本論文主要為戶外自主飛行的四旋翼無人飛行載具的設計與控制。首先，建立感測器系統數學模式，將其線性化並以轉換成線性數位系統，以利於設計擴增式卡爾曼濾波器。並驗證全球定位系統輔助慣性導航系統的擴增式卡爾曼濾波器(EKF)的定位確實比僅有GPS或INS的精度更高且可靠。接著，以模糊滑動模式分散控制法則應用於姿態 (即滾轉、俯仰、偏航)及高度。此控制法則並不需要QUAV的動態數學模式，僅需輸入及輸出數據，以建立有效的規則庫，經由每個子系統的三個比例因子及滑動面系數的調整。接著，即時規劃軌跡以提供控制器進行所設定的任務。並經由人機介面程式，讓使用者能快速且方便的了解飛行載具的狀態，並且以無線模組操控嵌入式系統的人機介面程式，完成使用者設定的動作。在本論文中四旋翼從地面之起始點起飛後，追蹤所規劃的軌跡，結束軌跡追蹤後，即自動降落至指定的結束點，完成所設定的任務。最後，並比較使用EKF進行軌跡估測之軌跡飛行追蹤控制與僅使用GPS及INS訊號之軌跡飛行追蹤控制的優劣，以驗證所建議的方法之有效性、務實性及強健性。

Due to advantages and disadvantages of inertia navigation system (INS) and global positioning system (GPS), it is not suitable for the only use of GPS or INS for the measured velocity and position of outdoor QUAV. Furthermore, the computation of the rotation described by Euler angle is inefficient; its description sometimes possesses the singularity problem. Hence, it is not suitable for the embedded single board computer to calculate the corresponding signals using the Euler angle based rotation description. In this thesis, the nonlinear mathematical model of sensors including GPS and INS is first established. Its linearized model around the GPS signal is constructed for the discrete version of extended Kalman filter (EKF). The estimated position and velocity from EKF are employed to correct the position and velocity of INS such that the controller design is more effective. The compared performances between GPS and INS, and GPS-aided INS confirm the effectiveness of the estimated signal through GPS-aided INS. Subsequently, the EKCF-based fuzzy decentralized path tracking control (FDPTC) is applied for the path tracking of an outdoor QUAV. The proposed control does not need the mathematical dynamic model of QUAV, it only needs its input/output data to construct the fuzzy rule table. After that, three factors and the coefficients of sliding surface for each subsystem are tuned to obtain the satisfactory control performance. Finally, the compared experiments of circular path confirm the effectiveness and robustness of the proposed method.

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