Control of Magnetic Flywheel System by Neuro-Fuzzy Logic

뉴로-퍼지를 이용한 플라이휠 제어에 관한 연구

  • 양원석 (전남대학교 기계공학과) ;
  • 김영배 (전남대학교 기계공학과)
  • Published : 2005.06.01

Abstract

Magnetic flywheel system utilizes a magnetic bearing, which is able to support the shaft without mechanical contacts, and also it is able to control rotational vibration. Magnetic flywheel system is composed of position sensors, a digital controller, actuating amplifiers, an electromagnet and a flywheel. This work applies the neuro-fuzzy control algorithm to control the vibration of a magnetic flywheel system. It proposes the design skill of an optimal controller when the system has structured uncertainty and unstructured uncertainty, i.e. it has a difficulty in extracting the exact mathematical model. Inhibitory action of vibration was verified at the specified rotating speed. Unbalance response, a serious problem in rotating machinery, is improved by using a magnetic bearing with neuro-fuzzy algorithm.

Keywords

References

  1. Salm,J.R., 'Active Electromagnetic Suspension of an Elastic Rotor: Modeling, Control, And Experimental Results,' ASME J, of Vibration, Acoustics, Stress, and Reliability in Design, Vol.110, pp. 493-501, 1988 https://doi.org/10.1115/1.3269556
  2. Okada, Y. and Saitoh, T., 'Vibration Control of Flexible Rotor Supported by Inclination Control Magnet Bearings,' Proceeding of the 1999 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp.788-793, 1999 https://doi.org/10.1109/AIM.1999.803273
  3. Oh, S.K. and Pedrycz, W., 'Identification of Fuzzy Systems by means of an Auto-Tuning Algorithm and Its Application to Nonlinear Systems,' Fuzzy Sets and Systems, 1999
  4. Kim, Y.B., Yi, H.B. and Lee, B.K., 'Design and Application of Magnetic Damper for Reducing Rotor Vibration,' KSME A, Vol.24, No.2, pp. 355-361, 2000
  5. Yi, H.B. and Kim, Y.B., 'A Study of Rotor Vibration Reduction using Fuzzy Magnetic Damper System,' KSME A, Vol.25, No.4, pp. 748-755, 2001
  6. Lum, K.Y., Coppola, V. and Bernstein, D.S., 'Adaptive Virtual Autobalancing for a Rigid Rotor with Unknown Mass Imbalance Supported by Magnetic Bearings,' ASME J, of Vibration and Acoustics, Vol.120, pp. 4557-4570, 1998
  7. Lum, K.Y., Bernstein, D.S. and Coppola, V., 'Adaptive Autocountering Control for an Active Magnetic Bearing Supporting a Rotor with Unknown Mass Imbalance,' IEEE Transactions on Control System Technology, Special Issue on Magnetic Bearing Control, 1996
  8. Hwang, H.S., Oh, S.K. and Woo, B.K., 'Synthesis of Genetic Algorithm and Fuzzy Inference system,' Journal of the KIEE, Vol.41, No.9, pp. 1095-1103, 1992
  9. Jang, J., Roger, S. and Gulley, N., Fuzzy, J. and Zamudia, C., 'Operation Planning Based on Cutting Process Model,' Annals of the CIRP, Vol. 39, pp. 517-521, 1990 https://doi.org/10.1016/S0007-8506(07)61110-X
  10. Paul, Y. K., 'Rotor Dynamics of the Present Condition and Problems,' KSNVE Journal of the Springtime Scientific Conference, pp. 11-19, 1997
  11. Ahn, Sang Chul and Kwon, Wook Hyun, 'A Construction of Fuzzy Controler using Learning,' J. of the KACC, pp. 484-489, 1992
  12. Jeon, Yong Sung, Park, Sang Bae and Lee, Kyun Kyung, 'Identification of Fuzzy Rule and Implementation of Fuzzy controller using Neural Network,' J. of the KACC, pp.856-860, 1991
  13. Kim, Hyung Tae, 'Study of Fuzzy Logic Controller for Reducing Rotor Vibration,' M.S. Thesis Chonnam University, 1998
  14. Oh, S.K., Ahn, T.C., Hwang, H.S., Park, J.J. and Woo, K.B., 'Design of a Hybrid Fuzzy Controller with the Optimal Auto-tuning Method,' Journal of Control, Automation and Systems Engineering, Vol.1 , No.1, pp. 63-70, 1995
  15. Park, C.S., Oh, S.K. and Pedrycz, W., 'Fuzzy Identification by means of Auto-Tuning Algorithm and Weighting Factor,' AFFS, pp. 701-706, 1998