Abstract
A characteristic model based all-coefficient adaptive control law was recently implemented on an experimental test rig for high-speed energy storage flywheels suspended on magnetic bearings. Such a control law is an intelligent control law, as its design does not rely on a pre-established mathematical model of a plant but identifies its characteristic model while the plant is being controlled. Extensive numerical simulations and experimental results indicated that this intelligent control law outperforms a μ-synthesis control law, originally designed when the experimental platform was built in terms of their ability to suppress vibration on the high-speed test rig. We further establish, through an extensive simulation, that this intelligent control law possesses considerable robustness with respect to plant uncertainties, external disturbances, and time delay.
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References
Brown GV, Kascak AF, Jansen RH, et al., 2005. Stabililizing gyroscopic modes in magnetic-bearing-supported flywheels by using cross-axis proportional gains. Proc AIAA Guidance, Navigation, and Control Conf and Exhibit, p.5955. https://doi.org/10.2514/6.2005-5955
Dever TP, Brown GV, Duffy KP, et al., 2004. Modeling and development of magnetic bearing controller for high speed flywheel system. 2nd Int Energy Conversion Engineering Conf, p.5626. https://doi.org/10.2514/6.2004-5626
Di L, Lin ZL, 2014. Control of a flexible rotor active magnetic bearing test rig: a characteristic model based all-coefficient adaptive control approach. Contr Theor Technol, 12(1):1–12. https://doi.org/10.1007/s11768-014-0184-0
Farhadi M, Mohammed O, 2016. Energy storage technologies for high-power applications. IEEE Trans Ind Appl, 52(3):1953–1961. https://doi.org/10.1109/TIA.2015.2511096
Hebner R, Beno J, Walls A, 2002. Flywheel batteries come around again. IEEE Spectr, 39(4):46–51. https://doi.org/10.1109/6.993788
Koohi-Kamali S, Tyagi VV, Rahim NA, et al., 2013. Emergence of energy storage technologies as the solution for reliable operation of smart power systems: a review. Renew Sust Energ Rev, 25:135–165. https://doi.org/10.1016/j.rser.2013.03.056
Li GX, Lin ZL, Allaire PE, et al., 2006. Modeling of a high speed rotor test rig with active magnetic bearings. J Vibr Acoust, 128(3):269–281. https://doi.org/10.1115/1.2172254
Lyu XJ, Di L, Yoon SY, et al., 2016. A platform for analysis and control design: emulation of energy storage flywheels on a rotor-AMB test rig. Mechatronics, 33:146–160. https://doi.org/10.1016/j.mechatronics.2015.12.007
Lyu XJ, Di L, Lin ZL, et al., 2018a. Characteristic model based all-coefficient adaptive control of an AMB suspended energy storage flywheel test rig. Sci China Inform Sci, 61(11):112204. https://doi.org/10.1007/s11432-017-9327-0
Lyu XJ, Di L, Lin ZL, et al., 2018b. Performance of AMB suspended energy sorage flywheel controllers in the presence of time delays. 16th Int Symp on Magentic Bearings.
Mousavi G SM, Faraji F, Majazi A, et al., 2017. A comprehensive review of flywheel energy storage system technology. Renew Sust Energ Rev, 67:477–490. https://doi.org/10.1016/j.rser.2016.09.060
Mushi SE, Lin Z, Allaire PE, 2012. Design, construction, and modeling of a flexible rotor active magnetic bearing test rig. IEEE/ASME Trans Mechatron, 17(6):1170–1182. https://doi.org/10.1109/TMECH.2011.2160456
Peng C, Fan YH, Huang ZY, et al., 2017. Frequency-varying synchronous micro-vibration suppression for a MSFW with application of small-gain theorem. Mech Syst Sign Process, 82:432–447. https://doi.org/10.1016/j.ymssp.2016.05.033
Reid CM, Miller TB, Hoberecht MA, et al., 2013. History of electrochemical and energy storage technology development at NASA Glenn research center. J Aerosp Eng, 26(2):361–371. https://doi.org/10.1061/(ASCE)AS.1943-5525.0000323
Schweitzer G, Maslen EH, 2009. Magnetic Bearings: Theory, Design, and Application to Rotating Machinery. Springer Berlin, Germany.
Sivrioglu S, Nonami K, Saigo M, 2004. Low power consumption nonlinear control with H∞ compensator for a zero-bias flywheel AMB system. Mod Anal, 10(8):1151–1166. https://doi.org/10.1177/1077546304043544
Wu HX, Hu J, Xie YC, 2007. Characteristic model-based all-coefficient adaptive control method and its applications. IEEE Trans Syst Man Cybern Part C (Appl Rev), 37(2):213–221. https://doi.org/10.1109/TSMCC.2006.887004
Wu HX, Hu J, Xie YC, 2009. Characteristic Model-Based and Intelligent Adaptive Control. Science and Technology Press of China, Beijing, China (in Chinese).
Zhao HR, Wu QW, Hu SJ, et al., 2015. Review of energy storage system for wind power integration support. Appl Energy, 137:545–553. https://doi.org/10.1016/j.apenergy.2014.04.103
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Project supported by the Fundamental Research Funds for the Central Universities, China (No. 2662018QD031)
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Lyu, X., Di, L. & Lin, Z. On robustness of an AMB suspended energy storage flywheel platform under characteristic model based all-coefficient adaptive control laws. Frontiers Inf Technol Electronic Eng 20, 120–130 (2019). https://doi.org/10.1631/FITEE.1800606
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DOI: https://doi.org/10.1631/FITEE.1800606
Key words
- Intelligent control
- Robustness
- Uncertainty
- Disturbance rejection
- Active magnetic bearings
- Energy storage flywheels