Aiming at the problem that the oil film thickness changes when the hydrostatic bearing external load changes, and the bearing capacity and damping are reduced, an active control method for the oil film thickness was designed. The proportional pressure valve was used as a pressure compensation element, and the control circuit was fed back with oil supply pressure, table displacement, oil chamber flow and working pressure. The supply pressure difference required to maintain the steadystate compensation for the film thickness difference was calculated as the PID control parameter value of the pressure valve, then combining the neural networktrained parameters, the best PID controller parameters were found, displacement compensation control was performed to achieve steady state equal film thickness control. The experimental results show that the neural network PID controller has faster transient oscillation convergence than other neural network controllers, and quickly reaches the target of equal film thickness.