Research on Manipulator Tracking Control Algorithm Based on RBF Neural Network

Abstract

Abstract According to the characteristics of strong coupling and highly nonlinear of manipulator, a trajectory tracking control method based on neural network is proposed. This paper makes full use of the neural network’s self-learning characteristics, parallel processing ability, nonlinear mapping ability, fault tolerance and so on, and combines it with other control methods to design a controller which can improve the tracking performance of manipulator. The simulation results show that the control method can improve the effectiveness and accuracy of robot arm trajectory tracking.