模糊邏輯建模(FLM)方法具有能力處理非線性多值函數的優點。本論文利用國籍航空公司班機的飛航記錄器(flight data recorder, FDR)中的飛航資料，經由雜訊處理後，對飛機遭遇強烈亂流的部份進行分析。當飛機遭遇到強烈亂流時，各項氣動力係數(攻角、空速、高度、加速度儀、控制面角度…等)皆顯示激烈震盪，能真實反映出飛機遭遇強烈亂流時之變化情形。接著利用FDR中經雜訊處理後的資料及計算所得之八個氣動力係數(攻角、攻角變化率、俯仰率、折合頻率、水平控制面、馬赫數、滾轉率、空速等)，經由模糊邏輯模式化後，建立正向力係數模型及其資料庫，並分析在各個折合頻率(k=0.0, 0.10, 0.12, 0.15)時，正向力係數與飛行攻角的關係。本文詳細討論FDR數據之雜訊處理、氣動力數據的建模及折合頻率的分析，其結果可作為模擬飛機遭遇亂流時之飛行狀態及飛控系統的設計參考，並可幫助飛行員在遭遇亂流時能做出正確的判斷，以期提升飛航安全之目標。

Fuzzy logic modeling(FLM) is a method capable of analyzing non-linear physical problems with multi-variables, such as the problems of flying aircraft encountering to the clear air turbulence. This study adopts the FLM to analysis the data from flight data recorder(FDR) of an aircraft A300-600 which encountered a clear air turbulence during an international flight. After noise suppression process to the FDR data, the angle of attack, computed air speed, altitude, acceleration, control surface angle, etc., all show severe oscillations of the aircraft when encountering to the severe turbulence. After the FLM is employed, eight flight data(such as angle of attack and its rate of change, pitch rate, reduced frequency, elevator deflection, mach number, roll rate, computed air speed) are computed and the database of normal force coefficient is established. Under different values of the reduced frequencies (k=0.0, 0.10, 0.12, 0.15), the relationship of the aircraft normal force coefficient with the angle of attack are studied. In this study, detailed noise suppression process and the formation of aerodynamic variable databanks are presented. The results of this study, when aircraft encountering to the severe turbulence, shows the fast flying motion and its responses to the aircraft, which are useful to provide data for flight control design, to help pilots do the best control of the aircraft, and to promote the aims of the flight safety.

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