Aiming at the problem of robot manipulator trajectory tracking control with external disturbance and system parameter uncertainty

an improved adaptive neural network sliding mode tracking control method is proposed.Firstly

three degree of freedom（DoF）manipulator dynamics model is established.Calculated moment method and the neural slip mode control method based on improved reaching law are respectively used to control the nominal part and the non-nominal part.The proposed method combines RBF neural network and sliding mode control based on the approach law

so that the control system adaptively compensates the uncertainty of the manipulator

Lyapunov function is used to derive the weight update rate of the neural network

and a kind of adaptive exponential approach law is proposed.The sliding mode controller with improved approaching law compensates the RBF for the approximation error of the neural network and further suppresses the chattering.The simulation results of the three-joint RRR type manipulator are compared and the simulation results of sliding mode control based on exponential approach law are compared to verify the effectiveness of the control scheme.