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Characteristic model based all-coefficient adaptive control of an AMB suspended energy storage flywheel test rig

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Abstract

Feedback control of active magnetic bearing (AMB) suspended energy storage flywheel systems is critical in the operation of the systems and has been well studied. Both the classical proportional-integral-derivative (PID) control design method and modern control theory, such as H control and μ-synthesis, have been explored. PID control is easy to implement but is not effective in handling complex rotordynamics. Modern control design methods usually require a plant model and an accurate characterization of the uncertainties. In each case, few experimental validation results on the closed-loop performance are available because of the costs and the technical challenges associated with the construction of experimental test rigs. In this paper, we apply the characteristic model based all-coefficient adaptive control (ACAC) design method for the stabilization of an AMB suspended flywheel test rig we recently constructed. Both simulation and experimental results demonstrate strong closed-loop performance in spite of the simplicity of the control design and implementation.

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References

  1. 1

    Mousavi G S M, Faraji F, Majazi A, et al. A comprehensive review of flywheel energy storage system technology. Renew Sustain Energy Rev, 2017, 67: 477–490

  2. 2

    Hebner R, Beno J, Walls A. Flywheel batteries come around again. IEEE Spectr, 2002, 39: 46–51

  3. 3

    Bitterly J G. Flywheel technology: past, present and 21st century projections. IEEE Aerosp Electron Syst Mag, 1998, 13: 13–16

  4. 4

    Reid C M, Miller T B, Hoberecht M A, et al. History of electrochemical and energy storage technology development at NASA Glenn Research Center. J Aerosp Eng, 2013, 26: 361–371

  5. 5

    Farhadi M, Mohammed O. Energy storage technologies for high-power applications. IEEE Trans Ind Applicat, 2016, 52: 1953–1961

  6. 6

    Zhao H, Wu Q, Hu S, et al. Review of energy storage system for wind power integration support. Appl Energy, 2015, 137: 545–553

  7. 7

    Hemmati R, Saboori H. Emergence of hybrid energy storage systems in renewable energy and transport applications -A review. Renew Sustain Energy Rev, 2016, 65: 11–23

  8. 8

    Schweitzer G, Maslen E H. Magnetic Bearings: Theory, Design, and Application to Rotating Machinery. Berlin: Springer, 2009

  9. 9

    Li G, Lin Z, Allaire P E, et al. Modeling of a high speed rotor test rig with active magnetic bearings. J Vib Acoust, 2006, 128: 269–281

  10. 10

    Li G. Robust stabilization of rotor-active magnetic bearing systems. Dissertation for Ph.D. Degree. Charlottesville: University of Virginia, 2007

  11. 11

    Dever T P, Brown G V, Duffy K P, et al. Modeling and development of a magnetic bearing controller for a high speed flywheel system. In: Proceedings of the 2nd International Energy Conversion Engineering Conference, Providence, 2004. 5626

  12. 12

    Brown G V, Kascak A, Jansen R H, et al. Stabilizing gyroscopic modes in magnetic-bearing-supported flywheels by using cross-axis proportional gains. In: Proceedings of the AIAA Guidance, Navigation, and Control Conference, San Francisco, 2005. 5955

  13. 13

    Arghandeh R, Pipattanasomporn M, Rahman S. Flywheel energy storage systems for ride-through applications in a facility microgrid. IEEE Trans Smart Grid, 2012, 3: 1955–1962

  14. 14

    Lyu X, Di L, Yoon S Y, et al. A platform for analysis and control design: emulation of energy storage flywheels on a rotor-AMB test rig. Mechatronics, 2016, 33: 146–160

  15. 15

    Ahrens M, Kucera L, Larsonneur R. Performance of a magnetically suspended flywheel energy storage device. IEEE Trans Contr Syst Technol, 1996, 4: 494–502

  16. 16

    Hawkins L A, Murphy B T, Kajs J. Analysis and testing of a magnetic bearing energy storage flywheel with gainscheduled, MIMO control. In: Proceedings of the ASME Turbo Expo, Munich, 2000. 1–8

  17. 17

    Peng C, Fan Y, Huang Z, et al. Frequency-varying synchronous micro-vibration suppression for a MSFW with application of small-gain theorem. Mech Syst Signal Process, 2017, 82: 432–447

  18. 18

    Sivrioglu S, Nonami K, Saigo M. Low power consumption nonlinear control with H1 compensator for a zero-bias flywheel AMB system. J Vib Control, 2004, 10: 1151–1166

  19. 19

    Mushi S E, Lin Z, Allaire P E. Design, construction, and modeling of a flexible rotor active magnetic bearing test rig. IEEE/ASME Trans Mechatron, 2012, 17: 1170–1182

  20. 20

    Wu H, Hu J, Xie Y. Characteristic model-based all-coefficient adaptive control method and its applications. IEEE Trans Syst Man Cybern Part C-Appl Rev, 2007, 37: 213–221

  21. 21

    Wu H, Hu J, Xie Y, et al. Characteristic Model-Based Intelligent Adaptive Control (in Chinese). Beijing: China Science and Technology Press, 2009

  22. 22

    Meng B, Wu H X, Lin Z L. Characteristic model based control of the X-34 reusable launch vehicle in its climbing phase. Sci China Ser F-Inf Sci, 2009, 52: 2216–2225

  23. 23

    Gao S G, Dong H R, Ning B. Characteristic model-based all-coefficient adaptive control for automatic train control systems. Sci China Inf Sci, 2014, 57: 092201

  24. 24

    Wang L J, Meng B. Characteristic model-based control of robotic manipulators with dynamic uncertainties. Sci China Inf Sci, 2017, 60: 079201

  25. 25

    Huang J F, Kang Y, Meng B, et al. Characteristic model based adaptive controller design and analysis for a class of SISO systems. Sci China Inf Sci, 2016, 59: 052202

  26. 26

    Jiang T T, Wu H X. A framework for stability analysis of high-order nonlinear systems based on the CMAC method. Sci China Inf Sci, 2016, 59: 112201

  27. 27

    Sun D Q. Stability analysis of golden-section adaptive control systems based on the characteristic model. Sci China Inf Sci, 2017, 60: 092205

  28. 28

    Di L, Lin Z. Control of a flexible rotor active magnetic bearing test rig: a characteristic model based all-coefficient adaptive control approach. Control Theor Technol, 2014, 12: 1–12

  29. 29

    Kascak P E, Dever T P, Jansen R H. Magnetic circuit model of PM motor-generator to predict radial forces. In: Proceedings of the 1st International Energy Conversion Engineering Conference, Cleveland, 2003

  30. 30

    Xie Y, Wu H. The application of the goden section in adative robust controller design (in Chinese). Acta Autom Sin, 1992, 18: 178–185

  31. 31

    Wu H, Hu J, Xie Y, et al. Theory and applications of characteristic modeling: an introductory overview. Int J Intell Contr Syst, 2015, 20: 1–8

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Correspondence to Zongli Lin.

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Lyu, X., Di, L., Lin, Z. et al. Characteristic model based all-coefficient adaptive control of an AMB suspended energy storage flywheel test rig. Sci. China Inf. Sci. 61, 112204 (2018). https://doi.org/10.1007/s11432-017-9327-0

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Keywords

  • adaptive control
  • characteristic modeling
  • energy storage flywheels
  • active magnetic bearings