Adaptive Repetitive Control Design With Online Secondary Path Modeling and Application to Bit-Patterned Media Recording

This paper presents an adaptive repetitive controller for active tracking (rejecting) of unknown periodic trajectories (disturbances). The proposed control law is based on a modified filtered-x least mean squares (MFX-LMS) algorithm with a novel variable step size that improves the convergence rate and fades the steady state excess error in a stochastic environment. A novel secondary path modeling scheme is also proposed to adaptively compensate for the dynamic mismatches between the internal model of the MFX-LMS and the real dynamic system in an online fashion. We further discuss the application of this adaptive controller in servo mechanisms for hard disk drives (HDDs) that use bit patterned media recording in which full spectrum tracking of a periodic trajectory is crucial. Finally, comprehensive numerical simulations and experimental implementations are presented for an HDD servo system that is subjected to periodic disturbances known as repeatable run-out.