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In pneumatic control valves, the development of control algorithms for intelligent electrical valve positioners usually needs to be based on the pneumatic membrane actuator model; In this study, the traditional Karnopp friction model applied to pneumatic membrane actuators is optimized, and the dynamic and static friction judgment condition DV (critical speed) is modified, and the modified model solves the problem of how DV is selected. The parameter identification method of the traditional pneumatic membrane actuator model is improved, and the multiple linear regression and least squares method are applied to estimate the mass of moving parts, spring rate coefficient, preload force, Coulomb friction and viscous friction coefficient in the pneumatic membrane actuator, and the parameter selection result is determined by the actual air chamber pressure and the standard error of the estimated air chamber pressure, the correlation coefficient and the p-value corresponding to each parameter in the parameter vector. The model is integrated into the dynamic model of pneumatic thin film actuator, and the effectiveness of the parameter identification method is verified by simulation and experiment. Simulation and experimental comparison are carried out under the stimulus of step signals and random signals of different amplitudes of open-loop, the results show that the integrated friction model can accurately simulate the dynamic process of pneumatic membrane actuator, the model and parameter identification method are also applicable to other mechanical equipment.