Robust feedrate control for high-efficiency machining using quantitative feedback theory

ABSTRACT This study used quantitative feedback theory (QFT) to design a robust controller suitable for various cutting conditions. First, servo dynamics and milling process models were identified. The nominal plant was defined for milling process conditions of 20-mm cutting depth, 500-rpm spindle speed, and 1-mm cutting width, and the workpiece material was aluminum. Different milling conditions can result in different milling process models, which are regarded as perturbed plants. The differences between nominal and perturbed plants were treated as system uncertainties and were applied in designing the QFT controller to ensure that robust performance could be guaranteed under various milling conditions. Instead of using force measured by a dynamometer, the robust controller adjusted feedrate according to the spindle current, which was easy to measure online. The experimental results illustrated that the cutting force could be maintained at a constant level at different cutting depths, and machining time could be reduced by over 20% compared with uncontrolled cases. The proposed controller’s robustness was validated by testing different tools, workpiece materials, and cutting parameters in different experiments.