The tool-workpiece vibration in the precision milling process plays a pivotal role in influencing the surface quality. To solve the machining problem coming with the process vibration, the active vibration control model as well as the corresponding platform are developed, and the active vibration control algorithms are applied to reduce the relative vibrations and improve the surface quality. Firstly, the milling vibration reduction and surface quality improvement are modelled based on the active control algorithms and the system dynamic characteristics. Then, applying the different algorithm control strategies, such as PID, Fuzzy PID, BP neural network and BP neural network PID control, the control effect is simulated and analyzed. Finally, the platform is experimentally set up to verify the reliability of the system, the frequency vibration control and the finish surface roughness improve efficiency of different active control methods are compared, providing optimal vibration control methods for precision milling.