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研究生:廖秉德
研究生(外文):bing-der liao
論文名稱:含磁滯估測器之三軸壓電致動平台穩定適應模糊控制設計
論文名稱(外文):Stable Adaptive Fuzzy Control with Hysteresis Observer for a Three-Axis Piezoactuated Stage
指導教授:林麗章
學位類別:碩士
校院名稱:國立中興大學
系所名稱:機械工程學系所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:中文
論文頁數:105
中文關鍵詞:磁滯效應壓電致動平台
外文關鍵詞:HysteresisPiezoactuated Stage
相關次數:
  • 被引用被引用:1
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本論文根據含簡化Dahl動態磁滯模式之三軸壓電致動平台動力學模式,設計一含PD回授之穩定適應模糊控制器,其中含一估測磁滯變數的估測器。設計控制策略時,針對系統的參數辨識誤差、不確定性與耦合效應視為外部干擾,採用模糊函數近似器加以補償。並以Lyapunov穩定理論證明整體閉迴路系統的穩定性。並以MATLAB進行電腦模擬,先針對二種不同期望軌跡瞭解控制策略之追蹤性能,再以不同的耦合效應探討模糊函數近似器的補償效能,最後也以改變系統參數的方式作大量電腦模擬,以瞭解該適應控制系統之強健性。
In this thesis, based on the dynamic model of a three-axis piezoactuated stage with simplified Dahl hysteresis model, we propose a stable adaptive fuzzy controller with a hysteresis variables observer. In the control design, a fuzzy function approximator is used for compensating for the effects of parameter estimate inaccuracy, model uncertainty, and coupling among three axes(considered as external disturbance). The overall closed-loop system stability is guaranteed in the design using Lyapunov stability theory. Some computer simulations using MATLAB are conducted to study the tracking performance under different desired trajectories. The compensation performance of the fuzzy function approximator is illustrated using different coupling effects among three axes. Finally, robustness of the adaptive control system with respect to system parameter variation is also discussed.
摘要 i
Abstract ii
誌謝 iii
目錄 iv
圖目錄 vi
符號說明 viii
第一章 緒論 1
1.1研究動機 1
1.2文獻回顧 1
1.3論文大綱 3
第二章 三軸壓電致動平台控制策略推導 4
2.1三軸壓電致動平台之數學模式[6] 4
2.2三軸壓電致動平台之穩定適應控制器設計 6
2.3磁滯估測器設計[6] 10
2.4模糊函數近似器設計[6] 11
2.5參數調適律推導和整體閉迴路系統穩定性證明 13
第三章 控制策略電腦模擬 19
3.1期望軌跡規劃 19
3.2相關參數選定 26
3.3公稱系統之模擬結果 28
3.4含不確定性與模糊補償之模擬結果 43
3.5系統強健性測試 73
第四章 結論與建議 102
參考文獻 104
附錄 106
作者簡歷 108
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[6] 張柏翌,“三軸奈米平台之穩定適應控制:以ALTERA DSP發展版
實現”,國立中興大學機械工程學系,碩士論文,民國九十四年。
[7]X. Sun, and T. Chang, “Control of Hysteresis in a Monolithic Nanoactuator,” in Proc. American Control Conference, Arlington, VA, Vol. 3, pp. 2261-2266, 2001.
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[11] L. A. Zadeh, “Fuzzy Sets,” Information and Control, Vol. 8, pp. 338-353, 1965.
[12] L.-X. Wang, A Course in Fuzzy Systems and Control, Prentice Hall, 1997.
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