Abstract: Aiming at the position control accuracy of electrohydraulic proportional system of rock drilling manipulator, a method of position control of the electro-hydraulic proportion system based on radical basis function(RBF)neural network tuning PID was proposed.Firstly, a simplified model of the electro-hydraulic proportion system for a valve-controlled non-symmetric hydraulic cylinder was built in AMESim, and parameters for each module were set. Then, a closed-loop control model of the system was constructed using MATLAB/Simulink. The RBF network model was continuously updated and the PID parameters were corrected, position control of the electro-hydraulic proportion system based on RBF neural network tuning PID was achieved. The built model of the electro-hydraulic proportion system in AMESim and the controller constructed in Simulink were combined for joint simulation. Finally, based on the mechanical arm experimental platform of a rock drilling rig, an electro-hydraulic proportional system position control experiment was conducted. The simulation results indicate that, under external disturbances, the RBF neural network tuning PID control system can control the piston rod to return to the target position within 0.3 s, with an average response time of 1.5 s, and the position accuracy error does not exceed 5mm. The experimental results show that compared with conventional PID control method, the RBF neural network tuning PID control piston rod position accuracy error is reduced by 75%, and the position accuracy error is within the 10mm range required by engineering practice. Therefore, the RBF neural network tuning PID algorithm can effectively improve the position control accuracy of the electro-hydraulic proportional system, and meet the control requirements for the position accuracy of the electro-hydraulic proportional system in the actual work of rock drilling robotic arms.
Key words: rock drilling robotic arm; radical basis function(RBF) neural network tuning PID; position control accuracy of electro-hydraulic proportional system; joint simulation; MATLAB/Simulink; AMESim