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신경망 학습을 이용한 2축 ARM 헬리콥터의 중심이동 조향법

Shift Steering Control of 2-axis ARM Helicopter based on a Neural Network

  • Bae, Hyun-Soo (Department of Electrical Engineering, Yeungnam University) ;
  • Kim, Byung-Chul (Department of Robotics Engineering, Yeungnam University) ;
  • Lee, Suk-Gyu (Department of Electrical Engineering, Yeungnam University)
  • 투고 : 2015.02.23
  • 심사 : 2015.05.21
  • 발행 : 2015.07.01

초록

This paper proposes a helicopter direction adjustment system using barycenter shift. Most conventional methods for direction adjustment of uniaxial helicopters rely on the angle of inclination of the main rotor. However, the inherent burden of the bearing of the main rotor and serious abrasion of the helicopter using the above methods may results in loss of balance. To decrease abrasion and enhance the barycenter stability, the proposed method was used to shift the barycenter of the helicopter instead of the main rotor for direction adjustment. We set a biaxial ARM on a uniaxial helicopter to adjust the direction of ARM pointing as well as to realize stable direction control when the helicopter loses its balance. The method may enhance the landing safety of helicopters in emergencies. Uniaxial helicopters can be controlled under any environment by adjusting the motor parameters of the ARM which is dependent on the center of mass using neural network. The experiment results show that the helicopter can return to the starting position quickly under the external disturbance.

키워드

참고문헌

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