隨著人口高齡化趨勢加劇，行動能力衰退所帶來的健康與生活品質問題日益受到關注，下肢輔具外骨骼逐漸成為協助老年人，以及行動不便者的重要工具。本論文提出一套基於自適應振盪器之下肢行動輔具外骨骼助力機制。首先，本論文回顧兩種自適應振盪器，且提出引入自動化程度之傅立葉自適應振盪器，將對週期性訊號之追蹤誤差，用以調整振盪器之學習率，使輸入訊號在進行頻率切換時能增加振盪器之收斂速度與穩定性，此外，透過引入自動化程度之傅立葉自適應振盪器之相位輸出作為步態相位的估測依據，為後續助力扭矩控制提供準確之相位資訊。在助力機制方面，本論文探討線上以及離線優化。線上優化使用協方差矩陣適應演化策略，將使用者反饋納入優化過程，以即時更新扭矩曲線參數。而本論文將離線優化之扭矩曲線設計視為非線性最佳化問題，提出兩種輔助扭矩參數化方式，其一為以雙曲正切函數建構之助力扭矩曲線，另一種則使用拉格朗日多項式插值法，透過對人的步態分析與機械功率考量，設計合適的限制條件以及目標函數，求解出客製化之助力扭矩曲線。最後，根據模擬與實驗場景測試所獲得之結果，顯示本論文所提出之助力機制的有效性。

With the intensifying trend of population aging, issues related to mobility decline and its impact on health and quality of life are receiving increasing attention. Lower-limb exoskeletons have gradually become important tools to assist the elderly and individuals with mobility impairments. This thesis proposes a lower-limb assistive mechanism based on an adaptive oscillator. First, Fourier-based adaptive oscillator with Automation Level is discussed. This thesis proposed using tracking error of periodic signals to adjust the learning rate of the oscillator, then the convergence speed and stability of the oscillator are improved during frequency transitions. Moreover, the phase output of the proposed oscillator is used as the basis for gait phase estimation, providing accurate phase information for the subsequent assistive torque control. In terms of the assistive mechanism, offline optimization approaches are explored. The offline optimization formulates the torque design as a nonlinear optimization problem and proposes two parameterization strategy for assistive torque: one based on hyperbolic tangent functions, and the other using Lagrange polynomial interpolation. Based on human gait analysis and mechanical power considerations, suitable constraints and objective functions are designed to derive personalized assistive torque profiles. Finally, simulation and experimental results verify the effectiveness of the proposed assistive mechanism.

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