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A new method for modeling the thermal response of semiconductor devices such as light-emitting diodes (LEDs) from temperature measurements is presented. The method uses a realization-theoretic approach to identification combined with convex optimization methods. Linear matrix inequalities are constructed to guarantee that the identified discrete-time model has strictly real eigenvalues between 0 and 1, so that, when converted to continuous time, the model will have strictly real time constants. Additional optional time-domain constraints are developed to guarantee a predetermined steady-state value, guarantee no undershoot or overshoot in the transient response, and/or guarantee a positive time-constant spectrum. The method is applied to the thermal response of a high-power LED. Temperature measurements of the semiconductor device are used to model the time constants of the thermal response and characterize the relative contribution of each time constant to temperature increase. Experiments indicate how the proposed method can be used to detect thermal defects. It is shown that models with five time constants can model the thermal effects of the LEDs used with high accuracy. The proposed method is applicable to larger order systems with multiple simultaneous temperature measurements.

An input shaping algorithm based on convex optimization techniques is presented for the design of reference and feedforward signals in a closed-loop discrete-time linear time-invariant system. The proposed algorithm allows closed-loop signals to be subjected to linear constraints on amplitude and rate of change. As an illustrative example the seeking process in a hard disk drive is investigated. The closed-loop system response to both shaped and non-shaped inputs are compared. The computational scheme was experimentally tested on a modified hard disk drive.

A dynamic model of the resistance heater element in a thermal flying height control (TFC) slider of a hard disk drive is identified and used for dynamic flying height control. Experimental data obtained on a spin stand and a generalized realization algorithm are used for identification of a discrete-time dynamic model of the thermal actuator. The flying height change is measured in two different ways: using servo burst information written onto the disk surface and using information written in the data sectors only. The resistance change of the thermal actuator based on the input power level is measured. Based on the identified discrete-time model of the heater and using convex optimization techniques, a computational scheme is proposed to obtain optimized feedforward input profiles to the heater element that minimize repeatable flying height variations and enable low flying heights.

In recent years, track densities of magnetic hard disks have continued to grow. A promising approach to continuing the trend to ultrahigh density is using bit-patterned media (BPM). However, the implementation of BPM in hard disk drives (HDDs) to achieve high recording density is challenging and requires various new techniques, such as new servo pattern designs and position error signal (PES) decoding schemes. In applying BPM in HDDs, it is important to select a servo pattern providing sufficient PES quality for head positioning. In this paper, we discuss evaluation of PES quality and servo pattern performance from a closed-loop (servo) point of view in order to evaluate the quality of several servo patterns. We consider three servo patterns (the amplitude pattern, chevron pattern, and differential frequency pattern) as case studies. We developed a PES simulation tool to provide a realistic HDD track-following simulation. Because of PES nonlinearity in the amplitude servo pattern, we considered time-based servo patterns as alternatives. For time-based servo patterns, we found that readback signal sampling and transition jitter greatly affect PES quality. Therefore, we conclude that the differential frequency servo pattern is superior to other patterns, since it is less sensitive to transition jitter and readback signal sampling.

In this paper, we consider the iterative learning control (ILC) framework to design a reference signal that directly cancels periodic disturbances in a feedback measurement. Cancellation of periodic disturbances is useful in reducing undesirable repeatable tracking errors in applications such as the two-stage servo track writing process for disk drives. A general problem description is given for a linear discrete-time periodic system and convergence results for the learning system are derived. A learning filter is designed with the use of a finite-impulse response model approximation for the inverse of the closed-loop sensitivity such that convergence is achieved in learning a reference signal that provides cancellation with periodic perturbations affecting the system measurement. The ILC algorithm is applied to a disk drive system where experimental results demonstrate the effectiveness of the method in reducing periodic measurement disturbances.

In a hard disk drive with a dual-stage actuator the standard rotary actuation of the voice coil motor (VCM) is combined with an additional micro- or milli-actuation to accomplish high-bandwidth and highly accurate track following. For extremely high density recording, the servo control algorithm designed for a specific dual-stage actuator needs to maintain high performance track following in lieu of external disturbances and uncertainties in the dynamic response induced by product manufacturing tolerances. Essential in the robust design of a servo control algorithm is to bound these uncertainties and design a robust track following servos accordingly. In this paper, we present an experiment based methodology to characterize and bound the uncertainties in the dynamic response of a dual-stage actuator in the form of an uncertainty model. Subsequently, the uncertainty model is used for the analysis and synthesis of a robust dual-stage servo controller that is able to optimize position error variance in the presence of uncertainty information.

To maximize bandwidth for a hard disk servo system in the presence of modeling uncertainty, a tradeoff between performance and controller complexity is addressed by control-relevant modeling and robust control. Control-relevant modeling is accomplished by using the information of the appropriate weighting functions used in the control design to find a model via frequency domain curve fitting. This paper illustrates control relevant modeling using frequency domain data and design of a high bandwidth servo system in the presence of modeling uncertainty. Results using real-time implementation show agreement between the designed and achieved bandwidths

A systematic design procedure is presented that can be used to construct servo controllers for dual-stage actuation in a hard disk drive. The systematic approach is based on optimal control theory using an H/sub /spl infin//-norm-based control design, where servo design specifications are formulated in terms of relatively simple weighting functions. Different possible servo control strategies are designed and compared on performance and energy consumption. Results based on a piezoelectric milli-actuator from Hutchinson Technology Inc. illustrate the design of a dual-stage servo controller that is able to perform high-density track recording, with a significant reduction in power consumption.