding Remarks 86 CHAPTER V SYSTEM VERIFICATION 87 5.1 Preparations 87 5.2 Random Position Tracking with SMC 89 5.2.1 Position (0, 0) Tracking with SMC 89 5.2.2 Position (-6, -6) Tracking with SMC 97 5.3 Random Position Tracking with RBFNNSMC 105 5.3.1 Position (0, 0) Tracking with RBFNNSMC 106 5.3.2 Position (-6, -6) Tracking with RBFNNSMC 113 5.4 Comparison 121 5.5 Concluding Remarks 124 CHAPTER VI CONCLUSIONS 126 6.1 Conclusions 126 6.2 Further Works and Suggestions 127 REFERENCES 128

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