Journal of the Korean Society for Aeronautical & Space Sciences (한국항공우주학회지)

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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System Identification of a Small Unmanned Air Vehicle Using Neural Networks

신경회로망을 이용한 소형 무인항공기 시스템 식별

  • 송용규 (한국항공대학교 항공우주 및 기계공학부) ;
  • 전병호 (한국항공대학교 항공우주 및 기계공학부 대학원)
  • Published : 2007.10.31
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Abstract

In this paper system identification of a small UAV via neural networks is tried and the estimated parameters are then compared to those obtained by Fourier Transform Regression and Maximum Likelihood Estimation Techniques. With the estimated parameters a linear system is constructed and simulated to compare to the flight data. The results show that parameter identification using neural networks is comparable to the existing techniques

논문에서는 신경회로망을 이용하여 소형 무인항공기의 횡/방향 운동 파라미터를 추정하고 기존 파라미터 추정기법인 퓨리에변환을 이용한 추정기법(FTR)과 후처리 기법인 최대공산법(MLE)의 추정 결과와 비교하여 신경회로망 기법을 이용한 파라미터 추정 결과의 신뢰성과 가능성을 확인하였다. 또한 파라미터 추정 결과를 이용하여 선형시스템을 구성하고 비행체의 특성을 확인하였으며, 선형 시뮬레이션을 통하여 추정된 파라미터의 타당성을 검증하였다.

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References

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