Predictive Function Control for Milling Process

Zhihuan Zhang, Chao Hu


The adaptive constant control for the cutting process is an effective way to improve the productivity of the Computer Numerical Control (CNC) milling machine. This control is achieved through adjusting the feed rate online, and many scholars has been concentrated in the field. However, in of the existing adaptive constant control algorithms, the controller parameters are tuned only depends on the dynamic behavior of the controlled system, without giving effect to control the input and system output prospects. Therefore, milling force mutated because of the mutation of the depth or width of cut usually resulting in the overshooting of control system or overflow of control input. In this paper, we present a new solution to the problem, in which a mathematical model of milling process is established based on the characteristics of the CNC milling process. Then the predictive functional control law is introduced on the milling process and the controller parameters can be tuned online. The Simulation results show that the proposed method has the advantages of strong robustness to different interferences, good practicability for the milling process, and good real-time control responsibility.





milling process; predictive function control; nonlinear system control

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