Trajectory Tracking Control of Robot Arm Based on Recurrent Neural Network
Aiming at the problem that the robot arm can not follow the change of the motion matrix in time in the process of continuous change,which leads to low control accuracy,a trajectory tracking control method of robot robot arm based on recurrent neural network is proposed.Firstly,a mathematical model of robot arm dynamics was established,and a trajectory tracking controller for the robot arm was designed.Then,a linear parameter model for trajectory tracking was established based on recurrent neural networks,which can adjust the motion trajectory of the robot arm in real-time.By solving static feedback control values,online adjustment of controller parameters was achieved to adapt to changes in the external environment,effectively improving the accuracy of robot arm motion control.The experimental results show that the proposed method has better robustness and higher control accuracy,and the average trajectory tracking error is only 0.008 m.The research results can provide theoretical support for high-precision control of the robot arm.
recurrent neural networkrobotparameter modelmulti joint armrobust control
NETL
NSTL
万方数据
