关键词: 关键词：机械臂, 滑模控制, 改进变结构趋近律, RBF神经网络, 抖振

Abstract: Abstract： Aiming at the problems of slow convergence speed and system chattering in the application field of sliding mode control in the manipulator， an improved variable structure reaching law is designed to improve the dynamic characteristics of the manipulator. The convergence speed and chattering suppression of the system are optimized by using the grouping characteristics and the inverse hyperbolic sine function. The mathematical model of the two degree of freedom manipulator is established by using the second Lagrange equation， and the RBF neural network is used to approximate the system model for the friction and other unmeasurable interference problems in the system. The stability of the system tracking is proved by Lyapunov function method. Finally， the feasibility and stability of the improved variable structure reaching law algorithm are verified by the experimental comparison with PID， constant rate reaching law and fast power reaching law in Simulink.

Key words: Key words： manipulator, sliding mode control, improved variable structure approach law, RBF neural network, chattering