무인항공기는 2000년대 중반부터 탐색, 조사, 매핑, 수색 및 구조 등의 3D 작업에 적극적으로 사용되기 시작했다. 이러한 세계적인 추세에 따라, 무인항공기의 정밀한 제어는 엄청난 응용 산업들의 측면에 있어서 혁명을 가져올 것이다. 논문의 첫 번째 파트에서는 시스템식별 기법을 사용하여 간략화 된 무인항공기의 모델을 이전의 이산시간 선형모델과 비교분석 한다. 두 번째 파트에서는 동적 모델의 세 가지 변수가 배치추정기법과 RLS추정기법을 사용하여 추정된다. 쿼드로터 무인항공기 호버링 기동 시의 각가속도 데이터가 항상 수렴한다고 분석되었다. 또한 실험 및 MATLAB시뮬레이션의 쿼드로터 무인항공기 비행 데이터에 의하면, 배치추정기법이 RLS추정기법보다 더 정확하다고 판명되었다.
무인항공기는 2000년대 중반부터 탐색, 조사, 매핑, 수색 및 구조 등의 3D 작업에 적극적으로 사용되기 시작했다. 이러한 세계적인 추세에 따라, 무인항공기의 정밀한 제어는 엄청난 응용 산업들의 측면에 있어서 혁명을 가져올 것이다. 논문의 첫 번째 파트에서는 시스템식별 기법을 사용하여 간략화 된 무인항공기의 모델을 이전의 이산시간 선형모델과 비교분석 한다. 두 번째 파트에서는 동적 모델의 세 가지 변수가 배치추정기법과 RLS추정기법을 사용하여 추정된다. 쿼드로터 무인항공기 호버링 기동 시의 각가속도 데이터가 항상 수렴한다고 분석되었다. 또한 실험 및 MATLAB 시뮬레이션의 쿼드로터 무인항공기 비행 데이터에 의하면, 배치추정기법이 RLS추정기법보다 더 정확하다고 판명되었다.
UAVs began to be actively applied to so-called 3D jobs, including the autonomous exploration, investigation, mapping, search and rescue, etc. since the mid-2000s. With this global trend, having a precise controllability of the UAV will certainly revolutionize the life of the modern human in the aspe...
UAVs began to be actively applied to so-called 3D jobs, including the autonomous exploration, investigation, mapping, search and rescue, etc. since the mid-2000s. With this global trend, having a precise controllability of the UAV will certainly revolutionize the life of the modern human in the aspect of tremendous applications of the UAV. In the first part, a simplified dynamic model of the UAV identified using system identification techniques is compared with the previously built time-discrete linear model. In the second part, the three parameters of the dynamic model are estimated using the batch and RLS methods. Angular acceleration data of the quadrotor UAV at the hovering maneuver are analyzed and shown to be converging at all time. Also, according to the quadrotor flight data from both experiments and MATLAB simulations, the batch estimation method turns out to be more accurate than the RLS estimation method based on the comparison of final parameter values.
UAVs began to be actively applied to so-called 3D jobs, including the autonomous exploration, investigation, mapping, search and rescue, etc. since the mid-2000s. With this global trend, having a precise controllability of the UAV will certainly revolutionize the life of the modern human in the aspect of tremendous applications of the UAV. In the first part, a simplified dynamic model of the UAV identified using system identification techniques is compared with the previously built time-discrete linear model. In the second part, the three parameters of the dynamic model are estimated using the batch and RLS methods. Angular acceleration data of the quadrotor UAV at the hovering maneuver are analyzed and shown to be converging at all time. Also, according to the quadrotor flight data from both experiments and MATLAB simulations, the batch estimation method turns out to be more accurate than the RLS estimation method based on the comparison of final parameter values.
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가설 설정
3. The z data is set to be sinusoidal with an amplitude of 2, the frequency of 2∙𝜋∙0125 rad/sec, and phase of -𝜋/2 rad. The visual simulation is shown in [Fig.
제안 방법
Angular accelerations of the roll, pitch, and yaw data required for the hovering maneuver are analyzed and shown to be convergent. Also, conditional status using SNR, the robustness of system identification using noise PDF, and real-time parameter estimation using the RLS method are performed for the additional parameter estimations.
In this paper, we showed system identification procedures for the quadrotor UAV using batch and RLS estimation methods. The commonly known quadrotor UAV model is adopted and simplified since we only focus on the hovering operation.
이론/모형
The UAV flight is also simulated using the MATLAB/Simulink toolbox developed by [13]. To obtain the desired UAV data, the Simulink model is modified as shown in [Fig.
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