The study of trajectory automatic control based on RBF neural network PID control

For the hot and difficult issues of trajectory automatic control based on single bucket hydraulic excavator, this paper introduce the control method of combining RBF neural network with traditional PID. By setting up the mathematical model of machine-electricity-hydraulic control system, using the MATLAB-Simulink simulation analysts to get the conclusion that based on RBF neural network PID control is superior to the conventional PID control. This control method can make the system have the adaptability, automatically adjust the control parameters, adapt to the changes in the charged process, improve the control performance and reliability and provide a theory basis to further realize the excavator trajectory intelligent control.