The tracking/rejection of periodic disturbances in linear systems is achievable via internal model principle-based techniques, such as repetitive control. However, when the frequency of the signal to track/reject is uncertain or time-varying, the performance of these controllers decays dramatically. This article discusses the basics of Model Reference Adaptive Control with Minimal Controller Synthesis, and assesses its applicability to this problem from a comparative study of the performance of this type of controllers and a repetitive controller, both designed to regulate the speed of a DC motor subject to periodic disturbances. The study is supported by experimental results.