DOI QR코드

DOI QR Code

High Performance Speed Control of IPMSM Drive using Recurrent FNN Controller

순환 퍼지뉴로 제어기를 이용한 IPMSM 드라이브의 고성능 속도제어

  • Received : 2011.05.31
  • Accepted : 2011.07.13
  • Published : 2011.09.01

Abstract

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.

Keywords

References

  1. G. R. Slemon, "Electric machines and drives," Addison-Wesley Publication Company, pp. 503-511, 1992.
  2. F. Blaschke, "The principle of field orientation as applied to the new transvector closed-loop control system for rotating-field machines," Siemens Review, vol. 34, pp. 217-220, 1972.
  3. N. Golea, A. Golea and M. Kadjoudj, "Robust MRAC adaptive control of PMSM drive under general parameters uncertainties," IEEE International Conference on Industrial Technology, pp. 1533-1537, 2006.
  4. B. Singh, B. P. Singh and S. Dwivedi, "DSP based implementation of sliding mode speed controller for vector controlled permanent magnet synchronous motor drive," India International Conference on Power Electronics, pp. 22-27, 2006.
  5. Y.A.-R.I. Mohamed, "Adaptive Self-Tuning Speed Control for Permanent-Magnet Synchronous Motor Drive With Dead Time," IEEE Transaction on EC, vol. 21, no. 4, pp. 855-862, 2006.
  6. M. A. Rahman and M. A. Hoque, "On-line self tuning ANN based speed control of a PM DC motor," IEEE/ASME Trans. on Mechatronics, vol. 2, no. 3, pp. 169-178, 1997. https://doi.org/10.1109/3516.622969
  7. M. A. Rahman and Ping Zhou, "Field circuit analysis of brushless permanent magnet synchronous motors," IEEE Trans. on IE, vol. 43, no. 2, pp. 256-267, 1996.
  8. 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.
  9. 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.
  10. J. S. Choi, J. S. Ko, J. H. Lee and D. H. Chung, "Speed control of IPMSM drive using neural network PI controller," ICEE'06, pp. 102, 2006.
  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. M.M.I.Chy, M.N.Uddin, "Development and Implementation of a New Adaptive Intelligent Speed Control for IPMSM Drive", Industry Applications, IEEE Trans, vol. 45, no. 3, pp. 1106-1115, 2009 https://doi.org/10.1109/TIA.2009.2018918