The Transactions of The Korean Institute of Electrical Engineers (전기학회논문지)

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

Neural Network Parameter Estimation of IPMSM Drive using AFLC

AFLC를 이용한 IPMSM 드라이브의 NN 파라미터 추정

  • Received : 2010.09.10
  • Accepted : 2010.10.28
  • Published : 2011.02.01
Download PDF
⟨ Previous Next ⟩

Abstract

A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and stator resistance and adaptive fuzzy learning contrroller(AFLC) for speed control in IPMSM Drives. AFLC is chaged fuzzy rule base by rule base modifier for robust control of IPMSM. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator and AFLC is confirmed by comparing to conventional algorithm.

Keywords

References

  1. G. R. Slemon, "Electric machines and drives," Reading, MA: Addison-Wesley, 1992.
  2. T. J. E. Miller, "Brushless permanent magnet and reluctance motor drives," Oxford, U. K.: Clarendon, 1989.
  3. C. M. Ong, "Dynamic simulation of elecctric machinery using Matlab/simulink," Upper Saddle River, NJ: Prentice-Hall, 1998.
  4. M. A. Rahman and M. A, Hoque, "On-line adaptive artificial neural network based vector control of permanent magnet synchronous motors," IEEE Trans. EC, vol. 13, pp. 311-318, 1998.
  5. B. K. Bose, "High Performance control and estimation in ac drives," in Proc. IEEE IECON'97, vol. 2, pp. 377-385, 1997.
  6. P. Pillay and R. Krishnan, "Control characteristics and speed controller design for a high performance permanent magnet synchronous motor drive," IEEE Trans. PE, vol. 5, pp. 151-159, 1990.
  7. N. Matsui and H. Ohashi, "DSP based adaptive control of brushless motor," IEEE IAS, Conf. Rec. Annu. Meet., pp. 375-380, 1988.
  8. K. Ohshi, N. Matsui and Y. Hori, "Estimation, identification and sensorless control system," Proceedings of IEEE, vol. 82, no. 8, pp. 1253-1265, 1994. https://doi.org/10.1109/5.301687
  9. K. H. Kim, et al., "Parameter estimation and control of permanent magnet synchronous motor drive using model reference adaptive technique," IEEE IAS, Conf. Rec. Annu. Meet., pp. 387-392, 1995.
  10. S. Weisgerber, et al., "Estimation of permanent magnet synchronous motor parameters," IEEE IAS, Conf. Rec. Annu. Meet., pp. 29-34, 1997.
  11. J. S. Ko, J. S. Choi, K. T. Park, B. S. Park and D. H. Chung, "Development of HBPI Controller for High Performance Control of IPMSM Drive", pp. 368-372, ICPE'07, 2007.
  12. J. S. Choi, J. S. Ko, J. H. Lee and D. H. Chung, "Speed control of IPMSM drive using neural network PI controller," CEE 06, pp. 102, 2006.
  13. J. S. Choi, J. S. Ko, J. H. Lee and D. H. Chung, "Maximum torque control of IPMSM drive with ALC-FNN controller," ICEE 06, pp. 101, 2006.
  14. J. S. Ko, J. S. Choi, J. H. Lee and D. H. Chung, "Maximum torque control of IPMSM drive with hybrid artificial intelligent controller," Proceeding of ICMATE'06, Session B1, pp. 177-182, 2006.
  15. H. G. Lee, S. M. Nam, J. S. Ko, J. S. Choi, J. C. Lee and D. H. Chung, "The speed control and estimation of IPMSM using adaptive FNN and ANN," ICCAS 2005, p. 134, 2005.
  16. J. Holtz and L. Springob, "Identification and compensation of torque ripple in high precision permanent magnet motor drives," IEEE Trans. IE, vol. 43, no. 2, pp. 309-330, 1996.