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Control system with a non-parametric predictive algorithm for a high-speed rotating machine with magnetic bearings

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Języki publikacji
EN
Abstrakty
EN
This paper deals with research on the magnetic bearing control systems for a high-speed rotating machine. Theoretical and experimental characteristics of the control systems with the model algorithmic control (MAC) algorithm and the proportional-derivative (PD) algorithm are presented. The MAC algorithm is the non-parametric predictive control method that uses an impulse response model. A laboratory model of the rotor-bearing unit under study consists of two active radial magnetic bearings and one active axial (thrust) magnetic bearing. The control system of the rotor position in air gaps consists of the fast prototyping control unit with a signal processor, the input and output modules, power amplifiers, contactless eddy current sensors and the host PC with dedicated software. Rotor displacement and control current signals were registered during investigations using a data acquisition (DAQ) system. In addition, measurements were performed for various rotor speeds, control algorithms and disturbance signals generated by the control system. Finally, the obtained time histories were presented, analyzed and discussed in this paper.
Rocznik
Strony
art. no. e138998
Opis fizyczny
Bibliogr. 26 poz., il., wykr., fot., tab.
Twórcy
  • Faculty of Mechatronics, Armament and Aerospace, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908, Warsaw, Poland
autor
  • Institute of Fundamental Technological Research, Polish Academy of Science, ul. Adolfa Pawińskiego 5B, 02-106, Warsaw, Poland
  • Faculty of Mechatronics, Armament and Aerospace, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908, Warsaw, Poland
  • Faculty of Mechatronics, Armament and Aerospace, Military University of Technology, ul. gen. Sylwestra Kaliskiego 2, 00-908, Warsaw, Poland
Bibliografia
  • [1] P.-H. Kuo, R.-M. Lee, and C.-C. Wang, “A High-Precision Random Forest-Based Maximum Lyapunov Exponent Prediction Model for Spherical Porous Gas Bearing Systems,” IEEE Access, vol. 8, pp. 168079‒168086, 2020, doi: 10.1109/ACCESS. 2020.3022854.
  • [2] E. Brusa, “Semi-active and active magnetic stabilisation of supercritical rotor dynamics by contra-rotating damping,” Mechatronics, vol. 24, pp. 500–510, 2014, doi: 10.1016/j.mechatronics. 2014.06.001.
  • [3] O. Halminen, A. Kärkkäinen, J. Sopanen, and A. Mikkola, “Active magnetic bearing-supported rotor with misaligned cageless backup bearings: A dropdown event simulation model,” Mech. Syst. Signal Process., vol. 50‒51, pp. 692–705, 2015, doi: 10.1016/j.ymssp.2014.06.001.
  • [4] J.Y. Hung, G.A. Nathaniel, and F. Xia, “Non-linear control of a magnetic bearing system,” Mechatronics, vol. 13, pp. 621–637, 2003, doi: 10.1016/S0957-4158(02)00034-X.
  • [5] J. Sawicki, E.H. Maslen, and K.R. Bischof, “Modeling and performance evaluation of machining spindle with active magnetic bearings,” J. Mech. Sci. Technol., vol. 21, pp. 847–850, 2007, doi: 10.1007/BF03027055.
  • [6] R. Siva Srinivas, R. Tiwari, and Ch. Kannababu, “Application of active magnetic bearings in flexible rotordynamic systems – A state-of-the-art review,” Mech. Syst. Signal Process., vol. 106, pp. 537‒572, 2018.
  • [7] K. Falkowski, M. Henzel, and M. Żokowski, “The analysis of the control system for the bearingless induction electric motor,” J. Vibroeng., vol. 14, no. 1, pp.16‒21, 2012.
  • [8] R. Stocki, T. Szolc, P. Tauzowski, and J. Knabel, “Robust design optimisation of the vibrating rotor shaft system subjected to selected dynamic constraints,” Mech. Syst. Signal Process., vol. 29, pp. 34‒44, 2012, doi: 10.1016/j.ymssp.2011.07.023.
  • [9] T. Szolc, K. Falkowski, M. Henzel, and P. Kurnyta-Mazurek, “Determination of parameters for a design of the stable electro-dynamic passive magnetic support of a high-speed flexible rotor,” Bull. Pol. Acad. Sci. Tech. Sci., vol. 67, no. 1, pp. 91‒105, 2019, doi: 10.24425/bpas.2018.125719.
