Fast servo bang-bang seek control

Ho, H.T.

doi:10.1109/20.649890

Cited by 45 publications

(33 citation statements)

References 7 publications

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“…Further, saturating actuator commands can excite unmodeled dynamics and lengthen settle time. Thus for short seeks, time-optimal strategies with saturated commands, as in [3] and [4], do not directly apply.…”

Section: Introductionmentioning

confidence: 99%

Model Inversion Architectures for Settle Time Applications with Uncertainty

Rigney

Pao²,

Lawrence³

2006

Proceedings of the 45th IEEE Conference on Decision and Control

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Abstract-We compare two common model inversion architectures, plant inverse (PI) and closed-loop inverse (CLI), by evaluating their ability to achieve settle time performance improvements. The plant models of interest are discretetime, single-input single-output (SISO), linear time-invariant (LTI), nonminimum phase (NMP), and uncertain. We use a simple algebraic analysis to show that PI and CLI yield the same desired to actual output dynamics if the plant is minimum phase. Using a stable inverse approximation when the plant is certain but NMP, the same algebraic analysis shows that CLI achieves superior settle time performance relative to PI when the settle boundaries are tight. Simulation and experimental data are used to derive conclusions when the plant is NMP and uncertain. We show that CLI has superior performance over PI for our plant dynamics of interest when low frequency parametric uncertainty is present. For higher frequency unstructured uncertainty, the distinction between the two inversion architectures is negligible.

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Section: Introductionmentioning

confidence: 99%

Model Inversion Architectures for Settle Time Applications with Uncertainty

Rigney

Pao²,

Lawrence³

2006

Proceedings of the 45th IEEE Conference on Decision and Control

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“…Time-optimal control strategies with saturated commands, as in [8], do not apply in this application because the actuator commands for single-track HDD seeks are far from the saturation limits. Traditional iterative learning control assumes a fixed desired trajectory [9].…”

Section: Nmp Inversion For Settling Performancementioning

confidence: 99%

Adaptive inverse control for settling performance improvements

Rigney

Pao²,

Lawrence³

2009

2009 American Control Conference

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Abstract-Single-track hard disk drive (HDD) seek performance is measured by settling time, ts, 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. Previous work has shown feedforward dynamic inversion, coupled with an aggressive desired trajectory y d , is capable of achieving high performance settling 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 and covariance resetting are necessary additions to the baseline adaptive algorithm in order to achieve fast settling times. Compared to the nonadaptive solution with accurate system identification, we show the adaptive algorithm achieves a 22% reduction in average settling time and a 53% reduction in settling time standard deviation.

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“…controller, and neither of them accounts for the slew rate limits. Input shaping is used to account for the flexible dynamics during the entire slewing motion in [4], but the design procedure requires the feedforward control command to be numerically re-computed for each set point change.…”

Section: Introductionmentioning

confidence: 99%

Shaped time-optimal control for disk drive systems with back EMF, slew rate limits, and different acceleration and deceleration rates

La-orpacharapan

Pao

Proceedings of the 2003 American Control Conference, 2003.

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This paper derives shaped time-optimal servomechanism (STOS) controllers for flexible structures consisting of a second-order rigid body with damping and a damped flexible mode. The approach uses input shaping to account for the damped flexible mode by altering the time-optimal velocity profile that moves the second-order rigid body with damping from rest to rest. Considering the slew rate limit constraints, the maneuver is categorized into three ranges due to their different shaped input profiles. For one of the maneuver ranges, when systems have different acceleration and deceleration capabilities, the time-optimal control for the second-order with damping rigid body portion has to be solved numerically. However, the STOS control for this maneuver range can still be derived analytically by using the curve-fit approximation of the switching time of the time-optimal control. Simulations show that the derived STOS control laws yield near timeoptimal performance without unwanted residual vibration at the end of the maneuver.

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Fast servo bang-bang seek control

Cited by 45 publications

References 7 publications

Model Inversion Architectures for Settle Time Applications with Uncertainty

Model Inversion Architectures for Settle Time Applications with Uncertainty

Adaptive inverse control for settling performance improvements

Shaped time-optimal control for disk drive systems with back EMF, slew rate limits, and different acceleration and deceleration rates

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