| 研究生: |
黎乃文 Li, Nai-Wen |
|---|---|
| 論文名稱: |
適應性扭矩控制應用於健身器械 Adaptive Torque Control Applied to Fitness Machines |
| 指導教授: |
蔡南全
Tsai, Nan-Chyuan |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 機械工程學系 Department of Mechanical Engineering |
| 論文出版年: | 2020 |
| 畢業學年度: | 108 |
| 語文別: | 中文 |
| 論文頁數: | 109 |
| 中文關鍵詞: | 輔助扭矩健身器械 、適應性阻抗控制 、模糊變阻抗控制 、無感測器阻抗控制 |
| 外文關鍵詞: | Torque Assist Fitness Machines, Adaptive Impedance Control (AIC), Fuzzy Variable Impedance Control, Sensorless Impedance Control |
| 相關次數: | 點閱:148 下載:5 |
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本論文提出一新式電動健身器械,利用適應性阻抗控制器(Adaptive Impedance Controller, AIC)將期望之阻抗特性實現於操作者與健身器械之間,以此在訓練上主要區分成兩種模式,主動模式下保有傳統健身器械之功能,被動模式則可使操作者在保有自主性的情況下跟隨一較有效率之操作軌跡進行訓練,使新手能更快速地進入專業健身領域; 並利用干擾觀測器(Disturbance Observer, DOB)衍生而成之外力估測器(External Force Estimator, EFE)估測出操作者之外部施加力矩,達到了無感測器阻抗控制,節省了感測器成本及防止系統頻寬降低; 而若是系統判斷操作者在訓練中途產生力竭現象,將切換至第三種模式,輔助模式,藉由模糊推論系統(Fuzzy Inference System, FIS)即時調變AIC中之期望剛性參數,以類似輔助扭矩概念,使操作者能在力竭時隨著一安全軌跡,且仍維持肌肉收縮之狀態下完成整趟操作,達成了增進訓練效率與安全之目的。
而本論文搭建一電動健身器械之雛形,利用dSPACE公司之DS1104作為控制設置,以實際驗證控制策略之成效。 於實驗結果中,AIC與EFE皆有相當程度之表現,AIC皆能維持軌跡追蹤之均方根誤差在4.10 degree內,EFE則能維持扭矩估測均方根誤差在3.25 N-m內,達成控制目標; 而在FIS方面,因有以外部干擾作為輸入,可比無外部干擾作為輸入之FIS具有更良好之抗干擾特性,將軌跡追蹤之誤差區間從[-29.49, 0.00] degree抑制在[-8.32, 0.00] degree之中。
A novel electric fitness machine which enhances the training efficiency and ensures the operator safety is proposed by this thesis. Firstly, Adaptive Impedance Controller (AIC) is employed for realizing the desired impedance between the operator and the fitness machine. Its operation can be classified into active mode, which is as same as traditional fitness machines, and passive mode, which can lead operators to follow an efficient trajectory consciously. Secondly, to replace a force/torque sensor, the External Force Estimator (EFE) is used for sensorless impedance control and prevention from bandwidth reduction and high expense. Thirdly, if operators feel exhausted, the desired impedance parameters will be adjusted by Fuzzy Inference System (FIS) in real-time to make operators finish the round of training completely under muscle contraction. Lastly, an electric fitness machine prototype is established to verify the overall control strategy based on the DS1104 interface setup. According to the experimental results, AIC can regulate the root-mean-square error of position tracking under 4.10 degree and EFE can regulate the root-mean-square error of the external torque estimation below 3.25 N-m. The FIS, to which the magnitude of external force is the third input, can reduce the position tracking error region from [-29.49, 0] degree to [-8.32, 0] degree and significantly improve the capability of anti-disturbance.
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