Multirate Adaptive Disturbance Suppression Beyond Nyquist Frequency

Abstract

In precision motion systems, suppression of high-frequency unknown disturbances is always critical and challenging. This becomes even more difficult when the system output is only available at limited sampling rates, but the frequencies of the disturbances are beyond the Nyquist frequency of the output samplers. Under such scenarios, the un-availability of the intersample outputs precludes most of traditional disturbance attenuation techniques including, for instance, loop shaping, disturbance observer (DOB), and adaptive control. To address this problem, a new adaptive disturbance suppression algorithm is proposed in this paper. Via iterative multirate extended-state estimation and parameter adaptation, the unknown beyond-Nyquist disturbances can be correctly estimated and compensated. Moreover, a special internal model structure is introduced for signals with aliasing frequencies so that the dynamics of the beyond-Nyquist disturbances can be identified more efficiently. Performance of the proposed algorithm is evaluated by simulations on a hard disk drive (HDD) benchmark problem, where the beyond-Nyquist disturbances are effectively suppressed without a priori knowledge of the disturbance models.