Robust repetitive control by Sampled-data H∞ filters

In this article, we study digital repetitive control to track continuous-time periodic references. Sampled-data control gives a very natural platform for studying digital repetitive control, and in particular, sampled-data H^∞ filtering is particularly suitable for this. The link is provided by introducing internal model control. This leads to a close connection between robust repetitive control and sampled-data H^∞ noise reduction, or regularization. With this connection, it becomes possible to employ a variety of filtering techniques, such as multirate filtering, for robust digital repetitive control. Design examples show the effectiveness of our method in robustness in digital repetitive control.