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Adaptive Backstepping Control Using Self Recurrent Wavelet Neural Network for Stable Walking of the Biped Robots

이족 로봇의 안정한 걸음새를 위한 자기 회귀 웨이블릿 신경 회로망을 이용한 적응 백스테핑 제어

  • 유성진 (연세대학교 전기전자공학과) ;
  • 박진배 (연세대학교 전기전자공학과)
  • Published : 2006.03.01

Abstract

This paper presents the robust control method using a self recurrent wavelet neural network (SRWNN) via adaptive backstepping design technique for stable walking of biped robots with unknown model uncertainties. The SRWNN, which has the properties such as fast convergence and simple structure, is used as the uncertainty observer of the biped robots. The adaptation laws for weights of the SRWNN and reconstruction error compensator are induced from the Lyapunov stability theorem, which are used for on-line controlling biped robots. Computer simulations of a five-link biped robot with unknown model uncertainties verify the validity of the proposed control system.

Keywords

References

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