Nonminimum phase adaptive inverse control for settle performance applications

Abstract

Single-track hard disk drive (HDD) seek performance is measured by settle time, t s , defined as the time from the arrival of a seek command until the measured position reaches and stays within an acceptable distance from the target track. Our previous work has shown feedforward dynamic inversion, coupled with an aggressive desired trajectory y d , is capable of achieving high performance settle times when the closed-loop dynamics are time-invariant and accurately modeled. In contrast, we describe an adaptive inversion procedure in this paper which removes the requirement for accurate initial models and tracks the position-variant dynamics present in our Servo Track Writer (STW) experimental apparatus. The proposed indirect adaptive inversion algorithm relies on a recursive least squares (RLS) estimate of the closed-loop dynamics. Pre-filtering of the RLS input signals, covariance resetting, and relative NMP system partitioning are necessary additions to the baseline adaptive algorithm in order to achieve fast settle times. Compared to the nonadaptive solution with accurate system identification, we show the adaptive algorithm achieves a 22% reduction in average settle time and a 53% reduction in settle time standard deviation.