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