Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Adaptive Neural Dynamic Surface Control via $H_{\infty}$ Approach for Nonlinear Flight System

비선형 비행 시스템을 위한 $H_{\infty}$ 접근법 기반 적응 신경망 동적 표면 제어

  • Yoo, Sung-Jin (Dept. of Electrical & Electronic Engineering, Yonsei University) ;
  • Choi, Yoon-Ho (School of Electronic Engineering, Kyonggi University) ;
  • Park, Jin-Bae (Dept. of Electrical & Electronic Engineering, Yonsei University)
  • 유성진 (연세대학교 전기전자공학과) ;
  • 최윤호 (경기대학교 전자공학부) ;
  • 박진배 (연세대학교 전기전자공학과)
  • Published : 2007.07.18
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Abstract

This paper presents an adaptive neural dynamic surface control (DSC) approach with $H_{\infty}$ tracking performance for a full dynamics of a nonlinear flight system. It is assumed in this paper that model uncertainties such as structured and unstrutured uncertainties and external disturbances influence the nonlinear aircraft model. In our control system, self recurrent wavelet neural networks (SRWNNs) are used to compensate model uncertainties of the nonlinear flight system, and an adaptive DSC technique is extended for disturbance attenuation of the nonlinear flight system. From Lyapunov stability theorem, it is shown that $H_{\infty}$ performance from external disturbances can be obtained. Finally, we perform the simulation for the nonlinear six-degree-of-freedom F-16 aircraft model to confirm the effectiveness of the proposed control system.

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