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研究生: 徐天助
論文名稱: 模糊可微分小腦模型晶片系統之設計
指導教授: 洪欽銘
學位類別: 碩士
Master
系所名稱: 工業教育學系
Department of Industrial Education
論文出版年: 2004
畢業學年度: 92
語文別: 中文
論文頁數: 84
中文關鍵詞: 模糊邏輯控制器可微分小腦模型控制器IC 設計現場可程式化閘陣列線性壓電陶瓷馬達
英文關鍵詞: Fuzzy Logical Controller, Differentiable Cerebellar Model, Articulation Controller,, FPGA, IC Design,, Linear Piezoelectric Ceramic Motor.
論文種類: 學術論文
相關次數: 點閱:215下載:1
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  • 本研究將設計一個整合模糊控制器與可微分小腦模型控制器的晶片。
    模糊邏輯控制器為仿效人類模糊判斷,採用模糊知識庫來描述受控系統的
    控制邏輯,比一般傳統控制方法擁有更好的強健性與適應性,但其模糊知
    識庫需採嘗試錯誤法來建立,且有穩態誤差,並無法保證達到精確的控
    制,經由可微分小腦模型控制器的加入,可以改善模糊邏輯控制器的缺
    點,縮短以嘗試錯誤法建立模糊知識庫的時間,進而提昇控制系統的效
    能,降低系統的追蹤誤差,並且有效地提昇控制精確度。本研究係以FPGA
    來設計本晶片,內含FLC 與DCMAC。本研究在FLC 方面以Mamdani 模
    糊推論法做為推論機制,高度法為解模糊策略,DCMAC 方面,以高斯查
    表法、非雜湊式映射位址運算,採FLC 與DCMAC 平行運算法的方式實
    現。最後將本研究應用於超音波線性壓電陶瓷馬達的定位控制上,證實本
    晶片系統,並驗證其具良好的控制效能

    The object of this thesis is building the FDCMAC chip system with
    integrating Fuzzy Logical Controller (FLC) with Differentiable Cerebellar
    Model Articulation Controller (DCMAC). FLC is imitating fuzzy judgment of
    human. It uses the fuzzy knowledge base to descript controlling logic of
    controlled system. Compared with general controller, FLC is more robust and
    suitable. But FLC has some steady state error, and the time of building fuzzy
    knowledge base is very long by try and error. It couldn’t be accurate in control.
    With integrating DCMAC and FLC into FDCMAC, it can improve the
    disadvantage of FLC, shortening the time of building fuzzy knowledge base,
    enhancing the performance of FLC, reducing error of tracing system, and
    making accuracy rising. In this study, it uses the FPGA to implement
    FDCMAC chip system. FLC, DCMAC and the main control is designed on the
    FPGA. In designing FLC, we adopt the Mamdani method to be the method of
    fuzzy inference. In designing DCMAC, we adopt lookup-table of Gauss
    function. And we design parallel FLC and DCMAC computing capability on
    FPGA by Verilog HDL. Finally, the FDCMAC chip system will experiment on
    controlling linear piezoelectric ceramic motor (LPCM) to prove that it has good
    performance of control.

    中文摘要……………………………………………………………………….. I 英文摘要……………………………………………………………………….II 總目錄………………………………………………………………………... III 圖目錄……………………………………………………………………….... V 表目錄…………………………………………………………………….... VIII 第一章緒論…………………………………………………………………. 1 1.1 研究背景與動機………………………………………………… 1 1.2 研究目的………………………………………………………… 3 1.3 範圍與限制……………………………………………………… 4 1.4 研究方法………………………………………………………… 4 1.5 研究步驟………………………………………………………… 5 第二章模糊控制與小腦模型控制…………………………………………. 7 2.1 模糊控制理論…………………………………………………… 7 2.1.1 理論背景…………………………………………………. 7 2.1.2 模糊集合的定義與操作…………………………………. 8 2.1.3 模糊集合運算…………………………………………... 10 2.1.4 模糊推論………………………………………………... 14 2.1.5 模糊控制………………………………………………... 16 2.2 小腦模型控制器理論………………………………………...... 20 2.2.1 小腦模型控制器理論背景……………………………... 20 2.2.2 傳統小腦模型控制器CMAC………………………….. 21 2.2.3 可微分小腦模型控制器DCMAC……………………... 27 2.2.4 CMAC 與DCMAC 的比較……………………………...34 第三章FDCMAC 控制器與晶片設計…………………………………..... IV 3.1 控制系統之架構……………………………………………….. 37 3.2 主控制器FLC 架構設計……………………………………..... 38 3.3 輔助控制器DCMAC 設計……………………………………..40 3.4 FDCMAC 非線性系統模擬……………………………………. 43 3.5 FPGA 積體電路設計…………………………………………… 46 3.6 FLC 與DCMAC 的IC 設計…………………………………… 49 3.7 線性壓電陶瓷馬達LPCM…………………………………….. 50 第四章FDCMAC 晶片設計與實驗……………………………………..... 52 4.1 FDCMAC 晶片及系統架構設計………………………………. 52 4.2 FDCMAC 硬體架構規劃………………………………………. 53 4.2.1 FDCMAC 功能規劃…………………………………….. 53 4.2.2 FDCMAC 單元規劃…………………………………….. 54 4.3 FDCMAC 設計…………………………………………………. 57 4.3.1 訊號擷取Single Catch…………………………………. 57 4.3.2 模糊邏輯控制FLC…………………………………….. 59 4.3.3 可微小腦模型控制DCMAC………………. …………. 67 4.3.4 訊號處理Single Process……………………………….. 71 4.4 受控電路設計………………………………………………….. 73 4.4.1 數位類比轉換DAC…………………….……………… 73 4.4.2 編碼Encoder……………………………….……………73 4.5 FDCMAC 控制系統整體外觀…………………………………. 74 4.6 實驗結果……………………………………………………….. 76 第五章結論與建議……………………………………………………....... 82 參考文獻…………..…………..………….………………………………….. 84

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