Stability of High-frequency Rotary Valve Spool Based on Radial Basis Function Neural Network Algorithm
In order to address the problem of high-frequency output accuracy degradation caused by hydrodynamic torque change when hydraulic motor drives high-frequency rotary valves,a rotary valve spool speed control strategy based on radial basis function neural network algorithm is proposed by using the hydraulic motor as the driving source.Firstly,the mathematical model of the high-frequency rotary valve spool speed control system is constructed.Secondly,the simulation model is constructed according to the mathematical model on the platform of MATLAB/Simulink,and the control characteristics of the spool speed under the action of different algorithms are simulated and analyzed.Finally,the experimental bench of the speed control system of high-frequency rotary valve is set up,and the speed control characteristics of the spool speed under the action of different algorithms are experimentally researched and theoretically verified.The results show that the radial basis function neural network-based high-frequency rotary spool valve speed control strategy,compared with the conventional PID control method,the minimum adjustment time required for the step response of the speed control system is 0.16 s,and the overshooting amount is small;the mean value of the triangular wave and sinusoidal wave speed tracking error decreases by a maximum of 46.51％and 53.69％;and the mean values of the steady state errors of the speed control system are reduced by 34.92％and 38.26％under 6 MPa and 10 MPa respectively.The radial basis function neural network algorithm effectively improves high-frequency rotary valve's spool speed control accuracy.
radial basis function neural network algorithmhigh-frequency rotary valvehydraulic motorspeed control
万方数据
维普
