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Adaptive Neural Network Controller Design for a Blended-Wing UAV with Complex Damage

전익형 무인항공기의 복합손상을 고려한 적응형 신경망 제어기 설계 연구

  • Received : 2017.03.07
  • Accepted : 2018.01.18
  • Published : 2018.02.01

Abstract

This paper presents a neural network controller design for complex damage to a blended wing Unmanned Aerial Vehicle(UAV): partial loss of main wing and vertical tail. Longitudinal/lateral axis instability and the change of flight dynamics is investigated via numerical simulation. Based on this, neural network based adaptive controller combined with two types of feedback linearization are designed in order to compensate for the complex damage. Performance of two kinds of dynamic inversion controllers is analyzed against complex damage. According to the structure of the dynamic inversion controller, the performance difference is confirmed in normal situation and under damaged situation. Numerical simulation verifies that the instability from the complex damage of the UAV can be stabilized via the proposed adaptive controller.

본 논문에서는 전익형 무인항공기의 복합손상을 고려한 신경망 적응제어기 연구 결과를 기술하였다. 여기서 복합손상이란 무인항공기의 주익과 수직미익의 동시 손상을 의미한다. 시뮬레이션을 통하여 종/횡축 불안정성과 비행역학 특성을 확인하였다. 이를 바탕으로 두 가지 형태의 역변환 제어기 기반 적응형 신경망 제어기를 설계하였다. 또한 두 가지 역변환 제어기 구조에 따라 무인항공기의 복합 손상 시 제어 성능 분석을 수행하였다. 역변환 제어기 구조에 따라서 일반 상황과 손상 상황에서 성능 차이를 확인하였다. 최종적으로 무인기에 발생된 복합손상으로 인한 항공기의 불안정성은 적용된 제어기를 통하여 극복할 수 있음을 확인하였다.

Keywords

References

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