研究生: |
江晨瑋 Chen-Wei Chiang |
---|---|
論文名稱: |
單氣壓肌肉驅動單自由度機械手臂之即時適應性積分逆步控制 Real-time Adaptive Integral Backstepping Control of a Single Pneumatic Muscle Actuated 1-DOF Manipulator |
指導教授: |
姜嘉瑞
Chia-Jui Chiang |
口試委員: |
黃安橋
An-Chyau Huang 江茂雄 Mao-Hsiung Chiang |
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: | 2021 |
畢業學年度: | 109 |
語文別: | 中文 |
論文頁數: | 127 |
中文關鍵詞: | 氣壓肌肉致動器 、非線性系統 、時變 、遲滯 、逆步控制 、積分器 、適應性控制 |
外文關鍵詞: | Pneumatic muscle actuator, Nonlinear system, Time variance, Hysteresis, Backstepping control, Integrator, Adaptive control |
相關次數: | 點閱:368 下載:0 |
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氣壓肌肉致動器有著優良的功率重量比、成本低、清潔、易於維護、可撓性且安全性佳等優點,使其非常適合用於需要與人體緊密接觸的機器人或醫療輔具中。然而,因氣壓肌肉屬於複合材料且氣體具可壓縮性,使其具高度非線性、時變及遲滞等特性,形成快速精密運動控制上的挑戰。為了解決上述問題,本論文提出以物理模型為基礎之適應性積分逆步控制器,以達成單氣壓肌肉驅動之單自由度機械手臂的追跡控制,並使其在不同頻率下皆能維持良好的控制性能。本論文中的單自由度機械手臂,兩側分別採用氣壓肌肉及彈簧,組成不對稱的架構,使得精確的追跡控制更具挑戰性,特別是在高頻追跡的情況下。首先,在系統模型中加入積分狀態,以提升穩態追跡性能。接著以逆步控制利用李亞普諾夫法則逆向反推,確保由氣壓肌肉驅動之機械手臂及積分項所組成的非線性系統每一層動態之穩定性。最後再結合適應性控制,利用梯度下降法更新參數,在不同操作頻率下最小化追跡誤差。實驗結果顯示本論文提出的適應性積分逆步控制器,在0.1Hz到1Hz的正弦波命令下,皆能一貫地達成精確的追跡控制。具體舉例來說,在1Hz的正弦波命令下所達成的最大追跡誤差約為1.6度。
The advantages of pneumatic muscle actuator (PMA), including high power-to-weight ratio, low cost, cleanness, ease of maintenance, pliability and inherent safety, make it suitable to be utilized in a robot that intimately assists movements of a human body. The complex material composition of the PMAs and compressibility of the air, however, result in high nonlinearity, time variance and hysteresis characteristics of the PMA, posing challenges to fast and precise motion control. To deal with the above mentioned problems, an adaptive integral backstepping controller is developed in this thesis based on a physics-based model to achieve accurate and consistent tracking performance of a single PMA actuated 1-DOF manipulator at various frequencies. The asymmetric structure of the 1-DOF manipulator, with a PMA on one end and a spring on the other, also presents a challenge to precise tracking control especially at higher frequencies. An integral state is first augmented to the system model to improve the steady-state tracking performance. The backstepping controller stabilizes recursively each layer of the dynamics consisting of the nonlinear PMA actuated manipulator and the integrator using the Lyapunov approach. Finally, an adaptive algorithm based on gradient descent method is applied to achieve minimum tracking errors at various frequencies. Experimental results show that the proposed adaptive integral backstepping controller achieves precise and consistent performance tracking sinusoidal references over frequencies ranging from 0.1Hz to 1Hz. Specifically, the maximum error achieved in tracking a 1Hz sinusoidal reference is about 1.6 degrees.
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