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

Sin Ho Lee; Jin Bae Park; Yoon Ho Choi

doi:10.1109/SICE.2006.315236

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

Sin Ho Lee, Jin Bae Park, Yoon Ho Choi

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 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 language	English
Title of host publication	2006 SICE-ICASE International Joint Conference
Pages	726-731
Number of pages	6
DOIs	https://doi.org/10.1109/SICE.2006.315236
Publication status	Published - 2006
Event	2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of Duration: 2006 Oct 18 → 2006 Oct 21

Publication series

Name	2006 SICE-ICASE International Joint Conference

Other

Other	2006 SICE-ICASE International Joint Conference
Country/Territory	Korea, Republic of
City	Busan
Period	06/10/18 → 06/10/21

All Science Journal Classification (ASJC) codes

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

Access to Document

10.1109/SICE.2006.315236

Cite this

@inproceedings{ea2bbca18eb043e996e6dd0a80fea094,

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

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.",

author = "Lee, {Sin Ho} and Park, {Jin Bae} and Choi, {Yoon Ho}",

year = "2006",

doi = "10.1109/SICE.2006.315236",

language = "English",

isbn = "8995003855",

series = "2006 SICE-ICASE International Joint Conference",

pages = "726--731",

booktitle = "2006 SICE-ICASE International Joint Conference",

note = "2006 SICE-ICASE International Joint Conference ; Conference date: 18-10-2006 Through 21-10-2006",

}

Lee, SH, Park, JB & Choi, YH 2006, Sliding mode control based on self-recurrent wavelet neural network for five-link biped robot. in 2006 SICE-ICASE International Joint Conference., 4108917, 2006 SICE-ICASE International Joint Conference, pp. 726-731, 2006 SICE-ICASE International Joint Conference, Busan, Korea, Republic of, 06/10/18. https://doi.org/10.1109/SICE.2006.315236

TY - GEN

T1 - Sliding mode control based on self-recurrent wavelet neural network for five-link biped robot

AU - Lee, Sin Ho

AU - Park, Jin Bae

AU - Choi, Yoon Ho

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

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M3 - Conference contribution

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SN - 9788995003855

T3 - 2006 SICE-ICASE International Joint Conference

SP - 726

EP - 731

BT - 2006 SICE-ICASE International Joint Conference

T2 - 2006 SICE-ICASE International Joint Conference

Y2 - 18 October 2006 through 21 October 2006

ER -

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

Abstract

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