Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Nonlinear Adaptive Flight Control Using Neural Networks and Backstepping

신경회로망 및 Backstepping 기법을 이용한 비선형 적응 비행제어

  • 이태영 (서울대학교 대학원 기계항공공학부, 정밀기계설계공동 연구소) ;
  • 김유단 (서울대학교 기계항공공학부, 정밀기계설계공동연구소)
  • Published : 2000.12.01
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Abstract

A nonlinear adaptive flight control system is proposed using a backstepping controller with neural network controller. The backstepping controller is used to stabilize all state variables simultaneously without the two-timescale assumption that separates the fast dynamics, involving the angular rates of the aircraft, from the slow dynamics which includes angle of attack, sideslip angle, and bank angle. It is assumed that the aerodynamic coefficients include uncertainty, and an adaptive controller based on neural networks is used to compensate for the effect of the aerodynamic modeling error. It is shown by the Lyapunov stability theorem that the tracking errors and the weights of neural networks exponentially converge to a compact set. Finally, nonlinear six-degree-of-freedom simulation results for an F-16 aircraft model are presented to demonstrate the effectiveness of the proposed control law.

Keywords

References

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