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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Self-Recurrent Wavelet Neural Network Based Adaptive Backstepping Control for Steering Control of an Autonomous Underwater Vehicle

수중 자율 운동체의 방향 제어를 위한 자기회귀 웨이블릿 신경회로망 기반 적응 백스테핑 제어

  • 서경철 (연세대학교 전기전자공학과) ;
  • 유성진 (연세대학교 전기전자공학과) ;
  • 박진배 (연세대학교 전기전자공학과) ;
  • 최윤호 (경기대학교 전자공학부)
  • Published : 2007.05.01
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Abstract

This paper proposes a self-recurrent wavelet neural network(SRWNN) based adaptive backstepping control technique for the robust steering control of autonomous underwater vehicles(AUVs) with unknown model uncertainties and external disturbance. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the steering model of AUV. The adaptation laws for the weights of SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for the on-line control of AUV. Finally, simulation results for steering control of an AUV with unknown model uncertainties and external disturbance are included to illustrate the effectiveness of the proposed method.

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References

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