Development of an adaptive smith controller for cutting torque control in a milling process

Optimizing the feedrate to regulate cutting force or torque not only enhances machining efficiency but also protects machines against wear and tear. Generally, most of the studies simplified the dynamic model of machining process as a first or second-order transfer functions and the effects of the interpolator and communication dead-time delay of control signals were not included. Neglecting these factors could lead to system instability or oscillations when machining conditions change. In this paper, a comprehensive machining process model that integrates interpolation, servo drive system, cutting model, and communication dead-time delay is developed. To address varying dynamic behaviors under different machining conditions, such as different cutting depths, an adaptive Smith controller was developed. The proposed controller integrates an online parameter estimator and a Smith predictor. The estimated parameter reflected the cutting process dynamics, including the effects of tool wear and system uncertainties. The Smith predictor architecture was used to solve the communication dead-time delay problem, which was neglected in previous studies. The performance of the adaptive Smith controller was experimentally validated on a workpiece with three different cutting depths. Compared to a conventional proportional-integral controller or a Smith predictor, the adaptive Smith controller could adjust the feedrate to maintain a constant torque with less oscillations. The proposed control architecture reduced machining time by 10.5 % compared to an uncontrolled case.