Robust Digital Repetitive Control with Optimized Tracking Performance Supporting Fast Tool Servo Applications

The fast tool servo (FTS) has emerged as one of the most promising manufacturing technology. The tracking performance of the FTS system determines the manufacturing quality, which is full of challenges in presence of machining load variations and external disturbances, as well as system nonlinearities and uncertainties. With consideration of the periodical trajectory tracking requirements of FTS systems, we propose a robust digital repetitive control structure to enable high-performance servos in this paper. On top the equivalent transformations of traditional repetitive controller, the inverse plant model is immerged into the low pass filter of the proposed control structure. Combining the periodical tracking performance improvement and robustness against of system uncertainties, we further formulate the design of the low pass filter as an
$\mathbf{H}\infty$
optimization problem. Real time experiments on the FTS prototype demonstrate excellent periodical tracking performance and robustness of the proposed control method.