Stage properties and its control algorithms of grating-ruling engine are important reasons that directly influence the ruling accuracy of large grating. In order to improve the running accuracy of grating ruling engine, a 300 mm travel macro-micro stage using PZT as actuator of the micro positioning stage is developed. Mathematical model of micro-positioning stage is established, and the influence of stage′s parameters on the dynamic performance of the system is analyzed by simulation. Micro-positioning stage is closed-loop controlled by BP neural network proportion integration differentiation (PID) method. Simulation results show that the dynamic performance of micro-positioning stage which is closely related with grating quality can be improved in general trend by increasing the stiffness or damping between inside and outside stage. Positioning experiments of stage, which is used to emptily rule 35 line/mm or higher line density grating and employ dual-frequency laser interferometer as nano-positioning measurement standard, show that BP neural network PID algorithm can achieve 3σ positioning error of macro-micro stage to be no more than 5.0 nm. The studies above can provide theoretical and technical guidance for structure design and control-algorithm choice of macro-micro stage of large grating ruling engine.