  • [10] S. Zhe et al., “Identification of active magnetic bearing system with a flexible rotor,” Mech. Syst. Signal Process., vol. 49, pp. 302–316, 2014.
  • [11] A. Chiba et al., Magnetic bearings and bearingless drives, Elsevier’s Science Technology Rights Department in Oxford, UK, 2005.
  • [12] G. Schweitzer, A. Traxler, and H. Bleuler, Magnetlager: Grundlagen, Eigenshaften und Anwendungen berührungsfreier elektromagnetischer Lager, Springer Verlag, Berlin, 1992.
  • [13] A. Piłat, “Modelling, investigation, simulation, and PID current control of active magnetic levitation FEM model,” Methods and Models in Automation and Robotics (MMAR), 18th International Conference on Methods and Models in Automation and Robotics, Poland, 2013, pp. 299–304, doi: 10.1109/MMAR.2013.6669923.
  • [14] B. Tomczuk, J. Zimon, and K. Zakrzewski, “Integral parameters determination in the magnetic bearing using finite element method,” Computational Electromagnetics (CEM), 6th International Conference on Computational Electromagnetics, Germany, 2006, pp. 1‒4.
  • [15] Z. Gosiewski and A. Mystkowski, “Robust control of active magnetic suspension: analytical and experimental results,” Mech. Syst. Signal Process., vol. 22, no. 6, pp. 1297‒1303, 2008, doi: 10.1016/j.ymssp.2007.08.005.
  • [16] M. Henzel and P. Mazurek, “The analysis of the control system of the active magnetic bearing,” Electrodynamic and Mechatronic Systems, 3rd International Students Conference on Electrodynamics and Mechatronics (SCE III), Opole, Poland, 2011, pp. 53‒58, doi: 10.1109/SCE.2011.6092124.
  • [17] A.M. Beizama, J.M. Echeverria, M. Martinez-Iturralde, I. Egana, and L. Fontan, “Comparison between pole-placement control and sliding mode control for 3-pole radial magnetic bearings,” 2008 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2008, pp. 1315‒1320, doi: 10.1109/SPEEDHAM.2008.4581115.
  • [18] Ch.Wu and Ch. Zhu, “Implicit generalised predictive control of an active magnetic bearing system,” 17th International Conference on Electrical Machines and Systems, Hangzhou, China, 2014, pp. 2319–2323.
  • [19] K.S. Holkar and L.M. Waghmare, “An overview of model predictive controller,” Int. J.Control Autom., vol. 3, no. 4, pp. 47–64, 2010.
  • [20] A.D. Lewis, A Mathematical Approach to Classical Control, Queen’s University, Canada, 2003.
  • [21] G. Genta, Dynamics of Rotating Systems, Springer Science + Business Media, Inc., Mechanical Engineering Series, 2005.
  • [22] A. Ammar et al., “An experimental assessment of direct torque control and model predictive control methods for induction machine drive,” International Conference on Electrical Sciences and Technologies in Maghreb, Algiers, 2018, pp. 1‒6, doi: 10.1109/CISTEM.2018.8613419.
  • [23] K.T. Wrobel, K. Szabat, and P. Serkies, “Long-horizon model predictive control of induction motor drive,” Arch. Electr. Eng., vol. 68, no. 3, pp. 579–593, 2019.
  • [24] P. Kurnyta-Mazurek, A. Kurnyta, and M. Henzel, “Analysis of the method of predictive control applicable to active magnetic suspension systems of aircraft engines,” Research Works of Air Force Institute of Technology, vol. 37, pp. 195‒206, 2015, doi: 10.1515/afit-2015-0034.
  • [25] A. Niederliński, J. Mościński, and Z. Ogonowski, Adaptive control, Scientific Publisher PWN, Warsaw, 1995 [in Polish].
  • [26] P. Kurnyta-Mazurek, T. Szolc, M. Henzel, and K. Falkowski: ”Analysis of control methods for the jet engine rotor with magnetic bearings,” Proceedings of 14th International Conference on SIRM 2021 – Dynamics of Rotating Machines, Gdansk, Poland, 2021.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-397eebcb-4865-4036-92d7-5f16ffb1c54e
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