Sliding Mode Control Based on Self-Recurrent Wavelet Neural Network for Five-link Biped Robot

Author

Sin Ho Lee ; Jin Bae Park ; Yoon Ho Choi

Author_Institution

Dept. of Electr. & Electron. Eng., Yonsei Univ., Seoul

fYear

2006

Firstpage

726

Lastpage

731

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

Keywords

Lyapunov methods; error analysis; error compensation; intelligent control; legged locomotion; nonlinear control systems; recurrent neural nets; stability; variable structure systems; wavelet transforms; Lyapunov stability theorem; approximation error; error compensation controller; five-link biped robot system; intelligent control; model uncertainty; nonlinear system parameters; self-recurrent wavelet neural network; sliding mode control; stable walking control; Control system synthesis; Error compensation; Intelligent control; Intelligent robots; Legged locomotion; Neural networks; Nonlinear control systems; Robot control; Sliding mode control; Uncertainty; Biped Robot; Self-Recurrent Wavelet Neural Network; Sliding Mode Control; Wavelet Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE-ICASE, 2006. International Joint Conference

Conference_Location

Busan

Print_ISBN

89-950038-4-7

Electronic_ISBN

89-950038-5-5

Type

conf

DOI

10.1109/SICE.2006.315236

Filename

4108917