대한전기학회논문지:시스템및제어부문D (The Transactions of the Korean Institute of Electrical Engineers D)

대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

SPMSM 드라이브의 속도 센서리스를 위한 하이브리드 지능제어

Hybrid Intelligent Control for Speed Sensorless of SPMSM Drive

  • 이정철 (순천대 공대 정보통신공학부) ;
  • 이홍균 (순천대 공대 정보통신공학부) ;
  • 정동화 (순천대 공대 정보통신공학부)
  • 발행 : 2004.10.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

This paper is proposed a hybrid intelligent controller based on the vector controlled surface permanent magnet synchronous motor(SPMSM) drive system. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of SPMSM using neural network-fuzzy(NNF) control and speed estimation using artificial neural network(ANN) Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the theoretical analysis as well as the simulation results to verify the effectiveness of the new method.

키워드

참고문헌

  1. A. B. Kulkarni and M. Ehsani, 'A novel position sensor elimination technique for interior permanent magnet synchronous motor,' IEEE IAS Conf. Rec. Meet., pp. 773-779, 1989 https://doi.org/10.1109/IAS.1989.96735
  2. A. P. Alves and S. Sathiakumar, 'Brushless permanent magnet motor position estimator,' IEEE IECON Conf. Rec. Meet., vol. 2, pp. 808-813, 1995 https://doi.org/10.1109/IECON.1995.483832
  3. D. Antic, J. B. Klaassens and W. Deleroi, 'Side effects in low speed AC drives,' IEEE PESC '94 Rec., pp. 998-1002, 1994 https://doi.org/10.1109/PESC.1994.373802
  4. M. Schroedl, 'Sensorless control of AC machines at low speed and standstill based on the 'INFORM' method.' in Conf. Red. IEEE-lAS Annu. Meeting, Vol. 1, 1996, pp 270-277 https://doi.org/10.1109/IAS.1996.557028
  5. F. Profumo, G. Griva, C. Ilas, R. Magureanu and P. Vranka, 'A unitary approach to speed sensorless induction motor field oriented drive based on various model reference schemes,' IEEE IAS Conf. Rec. Ann. Meet., pp. 1594-1599, 1996 https://doi.org/10.1109/IAS.1996.559281
  6. R. Dhaouadi, N. Mohan and L. Norum, 'Design and implementation of an extended kalman filter for the state estimation of a permanent magnet synchronous motor,' IEEE Trans. on PE, Vol. 6, No.3, pp. 491-497, 1991 https://doi.org/10.1109/63.85891
  7. Q. Li, 'Theory, design and application of adaptive control systems,' Science Press, Beijing, 1990
  8. K.J. Astron and B. Wittenmark, 'Adaptive control,' Addison-Wesley, 1989
  9. D. H. Chung, 'Fuzzy control for high performance vector control of PMSM drive system,' KIEE, Vol. 47, No. 12, pp, 2171-2180, 1998
  10. K. S. Narendra and K. Parthasarthy, 'Identification and control of dynamical system using neural network,' IEEE Trans. Neural Networks, Vol. 1, No. 1, pp. 4-27, 1990 https://doi.org/10.1109/72.80202
  11. Cybenko, 'Approximations by superposition of a sigmoidal function,' Mathematics of Contr., Signals and Syst., vol. 2, pp. 303-314, 1989 https://doi.org/10.1007/BF02551274
  12. A. K. Toh, E. P. Nowicki and F. Ashrafzadeh, 'A flux estimator for field oriented control of an induction motor using an artificial neural network,' IEEE IAS Conf. Rec. Ann. Meet., Vol. 1, pp. 585-592, 1994 https://doi.org/10.1109/IAS.1994.345461
  13. M. G. Simoes and B. K. Bose, 'Neural network based estimation of feedback signals for a vector controlled induction motor drive,' IEEE Trans. IA, Vol. 31, No.3, pp. 620-629, 1995 https://doi.org/10.1109/28.382124
  14. M. T. Wishart and R. G. Harley, 'Identification and control of induction machines using neural networks,' IEEE Trans. IA, Vol. 31, No.3, pp. 612-619, 1995 https://doi.org/10.1109/28.382123
  15. I. J. Leontaritis and S. A. Billings, 'Input-output parametric models for nonlinear systems,' Int. J. Contr., Vol. 41, pp. 303-344, 1985 https://doi.org/10.1080/0020718508961129