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

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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Real-time System Identification of Aircraft in Upset Condition Using Adaptive-order Zonotopic Kalman Filter

적응 차수 조노토픽 칼만 필터를 활용한 비정상 비행상태 항공기의 실시간 시스템 식별

  • Gim, Seongmin (Graduate School of Mechanical and Aerospace Engineering, Gyeongsang National University) ;
  • Harno, Hendra G. (Graduate School of Mechanical and Aerospace Engineering, Gyeongsang National University) ;
  • Saderla, Subrahmanyam (Indian Institute of Technology Kanpur) ;
  • Kim, Yoonsoo (Graduate School of Mechanical and Aerospace Engineering, Gyeongsang National University)
  • Received : 2021.10.31
  • Accepted : 2021.01.17
  • Published : 2022.02.01
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Abstract

It is essential to prevent LoC(Loss-of-Control) or upset situations caused by stall, icing or sensor malfunction in aircraft, because it may lead to the crash of the aircraft. With this regard, it is crucial to correctly identify the dynamic characteristics of aircraft in such upset conditions. In this paper, we present a SID(System IDentification) method utilizing the moving-window based least-square and the adaptive-order ZKF(Zonotopic Kalman Filter), which is more effective than the existing Kalman-filter based SID for the aircraft in upset condition at a high angle of attack with temporary sensor malfunction. The proposed method is then tested on real flight data and compared with the existing one.

실속, 결빙, 센서 이상 등으로 인해 일어나는 제어불능 또는 비정상 비행 상황은 항공기의 추락으로 이어지기 때문에 필수적으로 대비해야 한다. 이와 관련해 비정상 비행 상황에서 항공기의 동적 특성을 정확하게 파악하는 것은 매우 중요하다. 본 논문에서는 일시적인 센서 이상이 발생한 고받음각의 비정상 비행상태 항공기에 대해서 기존의 칼만 필터 기반의 시스템 식별법 대비 보다 효과적인 적응 차수 조노토픽 칼만 필터와 이동창-최소자승법을 활용한 시스템 식별법을 제시하였다. 제안한 방법을 실제 비행 데이터에 적용하고 그 성능을 기존 연구 결과와 비교하였다.

Keywords

Acknowledgement

본 연구는 2017 과학기술정보통신부의 재원으로 한국연구재단의 지원(NRF-2017R1A5A1015311)을 받아 수행되었습니다.

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