Fuzzy logic for constant force control of end milling

The machining condition usually has significant variation resulting from the change of cutting depth and the intrinsic property of the workpiece. In order to maintain the performance of a classical proportional integral derivative control system, the tool life and machining quality, conservative feedrate, and cutting depth change are prespecified as the limitations of computer numerically controlled operators, Therefore, constant cutting force control is proposed as a useful approach for increasing the metal removal rate and the tool life. However, the model-based controller cannot handle the nonlinearity of a force control system due to cutting condition variations. Here, a fuzzy controller with learning ability was employed to improve both the system performance and the adaptability. This control approach was implemented on a retrofit old-fashioned milling machine for the end milling process. The experimental results show that this control strategy has smooth feedrate and good cutting force dynamic responses.