Repetitive learning output-feedback control with unknown high-frequency gain sign

An adaptive repetitive learning control method is proposed for parametric output-feedback systems doing the same work repetitively. Nussbaum-gain technique is utilized to counteract the lack of a priori knowledge of sign of the high-frequency gain. A differential-difference parameter updating law which combines the time-domain and iteration-domain adaptation is introduced to facilitate the repetitive control. It is shown that the output of the system under control could converge to the desired trajectory asymptotically.