Abstract
The goal of this work is to concurrently counterbalance the dynamic cutting force and regulate the spindle position deviation under various milling conditions by integrating active magnetic bearing (AMB) technique, fuzzy logic algorithm, and an adaptive self-tuning feedback loop. The experimental data, either for idle or cutting, are utilized to establish the database of milling dynamics so that the system parameters can be on-line estimated by employing the proposed fuzzy logic algorithm as the cutting mission is engaged. Based on the estimated milling system model and preset operation conditions, i.e., spindle speed, cut depth, and feed rate, the current cutting force can be numerically estimated. Once the current cutting force can be real time estimated, the corresponding compensation force can be exerted by the equipped AMB to counterbalance the cutting force, in addition to the spindle position regulation by feedback of spindle position. At the end, the experimental simulations on realistic milling are presented to verify the efficacy of the fuzzy controller for spindle position regulation and the capability of the dynamic cutting force counterbalance.
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Tsai, NC., Shih, LW. & Lee, RM. Spindle vibration suppression for advanced milling process by using self-tuning feedback control. Int J Adv Manuf Technol 48, 1–10 (2010). https://doi.org/10.1007/s00170-009-2262-x
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DOI: https://doi.org/10.1007/s00170-009-2262-x