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Adaptive Robust Control F or Dual Stage Hard Drives

in GOD we trust. Adaptive Robust Control F or Dual Stage Hard Drives. استاد راهنما : جناب آقای دکتر حمید تقی راد. Dr. Hamid D. Taghirad. هادی حاجی اقراری دانشجوی کارشناسی ارشد مهندسی برق – کنترل دانشگاه خواجه نصیرالدین طوسی. H.H.Eghrary MS Student of Electrical Engineering

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Adaptive Robust Control F or Dual Stage Hard Drives

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  1. in GOD we trust Adaptive Robust Control ForDual Stage Hard Drives استاد راهنما :جناب آقای دکتر حمید تقی راد Dr. Hamid D. Taghirad هادی حاجی اقراری دانشجوی کارشناسی ارشد مهندسی برق –کنترل دانشگاه خواجه نصیرالدین طوسی H.H.Eghrary MS Student of Electrical Engineering K.N.Toosi Univ.

  2. 2end Seminar Presentation Sunday, August 12,2007 Introduction to Adaptive Robust Control • Obstacles for Control Algorithm Design • Strategies for Performance Improvement • Adaptive Robust Control (ARC) For a HDD Adaptive Control Robust Control • ARC via Discontinuous Projection • ARC via Smooth Projection • Desired Compensation ARC

  3. Obstacles for Control Algorithm Design: • Inherent Nonlinearity • Unknown But Reproducible • for example: Unknown parameters • Unreproducable • for example: • model Disturbance • Modeling Uncertainty

  4. Strategies for Performance Improvement: • Nonlinear Analysis And Synthesis Deal With Nonlinearity Directly : Nonlinear Control Effective for both reproducible and none Reproducible Uncertainities • Fast Robust Feedback • Controled Learning For Uncertainity Reduction Effective for Reproducible Uncertainities

  5. Adaptive Robust Control(ARC) Adaptive Robust • Reduce the model uncertainty • Zero Tracking Error • (Without High gain Feedback) • Attenuate the effect of model uncertainties through • robust feedback. • Instantaneous • Reaction • Drawbacks: • Transient Performance of the system is not Clear. • Unknown Nonlinear functions such as external disturbances are not considered. • Drawbacks: • Transient Performance of the system is not Clear. • Unknown Nonlinear functions such as external disturbances are not considered.

  6. Deterministic Robust Control Adaptive Control Conflicts • Used to Design Supervisor • Use to Design Base Line Controller Guarantee Transient Performance Prescribed final tracking accuracy Improved Asymptotic Input Tracking

  7. Conventional Adaptation Law  Estimated Parameters May not be Bounded Conflicts Deterministic Robust Control  Requires Bounds On Uncertainties Modify The Conventional Adaptation Law Bounded Estimation Parameters

  8. Adaptive Robust ControlForHard Disk Drive Servo System Problem Formulation:

  9. Robust Control scheme: Adaptive Control scheme:

  10. Stability Analysis: Lyapanov Function: Adaptive Control scheme: Parameter Estimation Estimation Error

  11. Results: • Limitations Of Adaptive Control • Transient Performance is Unknown • Uncertain nonlinearity are not Considered

  12. Robust Control scheme: More In Detail: • Error Dynamics  Choose The such that:

  13. Stability Analysis: Lyapanov Function: Choose small such that: : Stable

  14. Tracking Error • Steady State Error

  15. Decrease for decreasing Steady State Error Parameter Adaptation

  16. Adaptive Robust Control

  17. Conflicts Conventional Adaptation Law  Estimated Parameters May not be Bounded REMIND Deterministic Robust Control  Requires Bounds On Uncertainties Modify The Conventional Adaptation Law Bounded Estimation Parameters

  18. Adaptive Robust Control Via Discontinuous Projection

  19. Remains in Increases Decreases Remains in Parameter Uncertainty Bounded via Adaptation Progress RobustControlProblem Solved

  20. Adaptive Robust Control Via Smooth Projection There is a Lyapanov Function : Stability is Guaranteed

  21. Desired Compensation ARC Desired Trajectory Remind ARC Scheme Real Parameter Measurement (Measurement Noise) Dynamic Stabilizing Feedback Static Feedback

  22. Desired Compensation ARC Regressors Dose not Depend On Measurements • Eliminate Measurement Noise Effect on Parameter Adaptation • Off-Line Regressors Calculation Fast Error Dynamic and Parameter Adaptation Facilitate Control Gain Tuning Process due to Separation of Robust Control And Parameter Adaptation

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