Novel Schemes for Repeatable Runout Compensation Using Adaptive Feedforward Cancellation

Shang-Chen Wu, Masayoshi Tomizuka

Abstract: In this paper, new methods to estimate repeatable runout (RRO) in hard disk drives are proposed. The techniques are based on adaptive feedforward cancellation (AFC). To enhance the performance, the modified filtered-X LMS (MFX-LMS) adaptive algorithm is combined with Kalman filtering. The estimated data are used in real-time control to generate the compensation signal which cancels RRO disturbances. Simulation results show the effectiveness of the proposed schemes and the resulting reduction of position errors in the track following mode.