Experimental Study of Adaptive- $Q$ Control for Disk Drive Track-Following Servo Problem

This paper presents the design of an adaptive-Q control algorithm for minimizing the position error signal (PES) in a hard-disk-drive track-following servo. Also, we discuss the results obtained from experiments done on a commercial disk drive using the said scheme. The adaptive- Q control algorithm approach uses the well-known result that all stabilizing controllers for a plant can be synthesized by conveniently parametrized augmentation to a nominal controller. The augmentation to a linear quadratic Gaussian (LQG) optimal control is parametrized by a stable filter Q. The Q filter is restricted to a finite-impulse response filter, which minimizes the rms value of the track following error. Experiments done with a fifth-order adaptive filter that uses PES signal as feedback show a 15% improvement in the achievable track misregistration over a model-based LQG controller. The adaptive-Q algorithm implemented via a recursive least squares numerically stable adaptive algorithm shows fast convergence rate and a consistent performance improvement over a fixed controller for various track locations. Also, the tracking performance improves with increase in the adaptive filter order.