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Robust track-following control for dual-stage servo systems in HDDs Ryozo Nagamune Division of Optimization & Systems Theory Royal Institute of Technology,

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Presentation on theme: "Robust track-following control for dual-stage servo systems in HDDs Ryozo Nagamune Division of Optimization & Systems Theory Royal Institute of Technology,"— Presentation transcript:

1 Robust track-following control for dual-stage servo systems in HDDs Ryozo Nagamune Division of Optimization & Systems Theory Royal Institute of Technology, Sweden Seminar at Department of Mechanical Engineering, University of British Columbia February 3 rd, 2006 (Joint work with R. Horowitz and his students at UC Berkeley)

2 Outline Track following control in HDDs Worst-case H 2 performance minimization Design techniques –Multirate control –Robust control (Mixed H 2 /H 1, Mixed H 2 / , Robust H 2 ) Examples Conclusions

3 Track following control Data track Read/Write head Goal: Control the R/W head to follow the data track in a highly accurate manner Inputs : Voice Coil Motor (VCM) + mini/micro-actuator Measurements : Position Error Signal (PES) + other sensor signals VCM Servo sector Dual-stage & multi-sensing system

4 Robust control theory Dual-stage multi-sensing control Dual-stage multi- sensing system PESVCM Micro- actuator Sensor signals (PZT-sensor etc) Fixed sampling rate : Disturbances (track runout, windage, measurement noise, etc.) Variations 1. Multivariable control 2. Possibly multirate control 4. Optimal control 3. Robust control Control features Conventional methods PQ method Sensitivity decoupling

5 Outline Track following control in HDDs Worst-case H 2 performance minimization Design techniques –Multirate control –Robust control (Mixed H 2 /H 1, Mixed H 2 / , Robust H 2 ) Examples Conclusions

6 Dual-stage multi-sens. system S : Multirate sampler, H : Multirate hold K : PES etc. : Disturbances (runout, windage, noise) Multirate Multivariable Design K s.t. MeasurementsControl inputs RobustnessOptimality : map from w to z Controller Uncertainty : robustly stabilizing controller set Parametric uncertainties in Dynamic uncertainty Worst-case H 2 minimization

7 Outline Track following control in HDDs Worst-case H 2 performance minimization Design techniques –Multirate control –Robust control (Mixed H 2 /H 1, Mixed H 2 / , Robust H 2 ) Examples Conclusions Control for LTI systems

8 Outline Track following control in HDDs Worst-case H 2 performance minimization Design techniques –Multirate control –Robust control (Mixed H 2 /H 1, Mixed H 2 / , Robust H 2 ) Examples Conclusions

9 Nominal K Dynamic uncertainty Original formulation Performance : Nominal Stability : Dynamic uncertainty Advantage : Computationally inexpensive Disadvantage : Insufficient robustness conditions We solve a convex optimization problem. Mixed H 2 /H 1 synthesis (Scherer, Oliveira, etc)

10 Nominal K Dynamic & parametric uncertainties Original formulation Performance : Nominal Stability : Dynamic & parametric Advantage : Guaranteed robust stability Disadvantage : No robust performance We combine a mixed H 2 /H 1 technique with D-K iterations. Mixed H 2 /  synthesis (Packard, Doyle, Young, etc)

11 Nominal K Parametric uncertainties Original formulation Performance : Robust Stability : Parametric uncertainties Advantage : Robust performance Disadvantage : Computationally expensive No dynamic uncertainty We solve a series of convex optimization problems. Robust H 2 synthesis (Kanev, Scherer, Paganini, etc)

12 Outline Track following control in HDDs Worst-case H 2 performance minimization Design techniques –Multirate control –Robust control (Mixed H 2 /H 1, Mixed H 2 / , Robust H 2 ) Examples Conclusions

13 VCM Relative position error signal Position Error Signal (PES) Vibration signal Slider Read/write head Micro- actuator (MA) Two inputs Sampling/hold rates twice faster than that of PES Noise Airflow Track runout Three outputs Example 1: Setting

14 Example 1 : Block diagram Gvcm Gma Gc Input Output Disturbance Parametric uncertainty Dynamic uncertainty VCM dynamics Microactuator dynamics Runout model

15 Example 1 : Simulation result Design method RMS value of PES (nm) degK ( before reduction ) NominalWorst PQ method Sensitivity decoupling Mixed H 2 /H (13) Mixed H 2 /  (13) Robust H (11) 200 enumerations of parametric variations

16 Example 2 : Setting (with R. de Callafon at UC San Diego) Inputs : u V (VCM) u PZT (PZT-actuator) Measurement : y LDV (Head position) Frequency responses for 36 dual-stage systems u V to y LDV u PZT to y LDV PZT-actuated suspension

17 Example2 : Modeling Suspension modes E-block PZT-driver uVuV y LDV u PZT    u V to y LDV u PZT to y LDV Experiment Sampled models u V to y LDV u PZT to y LDV

18 Example 2 : Controller design SimulationExperiment Amplitude plots of sensitivity functions (from runout to PES)  Robust H 2 synthesis  Single-rate controller  deg K = 13 runout + - PES plantK - uVuV u PZT y LDV

19 Outline Track following control in HDDs Worst-case H 2 performance minimization Design techniques –Multirate control –Robust control (Mixed H 2 /H 1, Mixed H 2 / , Robust H 2 ) Examples Conclusions

20  A multirate multivariable robust optimal track-following control in HDDs  Worst-case H 2 minimization problem  Design methods via convex optimization  Mixed H 2 /H 1  Mixed H 2 /   Robust H 2  General dual-stage multi-sensing systems Conclusions

21 Future research topics  Sampled-data control Inter-sampling behavior  Performance analysis tool Degradation of track-following property  Multiple controller / Adaptive controller Improvement of tracking precision  Probabilistic approach More accurate uncertainty description  User-friendly software


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