An Iterative Learning Control design for Self-Servowriting in Hard Disk Drives using L<inf>1</inf> optimal control

Abstract

This paper presents an Iterative Learning Controller (ILC) design for Self-Servowriting (SSW) process in Hard Disk Drives (HDDs). In SSW, the position and timing information are written onto the disk surface by referring to the previously written servo information. This process is repeated until the whole disk is completely written. The main issue in this process is Radial Error Propagation (REP), which refers to the accumulation of the written-in errors as tracks are written sequentially. In this paper, an ILC scheme is designed by using the position error information in the previous track to prevent REP and improve the quality of servowriting. Analytic conditions for stability and monotonic convergence are discussed. The learning filter design is formulated as an (or induced L ) optimal control problem, which is solved by optimization programming. Simulation results show that REP is contained and a good quality of servowriting is assured.

Control design of concentric self-servo track writing systems for hard disk drives

“…Several novel control design techniques have been developed for SSTW servo systems that are based on the on the feedforward control structure [20][21][22][23][24]. All of these techniques involve a two-step design process.…”

“…In [24], the authors utilized the estimation of the head position to design the feedforward control. In [21], [22] and [23] iterative learning control design methodologies are employed to design the feedforward compensator in the lifted domain, assuming zero initial conditions at the beginning of each track servo writing stage and the existence of finite impulse-response (FIR) representations for the servo's sensitivity and complimentary sensitivity functions. We note however, that these assumptions are not strictly satisfied in real HDD applications.…”

“…This expression is subsequently used to formulate the simultaneous design of both a feedback and a feedforward controller, using a mixed H 2 /H ∞ control scheme, which ensures the containment of the error propagation and the achievement of good disturbance attenuation, and is solved via an SDP involving LMI constraints. Neither of these techniques requires the simplifying initial condition and FIR modeling assumptions used in [21] and [22]. Simulation results using the HDD benchmark problem developed in [25] show that the controllers synthesized using the proposed schemes outperform the controllers synthesized by the techniques in [21], and offer levels of performance that are comparable to the 2-dimensional H 2 control technique in [17] while having a simpler structure.…”

Model-free learning control of nonlinear discrete-time systems

“…The learning control techniques evolved during the last two decades [1], [2], [3], [4], [5], [6] offer an effective solution for many applications ranging from robotics [7], [8] to fluid power applications [9], [10], [11] to disk drive actuation [6] and magnetic levitation [5].…”

On the robust controller design for Hard Disk Drive servo systems with time delays

“…Track-seeking is also an important topic inviting considerable studies, for example, the wellknown PTOS (Proximate Time Optimal Seek) control approach discussed in [16], [17], and more recent result on the use of variable structure observer in seeking control [15]. Advanced control algorithms are not only used in servo operations for data access, but also in the process of writing servo patterns during HDD manufacturing, see for example [20], [5], [14].…”