The Transactions of the Korean Institute of Electrical Engineers B (대한전기학회논문지:전기기기및에너지변환시스템부문B)

The Korean Institute of Electrical Engineers (대한전기학회)
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Simple Al Robust Digital Position Control of PMSM using Neural Network Compensator

신경망 보상기를 이용한 PMSM의 간단한 지능형 강인 위치 제어

  • Published : 2000.08.01
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Abstract

A very simple control approach using neural network for the robust position control of a Permanent Magnet Synchronous Motor(PMSM) is presented. The linear quadratic controller plus feedforward neural network is employed to obtain the robust PMSM system approximately linearized using field-orientation method for an AC servo. The neural network is trained in on-line phases and this neural network is composed by a feedforward recall and error back-propagation training. Since the total number of nodes are only eight, this system can be easily realized by the general microprocessor. During the normal operation, the input-output response is sampled and the weighting value is trained multi-times by error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. In addition, the robustness is also obtained without affecting overall system response. This method is realized by a floating-point Digital Signal Processor DS1102 Board (TMS320C31).

Keywords

References

  1. Paul C. Krause, Analysis of Electric Machinery, McGraw-Hill, 1984
  2. K. Furuta, K. Kosuge, and H. Kobayyashi, 'VSS-Type Self-Tuning Control of Direct-Drive Motor', Proc. of IECON 89, pp. 281-286, 1989 https://doi.org/10.1109/IECON.1989.69646
  3. P. Werbos, 'Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Sciences', PhD Thesis, Harvard, Cambridge, MA, August, 1974
  4. Chen , F. 'Back-Propagation Neural Networks for Nonlinear Self-Tuning Adaptive Control', IEEE Control System Magazine, April, 1990 https://doi.org/10.1109/37.55123
  5. Jong-Sun Ko and Myung-Joong Youn, 'Robust Digital Position Control of BLDD Motors using Neural Network with State Feedback,' Proc. of the 3rd. International Workshop on Advanced Motion Control, pp. 852-861, March, 1994
  6. Jong-Sun Ko, Sung-Koo Youn, and Bimal K. Bose, 'A Study on Adaptive Load Torque Observer for Robust Precision Position Control of BLDC Motor' Proc. of the 25th Annual Conference of the IEEE Industrial Electronics Society(IECON'99), pp. 1091-1096, October, 1999 https://doi.org/10.1109/IECON.1999.819360
  7. D.W. Novotny and R.D.Lorentz, Introduction to Field Orientation and High Performance AC Drives, IAS-Tutorial Course, 1988
  8. Arthur E.Bryson JR and David G.Luenberger 'The Synthesis of Regulator Logic using State- Variable Concept', IEEE Proceedings, vol. 58, pp. 1803-1811, 1970
  9. J. S. Ko, J. H. Lee, S. K. Chung, and M. J. Youn, 'A Robust Digital Position Control of Brushless DC Motor with Dead Beat Load Torque Observer,' IEEE Trans. Ind. Electron., vol. IE-40, pp. 512-520, 1993 https://doi.org/10.1109/41.238020
  10. J. H. Lee, J. S. Ko, S. K. Chung, D. S. Lee, J. J. Lee, and M. J. Youn, 'Continuous Variable Controller for BLDDSM Position Control with Prescribed Tracking Performance,' IEEE Transaction on Industrial Electronics, vol. 41, no. 5, pp. 483-491, October 1994 https://doi.org/10.1109/41.315266
  11. K. J. Astrom and B. Wittenmark, Computer controlled system, Prentice Hall, 1984
  12. Hornick K., Stinchcombe M., and White H., 'Multi-layer Feedforward Networks are Universal Approximators', Neural Networks, Vol. 2, 1989 https://doi.org/10.1016/0893-6080(89)90020-8