Robot trajectory tracking control of improved neural network adaptive sliding mode control

摘要

In order to improve the trajectory tracking control performance of the robot,a modified neural network adaptive sliding mode control method is proposed on the basis of the neural network sliding mode control method.This method uses neural network as a controller,and uses the nonlinear mapping ability of neural network to approximate unknown nonlinearity.At the same time,the robust control law is added to eliminate the approximation error.Considering the influence of the hidden layer unit number and the network structure parameters on the validity of neural network mapping,reducing chattering is regarded as optimization target,and particle swarm optimization algorithm is adopted to optimize the network structure parameters.Finally,the simulation experiment is done under the environment of Matlab/Simulink,and comparative analyses with other control methods are conducted.The simulation results show that the control system designed by the proposed method has good robustness and control precision,and can reduce the chattering efficiently.