簡易檢索 / 詳目顯示

研究生: 劉威呈
Liu, Wei-Cheng
論文名稱: 模糊邏輯於功能性神經電刺激控制器之應用
Application of Fuzzy Logic to Design of Functional Neuromuscular Stimulation Controller
指導教授: 朱銘祥
Ju, Ming-Shaung
林宙晴
Lin, C.-C. K
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: 2006
畢業學年度: 94
語文別: 中文
論文頁數: 73
中文關鍵詞: 功能性神經電刺激簡化電流脈寬調變法模糊控制神經工程
外文關鍵詞: FNS, SAWM, fuzzy control, neural engineering
相關次數: 點閱:74下載:6
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 摘 要
    功能性神經電刺激術主要用於恢復中樞神經與周邊神經間失去聯繫之病患,為神經工程主要方法。此法利用植入式電極如銬型電極與周邊神經接觸,由電刺激器控制電流強度與脈寬使癱瘓之肌肉產生收縮力,但由於受刺激之肌肉之徵召曲線會隨時間而變化且肌肉容易疲勞。本研究之目的即在於發展一套能同時控制電流強度與脈寬之方法,同時配合PID和三種模糊控制器以進行家兔踝關節扭矩控制。將家兔踝關節在自然角度及不同之角度下進行等長扭矩電刺激的結果顯示:(1)Fuzzy PD響應快,超越量小但干擾靈敏度高且穩態誤差太高(2)Fuzzy PD+I響應快超越量小且穩態誤差小(3)Fuzzy PI穩態誤差最小,控制訊號平滑,安定時間短,但超越量稍大。三者中以Fuzzy PI之ITAE值最小。總之,本研究發展之簡化電流脈寬調變法可以避免受刺激肌肉快速疲勞,Fuzzy PI控制較PID控制優且適用於踝關節在運動範圍內之等長力矩控制。

    Abstract
    The functional neuromuscular stimulation (FNS) is a major method in neural engineering for restoring the patients who lose the connection between central and peripheral nervous systems. IN FNS an implanted electrode, e.g. cuff electrode contacts with the peripheral nerve and the amplitude and pulse-width of the stimulus current is controlled by an electrical stimulator. Due to the time-varying characteristics of muscle recruitment and fast fatigue of artificially stimulated muscles, it is necessary to develop a method which can simultaneously control the amplitude and pulse-width of the stimulus and combined with feedback control algorithms to yield better FNS. The goal of this thesis is to develop a simplified amplitude/pulse-width modulation (SAWM) technique and combined with a PID and three fuzzy controls, namely, Fuzzy PD, Fuzzy PI, Fuzzy PD+I to the isometric ankle torque control of anesthetized rabbits. The rabbit’s ankle was fixed at natural and various positions in the range of motion and different control algorithms were employed to test the step response of the FNS system. Experimental results showed that: (1) Fuzzy PD has fast response, small overshoot percentage but high sensitivity to disturbance and large steady-state error (2) Fuzzy PD+I has fast response, small overshoot percentage and small steady-state error (3) Fuzzy PI has smallest steady-state error, smaller settling time, smoother control signal but large overshoot percentage. For the integrated time multiplied by absolute error (ITAE), the Fuzzy PI is superior to others. From the results, one may conclude that the SAWM technique is effective in preventing the fatigue of stimulated muscles. Fuzzy PI control is better than PID control and it is adaptive to the ankle position for isometric torque control on anesthetized rabbits.

    目 錄 摘 要 i Abstract ii 誌 謝 iii 目 錄 iv 圖目錄 vi 表目錄 viii 符號說明 ix 第一章 緒論 1 1-1 研究背景 1 1-2 文獻回顧 6 1-3 研究動機與目的 8 1-4 本文架構 9 第二章 研究方法與實驗 10 2-1 電流強度與脈寬調變 10 2-2 模糊邏輯控制器設計 14 2-2-1 設計流程 15 2-2-2 模糊控制器型式 28 2-3 PID控制器設計 31 2-4 系統模擬 33 2-5 實驗設備與流程 35 2-5-1 電極形式 35 2-5-2 實驗平台架構 37 2-5-3 動物實驗流程 39 第三章 結果 41 3-1 徵召曲線之找尋與簡化 41 3-2 控制器模擬 44 3-2-1 受控場模型判認 44 3-2-2 控制器模擬 46 3-3 動物控制實驗結果 48 3-3-1 PID控制器 48 3-3-2 模糊控制器 51 3-4 不同角度之力矩控制 58 第四章 討論 61 4-1 徵召曲線與控制器關係 61 4-2 控制器模擬 64 4-3 控制器實現後之性能比較 65 4-4 不同角度之力矩控制 66 4-5 與文獻比較 67 第五章 結論與建議 69 5-1 結論 69 5-2 建議 70 參考文獻 71 自 述 73

    參考文獻
    [1] W. L. C. Rutten, H. J. Wier, and J. H. M. Put, “Sensitivity and selectivity of intraneural using a silicon electrode array,” IEEE Trans. Biomed. Eng., vol. 38, no. 2, pp. 192-196, 1991.

