关键词: 全局快速终端滑模控制, 神经网络, 建模误差, 抖振, 滑模面

Abstract: A neural sliding mode controller is given for trajectory tracking control of multi-link robots with uncertain external disturbances and system model errors.This approach uses a global fast terminal sliding mode manifold，which guarantees that the controlled system can reach the sliding mode manifold and equilibrium point in finite time from any initial state.A Radial Basis Function（RBF） neural network is applied to learn the upper bound of system model errors and external disturbances，and enforce the sliding mode motion.The control law and the cost function of the RBF neural network is calculated by Lyapnov stability method.Chattering of the sliding mode control is reduced，even eliminated without sacrificing its robustness by the RBF neural network’s learning.Simulation results verify the validity of the control scheme.

Key words: global fast terminal sliding mode control, neural network, model error, chattering, sliding mode manifold