本論文旨在研製一套結合虛擬實境與萬向平台之四軸旋翼機飛控訓練虛實整合系統，該系統包含實體四軸旋翼機、內建三軸之磁角感測模組之萬向平台、由Unity 3D建構而成之飛行環境虛擬平台以及使用者圖形操控介面。實體旋翼機於萬向平台飛行時，需要透過遙控器及接收機經由RF通訊方式來控制飛行，而飛行過程中則需要雙環PID控制器來穩定飛行，控制器的部分則是由外環與內環之雙環結構組成，飛行時透過旋轉萬向平台使磁角感測模組產生角度變化，再透過WiFi協定傳輸旋翼機姿態給虛擬平台分析，進而模擬飛行，形成無線旋翼機姿態捕捉網路，達到虛實整合之目的。在虛實整合系統部分，關鍵在於如何精準地透過萬向平台上之磁角感測模組傳輸姿態給虛擬平台做模擬飛行的動作，由於傳輸的部分只有姿態角的部分，本論文提出了將飛行角度推算為飛行軌跡之旋翼機軌跡估測演算法，可以模擬真實的飛行軌跡。實驗結果發現，無線旋翼機姿態捕捉網路可以精準地捕捉旋翼機飛行姿態，於一般飛行時飛行240秒的平均角度誤差為2.36±0.33度，此研究結果驗證了虛實整合系統可以應用於飛行訓練之可行性。希冀本系統商品化後能幫助飛手更有效率的自我訓練並得到精準的飛行操控表現。

This thesis aims to develop a quadcopter flight control training cyber-physical system realized by a gimbal platform combined with virtual reality. The system consists of a physical quadcopter, a gimbal platform with three-axis magnetic angle sensing module, and a virtual platform constructed by Unity 3D to create a virtual flying environment, and a graphical user interface for controlling the quadcopter. When the physical quadcopter is flying in the gimbal platform, the control command for the quadcopter is sent via RF communication through the remote controller and the receiver on the quadcopter. A double-loop PID controller has been developed to stabilize the flight, and the controller scheme is a double-ring structure composed of an outer ring and an inner ring. During the flight, the magnetic angle sensing modules generate angle values changed through the rotating gimbal platform, and then transmit the attitudes of the quadcopter to the virtual platform through the WiFi protocol, which forms a wireless quadcopter attitude capture network to simulate the flight to achieve the integration of virtual reality with a physical platform, the so-call cyber-physical system. For the cyber-physical system, the key is how to accurately transmit the attitude to the virtual platform through the magnetic angle sensing module on the gimbal platform. Since only the attitude angles are available, this study proposes a quadcopter trajectory estimation algorithm that can convert the flight angle to the flight trajectory, which approximates the real flight trajectory. The experimental results verify the feasibility of the cyber-physical system for flight training. The wireless quadcopter attitude capture network can accurately capture the flight attitude of the quadcopter. The average angular error for 240 seconds flight is 2.36±0.33 degrees. In the future, we hope this system can be commercialized to help beginners to train how to control drones flying precisely.

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