    [2] M. S. Ju, H. C. Chien, G. S. Chen, C. C. K. Lin, C. H. Chang, and C. W. Chang, “Design and fabrication of multi-microelectrode array for neural prosthesis,” Chin. J. Med. Biol. Eng., vol. 22, pp. 33-40, 2002.

    [3] A. Q. Choi, J. K. Cavanaugh, and D. M. Durand, “Selectivity of multiple-contact nerve cuff electrodes: a simulation analysis,” IEEE Trans. Biomed. Eng., vol. 48, pp. 165-172, 2001.

    [4] D. J. Tyler and D. M. Durand, “Functionally selective peripheral nerve stimulation with a flat interface nerve electrode,” IEEE Trans. Neural. Syst. Rehabil. Eng., vol. 10, pp. 294-303, 2002.

    [5] A. Kralj and T. Bajd, “Functional electrical stimulation: standing and walking after spinal cord injury” Boca Raton, FL: CRC, 1989.

    [6] R. Davoodi and B. J. Andrews, “FES standing up in paraplegia: a comparative study of fixed parameter controllers,” IEEE in Med. Biol. Society, vol. 1, pp. 447-448, 1996.

    [7] J. J. Abbas, “Feedback control of coronal plane hip angle in paraplegic subjects using neuromuscular stimulation,” IEEE Trans. Biomed. Eng. vol. 38, pp. 678-698, 1991.

    [8] N. Lan, P.E. Crago, and H. J. Chizeck, “Control of the end-point force of a multijoint limb by functional electrical stimulation,” IEEE Trans. Biomed. Eng. vol. 38, pp. 953-965, 1991.

    [9] N. Itakura, K. Fujita, K. Kubo, Y. Iguchi, and H. Minamitani, “Evaluation of FES control system employing adaptive and PI controllers,” IEEE in Med. Biol. Society, vol. 4, pp. 1738-1740, 1988.

    [10] R. Davoodi, and B. J. Andrews, “Computer simulation of FES standing up in paraplegia: a self-adaptive fuzzy controller with reinforcement learning,” IEEE Trans. Rehabil. Eng. vol. 6, pp. 151-161,1998.

    [11] M. S. Hatwell, B. J. Oderkerk, C. A. Sacher, and G. F. Inbar, “The development of a model reference adaptive controller to control the knee joint of paraplegics,” IEEE Trans. Automat. Contr. vol. 36, pp. 683-691, 1991.

    [12] P. Bonato, S. H. Roy, M. Knaflitz, and C. J. De luca, “Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions,” IEEE Trans. Biomed. Eng., vol. 48, pp. 745-753, 2001.

    [13] P. Mela, P. H. Veltink, P. A. Huijing, S. Salmons, J. C. Jarvis, “The optimal stimulation pattern for skeletal muscle is dependent on muscle length,” IEEE Trans. Neural. Syst. Rehabil. Eng., vol. 10, pp. 85-93, 2002.

    [14] H. Qi, D. J. Tyler, and D. M. Durand, “Neurofuzzy adaptive controlling of selective stimulation for fes: a case study,” IEEE Trans. Rehab. Eng., vol. 7, pp. 183-192, 1999.

    [15] H. S. Cheng, M. S. Ju, and C. C. K. Lin, “Estimation of peroneal and tibial afferents from a multi-channel cuff placed on sciatic nerve,” Muscle & Nerve, vol. 32, pp. 589-599, 2005.

    [16] C. C. Lee, “Fuzzy logic in control system: Fuzzy logic controller, Part I and Part II,” IEEE Trans. System, Man and Cyb., vol. 20, pp. 404-435, 1990.

    [17] J. Jan, “Tuning of fuzzy PID controllers,” report no 98-H 871(fpid), 1998. http://www.iau.dtu.dk/~jj/pubs/fpid.pdf

    [18] H. J. Chizeck, P. E. Crago, and L. S. Kofman, “Robust closed-loop control of isometric muscle force using pulsewidth modulation,” IEEE Trans. Biomed. Eng. vol. 35, pp. 510-517, 1988

    下載圖示 校內:2011-07-26公開
    校外:2011-07-26公開
    QR CODE