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Determining the observer parameters for back EMF estimation for selected types of electrical motors

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EN
Abstrakty
EN
In the paper a procedure for determining the observer parameters for selected types of electrical motors is discussed. The procedure is based on the identity observer developed by Luenberger. The paper presents determining the parameters using calculation examples for the DC motor and also for the permanent magnet synchronous motor (PMSM), which utilize the extended state vector to estimate the back electromotive force (BEMF). Presented observer for PMSM does not need to use the information about load torque. The main task of this study is to show how to utilize these general theory to a specified type of motors. Such procedure avoids the use of time-consuming methods of the parameters selection, which are based on random algorithms or the computational intelligence.
Rocznik
Strony
439--447
Opis fizyczny
Bibliogr. 16 poz., rys., wykr.
Twórcy
autor
  • Institute of Control and Information Engineering, Poznan University of Technology, 3A Piotrowo St., 61-138 Poznan, Poland
Bibliografia
  • [1] D. Luenberger, “An introduction to observers”, IEEE Transactions on Automatic Control 16 (6), 596–602 (1971).
  • [2] A. Dębowski, D. Lewandowski, and P. Łukasiak, “Mixed-loop control of an asynchronous traction drive based on electromagnetic state stimulator concept”, 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA), 1–10 (2013).
  • [3] K. Urbański and K. Zawirski, “Improved method for position estimation using a two-dimensional scheduling array”, Automatika 56 (3), 331–340 (2015).
  • [4] X. Song, J. Fang, B. Han, and S. Zheng, “Adaptive compensation method for high-speed surface PMSM sensorless drives of EMFbased position estimation error”, IEEE Transactions on Power Electronics 31 (2), 1438–1449 (2016).
  • [5] D. Janiszewski, “Load torque estimation for sensorless PMSM drive with output filter fed by PWM converter”, 39th Annual Conference of the IEEE Industrial Electronics Society (IECON 2013), 2953–2959 (2013).
  • [6] Z. Wang, Y. Zheng, Z. Zou, and M. Cheng, “Position sensorless control of interleaved CSI fed PMSM drive with extended Kalman filter”, IEEE Transactions on Magnetics 48 (11), 3688–3691 (2012).
  • [7] K. Urbański, “Comparison of methods for back EMF estimation at low speed for PMSM drive”, 2014 16th International Conference on Mechatronics – Mechatronika (ME), 32–37 (2014).
  • [8] F. Parasiliti, R. Petrella, and M. Tursini, “Sensorless speed control of a PM synchronous motor by sliding mode observer”, Proceedings of the 1997 IEEE International Symposium on Industrial Electronics, ISIE’97, 1106–1111 (1997).
  • [9] P. Vaclavek and P. Blaha, “Lyapunov function based design of PMSM state observer for sensorless control”, 2009 IEEE Symposium on Industrial Electronics Applications, ISIEA 2009 1, 331–336 (2009).
  • [10] P. Brandstetter, M. Dobrovsky, O. Petrtyl, C.S.T. Dong, and H.H. Vo, “Sensorless control of induction motor drive using BEMFMRAS with Kalman filter”, 2016 ELEKTRO, 121–126 (2016).
  • [11] O. Benjak and D. Gerling, “Review of position estimation methods for IPMSM drives without a position sensor. Part II: Adaptive methods”, 2010 XIX International Conference on Electrical Machines (ICEM), 1–6 (2010).
  • [12] H. Kim, J. Son, and J. Lee, “A high-speed sliding-mode observer for the sensorless speed control of a PMSM”, IEEE Transactions on Industrial Electronics 58 (9), 4069–4077 (2011).
  • [13] J. Kabziński, “Adaptive, compensating control of wheel slip in railway vehicles”, Bull. Pol. Ac.: Tech. 63 (4), 955–963 (2015).
  • [14] P. Vas, Sensorless Vector and Direct Torque Control, Oxford University Press, Oxford, 1998.
  • [15] E. Clarke, Circuit Analysis of A-C Power Systems: Symmetrical and Related Components, Wiley, New York, 1943.
  • [16] A. Germano, F. Parasiliti, and M. Tursini, “Sensorless speed control of a PM synchronous motor drive by Kalman filter”, Proc. 1994 International Conference on Electrical Machines 2, 540–544 (1994).
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017).
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-67e39043-648c-43c2-b0b3-b48f80fdaa55
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