Sliding mode control based on self-recurrent wavelet neural network for five-link biped robot

Sin Ho Lee, Jin Bae Park, Yoon Ho Choi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

In this paper, we propose the intelligent control of biped robot system with unknown model uncertainty. In our proposed control system, we employ the sliding mode control (SMC) for stable walking control of biped robot and the error compensation controller for the approximation error of self-recurrent wavelet neural network (SRWNN) which is used to estimate unknown model uncertainty of the biped robot system and nonlinear system parameters. Also, the adaptive laws for all weights of SRWNN are induced from the Lyapunov stability theorem, which are used to guarantee the stability of control system. Finally, we carry out computer simulations based on the 5-link biped robot model for the effectiveness of the proposed control system.

Original languageEnglish
Title of host publication2006 SICE-ICASE International Joint Conference
Pages726-731
Number of pages6
DOIs
Publication statusPublished - 2006 Dec 1
Event2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of
Duration: 2006 Oct 182006 Oct 21

Other

Other2006 SICE-ICASE International Joint Conference
CountryKorea, Republic of
CityBusan
Period06/10/1806/10/21

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All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Lee, S. H., Park, J. B., & Choi, Y. H. (2006). Sliding mode control based on self-recurrent wavelet neural network for five-link biped robot. In 2006 SICE-ICASE International Joint Conference (pp. 726-731). [4108917] https://doi.org/10.1109/SICE.2006.315236