Fuzzy Neural Sliding Mode Control for Multi-link Robots

A fuzzy neural sliding mode controller is proposed for trajectory tracking control of multi-link robots with uncertain exter-nal 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 fuzzy neural net-work 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 fuzzy neural network are calculated by Lyapnov stability method.Chattering of the sliding mode control is reduced by the fuzzy neural network's learning.Simulation results verify the validity of the control scheme.