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Sliding Mode Control of 5-link Biped Robot Using Wavelet Neural Network

Chul Ha Kim, Sung-Jin Yu, Jin Bae Park, Yoon Ho Choi

Year
2005
Citations
11

Abstract

Generally, biped walking is difficult to control because it is a nonlinear system with various uncertainties. In this paper, we design a robust control system based on sliding-mode control (SMC) of 5-link biped robot using the wavelet neural network(WNN), in order to improve the efficiency of position tracking performance of biped locomotion. In our control system, the WNN is utilized to estimate uncertain and nonlinear system parameters, where the weights of WNN are trained by adaptive laws that are induced from the Lyapunov stability theorem. Finally, the effectiveness of the proposed control system is verified by computer simulations.

Keywords

Control theory (sociology)Artificial neural networkSliding mode controlNonlinear systemLyapunov functionComputer sciencePosition (finance)Lyapunov stabilityAdaptive controlStability (learning theory)

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