Second Order Sliding Mode Trajectory Tracking Control of Robot Based on Neural Network
基于神经网络的机器人二阶滑模控制

This paper proposes a synergetic controls algorithm by adaptive neural network and Second order sliding mode control. Design a second order sliding mode control method with novelty and facility, and the chattering problem is avoided effectively, Neutral network is used to adaptive learn and compensate the unknown nonlinear model. The learning algorithm for the free neutral network parameters are presented by Lyapunov direct method. The global asymptotic stability is guaranteed. Finally, the control performance of the proposed controller is verified with simulation studies.