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研究生： 李欣翰
Hsin-Han Lee
論文名稱： 雙輪倒單擺車之智慧型運動控制
Intelligent Motion Control of Two Wheel Inverted Pendulum Vehicle
指導教授： 黃緒哲
Shiuh-Jer Huang
口試委員: 張以全
Peter I-Tsyuen Chang
周瑞仁
Jui-jen Chou
學位類別： 碩士
Master
系所名稱： 工程學院 - 機械工程系
Department of Mechanical Engineering
論文出版年： 2015
畢業學年度： 103
語文別： 中文
論文頁數： 97
中文關鍵詞： FSMC 、雙輪倒單擺車 、Arduino 、陀螺儀 、加速度計 、死區
外文關鍵詞： FSMC, Two-Wheel Inverted Pendulum, Arduino, Gyroscope, Accelerometer, Dead Zone
相關次數： 點閱：327  下載：6 
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    • 本研究主要是進行雙輪倒單擺車的自動運動控制，雙輪倒單擺車使用Arduino Nano 作為控制核心，利用陀螺儀及加速度計量測車身傾斜角及車身傾斜角速度，並透過卡爾曼濾波器進行資料融合，得到較佳的傾斜角資訊。使用直流輪轂馬達作為動力源，透過旋轉編碼器量測輪轂馬達的位移量及轉速，並在前方設有轉向機構，透過電位計達到兩輪差速轉向功能。
    控制器使用不需模型並具有高強健性的模糊滑動模式控制器(Fuzzy Sliding Mode Control)，由於輪轂馬達存在著死區的特性，因此將死區直接設計在模糊規則中，使其達到穩定平衡控制，並設計兩輪同步控制器、速度控制器、位置控制器以提升輪車之移動性能，經實驗結果證明，使用 FSMC 控制器能成功使倒單擺車達成各種動作之控制。

    In this thesis, the design and implementation of two-wheel inverted pendulum (TWIP) vehicle motion control is investigated. Arduino Nano is used as the controller of this system. An accelerometer and gyroscope sensors are used to measure the tilt angle and angular velocity of the inverted pendulum. Kalman Filter is employed to estimate the accurate tilt angle based on sensor fusion process. DC hub motor is employed as the wheel driving power and encoders are used to measure the rotational speed of motors. TWIP vehicle turning is based on the handle bar potentiometer signal.
    The model-free and robust fuzzy sliding model controller (FSMC) is chosen for controlling this system. The significantly dead zone characteristic is considered into fuzzy rule base directly. In addition, TWIP balance control, wheel synchronization control, velocity and position control blocks are designed and integrated into the system control for improving the vehicle motion performance. The experimental results show that the FSMC controller successfully monitors the TWIP vehicle dynamic operator.

    摘要 I Abstract II 致謝 III 目錄 IV 圖目錄 VII 表目錄 XII 第一章 緒論 1 1.1 文獻回顧 1 1.2 研究動機 4 1.3 論文架構 4 第二章 系統架構 5 2.1 雙輪倒單擺硬體架構 7 2.1.1 旋轉編碼器E6C2-C 7 2.1.2 三軸加速度計MMA7361 9 2.1.3 雙軸陀螺儀LPY503AL 12 2.1.4 卡爾曼濾波器(Kalman Filter) 14 2.1.5 無線通訊模組XBee S1 16 2.1.6 直流輪轂馬達 17 2.2 Arduino Nano 3.0 19 2.2.1 計時計數器與脈寬調變訊號(Timer、PWM) 21 2.2.2 類比數位轉換器(ADC) 23 2.2.3 外部訊號變化中斷(PCINT) 25 2.3 馬達驅動電路 27 2.3.1 半橋驅動晶片 IR2104 29 2.3.2 靴帶電路(Bootstrap) 30 2.4 主控制板電路 32 第三章 控制理論 35 3.1 模糊邏輯控制 35 3.1.1 模糊集合與隸屬函數 35 3.1.2 基本模糊控制器架構 36 3.2 滑動模式控制 40 3.2.1 滑動模式控制原理 40 3.2.2 滑動模式理論基礎 41 3.3 模糊滑動模式控制 44 第四章 實驗結果 47 4.1 平衡控制實驗 48 4.1.1 實驗說明 48 4.1.2 實驗參數 49 4.1.3 FSMC平衡控制器實驗結果 50 4.1.4 實驗結果討論 53 4.2 兩輪同步控制器 55 4.2.1 實驗說明 55 4.2.2 實驗參數 55 4.2.3 FSMC兩輪同步控制器實驗結果 56 4.2.4 實驗結果討論 60 4.3 輪車前進速度控制器 63 4.3.1 實驗說明 63 4.3.2 實驗參數 63 4.3.3 FSMC速度控制器實驗結果(V=0.2 m/sec) 65 4.3.4 FSMC速度控制器實驗結果(V=0.3 m/sec) 69 4.3.5 實驗結果討論 73 4.4 位置控制實驗 74 4.4.1 實驗說明 74 4.4.2 實驗參數 74 4.4.3 FSMC位置控制實驗結果(P=1 m) 76 4.4.4 FSMC位置控制實驗結果(P=2 m) 80 4.4.5 實驗結果討論 83 4.5 手把轉向測試 86 4.5.1 實驗說明 86 4.5.2 實驗結果 86 4.5.3 實驗結果討論 90 第五章 結論與未來展望 93 5.1 結論 93 5.2 未來展望 93 參考文獻 94

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