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Mixed Phenomenological and Neural Approach to Induction Motor Speed Estimation

  • Bartlomiej BeliczynskiEmail author
  • Lech M. Grzesiak
  • Bartlomiej Ufnalski
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 517)

Abstract

A special phenomenological model of induction motor speed estimation in the drive system is derived. The basis of approximation is calculated from the system mathematical model as a set of transformed, easily measured input variables. It is demonstrated analytically that the set suits well to speed approximation if the approximated signal is a constant or changes linearly. It is then demonstrated numerically that this set is also quite effective under non-zero jerk. Such a system could easily be implemented by widely experienced feedforward neural networks. Illustrative examples and simulation results are attached.

Keywords

Induction Motor Load Torque Speed Estimation Rotor Winding Induction Motor Drive 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Beliczynski, B., Grzesiak, L.: Induction motor speed estimation: Neural versus phenomenological model approach. Neurocomputing 43, 17–36 (2002)CrossRefzbMATHGoogle Scholar
  2. 2.
    Beliczynski, B., Kubowicz, K.: Appoximately static relationship between model variables. Przeglad Elektrotechniczny 53(4), 385–389 (2004)Google Scholar
  3. 3.
    Britz, F., Degner, M., Garcia, P., Lorentz, R.: Comparison of saliency-based sensorless control techniques for ac machines. IEEE Trans. Ind. Appl. 40(4), 1107–1115 (2004)CrossRefGoogle Scholar
  4. 4.
    Cirrincione, M., Accetta, A., Pucci, M., Vitale, G.: MRAS speed observer for high-performance linear induction motor drives based on linear neural networks. IEEE Transactions on Power Electronics 28(1), 123–134 (2013)CrossRefGoogle Scholar
  5. 5.
    Dumnic, B., Popadic, B., Milicevic, D., Katic, V., Oros, D.: Speed-sensorless vector control of an wind turbine induction generator using artificial neural network. In: 16th International Power Electronics and Motion Control Conference and Exposition (PEMC), pp. 371–376, September 2014Google Scholar
  6. 6.
    Girovsky, P., Timko, J., Zilkova, J.: Shaft sensor-less foc control of an induction motor using neural estimators. Acta Polytechnica Hungarica 9(4) (2012)Google Scholar
  7. 7.
    Goedtel, A., Nunes da Silva, I., Amaral Serni, P.J., Suetake, M., Franscisco do Nascimento, C.: Speed estimation for induction motor using neural networks method. IEEE Latin America Transactions (Revista IEEE America Latina) 11(2), 768–778 (2013)CrossRefGoogle Scholar
  8. 8.
    Holtz, J.: Methods for speed sensorless control of AC drives. IEEE 1, 21–29 (1998)Google Scholar
  9. 9.
    Holtz, J.: Sensorless control of induction motor drives. Proceedings of the IEEE 90, 1359–1394 (2002)CrossRefGoogle Scholar
  10. 10.
    Karanayil, B., Rahman, M., Grantham, C.: Online stator and rotor resistance estimation scheme using artificial neural networks for vector controlled speed sensorless induction motor drive. IEEE Trans. Ind. Electronics 54, 167–176 (2007)CrossRefGoogle Scholar
  11. 11.
    Maiti, S., Verma, V., Chakraborty, C., Hori, Y.: An adaptive speed sensorless induction motor drive with artificial neural network for stability enhancement. IEEE Transactions on Industrial Informatics 8(4), 757–766 (2012)CrossRefGoogle Scholar
  12. 12.
    Niasar, A.H., Khoei, H.R.: Sensorless direct power control of induction motor drive using artificial neural network. Advances in Artificial Neural Systems, 1–9 (2015)Google Scholar
  13. 13.
    Orlowska-Kowalska, T., Kowalski, C.T.: Neural network application for flux and speed estimation in the sensorless induction motor drive. In: Proc. Of ISIE 1997, pp. 1253–1258. IEEE (1997)Google Scholar
  14. 14.
    Ponce, P., Molina, A., Tellez, A.: Neural network and fuzzy logic in a speed close loop for DTC induction motors. In: International Caribbean Conference on Devices, Circuits and Systems (ICCDCS), pp. 1–7, April 2014Google Scholar
  15. 15.
    Santos, T.H., Goedtel, A., Silva, S.A.O., Suetake, M.: Speed estimator in closed-loop scalar control using neural networks. In: International Conference on Electrical Machines (ICEM), pp. 2570–2576, September 2014Google Scholar
  16. 16.
    Simoes, K., Bose, B.: Estimation of feedback signals for a vector controlled induction motor drive. IEEE Trans. on Industry Application, 629–639 (1995)Google Scholar
  17. 17.
    Sun, X., Chen, L., Yang, Z., Zhu, H.: Speed-sensorless vector control of a bearingless induction motor with artificial neural network inverse speed observer. IEEE/ASME Transactions on Mechatronics 18(4), 1357–1366 (2013)CrossRefGoogle Scholar
  18. 18.
    Ufnalski, B.: Speed estimation in rotating reference frame. MATLAB Central (2014). www.mathworks.com/matlabcentral/fileexchange/48390-speed-estimation-in-rotating-reference-frame
  19. 19.
    Ufnalski, B.: Speed-sensorless induction motor drive. MATLAB Central (2014). www.mathworks.com/matlabcentral/fileexchange/48012-speed-sensorless-induction-motor-drive
  20. 20.
    Zaky, M., Khater, M.M., Shokralla, S., Yasin, H.A.: Wide-speed-range estimation with online parameter identification schemes of sensorless induction motor drives. IEEE Trans. Ind. Electronics 56, 1699–1707 (2009)CrossRefGoogle Scholar
  21. 21.
    Zaky, M., Khater, M.M., Yasin, H., Shokralla, S.: Very low speed and zero speed estimations of sensorless induction motor drives. Electric Power Systems Research 80, 143–151 (2010)CrossRefGoogle Scholar
  22. 22.
    Zhao, L., Huang, J., Liu, H., Li, B., Kong, W.: Second-order sliding-mode observer with online parameter identification for sensorless induction motor drives. IEEE Trans. Ind. Electronics 61, 5280–5289 (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Bartlomiej Beliczynski
    • 1
    Email author
  • Lech M. Grzesiak
    • 1
  • Bartlomiej Ufnalski
    • 1
  1. 1.Institute of Control and Industrial Electronics, Faculty of Electrical EngineeringWarsaw University of TechnologyWarsawPoland

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