Simulation design and research of joint Angle automatic control of multi-degree of freedom manipulator based on neural network

In order to solve the problem of motion trajectory control and accuracy compensation of manipulator, a joint Angle automatic control scheme of multi-degree-of-freedom manipulator was proposed. Based on the dynamic analysis of the motion process of the connecting rod and joint of the multi-degree-of-freedom robot arm, the strategy to realize the automatic control of the connecting part and the control part of the robot arm is designed by combining gradient descent method and artificial nervous system. The Angle control model of the joint of the multi-degree-of-freedom robot arm is established to realize its automatic control function. According to the simulation results, the control strategy proposed in this paper can control the joint Angle of the robot arm well, track the motion trajectory of the robot arm well, and effectively improve the grasp accuracy of the robot arm, reaching 96%.