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Real-Time Implementation of Brain Emotional Learning Developed for Digital Signal Processor-Based Interior Permanent Magnet Synchronous Motor Drive Systems

  • Sadeghi, Mohamad-Ali (Dept. of Electrical Eng., Sirjan Branch, Islamic Azad University) ;
  • Daryabeigi, Ehsan (Young Researchers and Elite Club, Najafabad Branch, Islamic Azad University)
  • 투고 : 2013.09.02
  • 발행 : 2014.01.20

초록

In this study, a brain emotional learning-based intelligent controller (BELBIC) is developed for the speed control of an interior permanent magnet synchronous motor (IPMSM). A novel and simple model of the IPMSM drive structure is established with the intelligent control system, which controls motor speed accurately without the use of any conventional PI controllers and is independent of motor parameters. This study is conducted in both real time and simulation with a new control plant for a laboratory 3 ph, 3.8 Nm IPMSM digital signal processor (DSP)-based drive system. This DSP-based drive system is then compared with conventional BELBIC and an optimized conventional PI controller. Results show that the proposed method performs better than the other controllers and exhibits excellent control characteristics, such as fast response, simple implementation, and robustness with respect to disturbances and manufacturing imperfections.

키워드

참고문헌

  1. F. Blaschke, "The principle of field orientation as applied to the new transvector closed-loop control system for rotating-field machines," Siemens Reviews., Vol. 34, pp. 217 220, May 1972.
  2. M. Nasir, M. Uddin, and M. A. Rahman, "High-speed control of ipmsm drives using improved fuzzy logic algorithms", IEEE Trans. on Indus. Electron., Vol. 54, No. 1, pp. 190-199, Feb. 2007. https://doi.org/10.1109/TIE.2006.888781
  3. Utkin, V., Sliding Modes in Control Optimization: Springer Verlag, 1992.
  4. M. F. Rahman, I. Zhong, and K. W. Lim, "A direct torque controlled interior magnet synchronous motor drive incorporating field weakening," IEEE Trans. Ind. Applicat., Vol. 34, pp. 1246-1253, Nov./Dec. 1998. https://doi.org/10.1109/28.738985
  5. M. F. Rahman, M. E. Haque, L. Tang, and L. Zhong, "Problems associated with the direct torque control of an interior permanent-magnet synchronous motor drive and their remedies", IEEE Trans, on Ind. Electron., Vol. 51, No. 4, pp. 799-809, Aug. 2004. https://doi.org/10.1109/TIE.2004.831728
  6. Y. V. S. Reddy, M. V. Kumar, T. B. Reddy, and J. Amarnath, "Direct torque control of induction motor based on state feedback and variable structure fuzzy, controllers," in Proceeding of IEEE Conf., 2006.
  7. M. A. Rahman, M. Vilathgamuwa, M. N. Uddin, and K. J. Tseng, "Nonlinear control of interior permanent magnet synchronous motor," IEEE Trans. Ind. Appl., Vol. 39, No. 2, pp. 408-416, Mar./Apr. 2003. https://doi.org/10.1109/TIA.2003.808932
  8. R. Ortega, P. J. Nicklasson, and G. Espinosa, "Passivity-based control of a class of Blondel-Park transformable electric machines," IEEE Trans. Automat. Contr., Vol.42, pp. 629 - 647, 1997. https://doi.org/10.1109/9.580867
  9. B. K. Bose, "Neural network applications in power electronics and motor drives-An introduction and perspective," IEEE Trans. Ind. Electron, Vol. 54, No. 1, pp. 14-33, Feb. 2007. https://doi.org/10.1109/TIE.2006.888683
  10. T. Orlowska-Kowalska and K. Szabat, "Control of the drive system with stiff and elastic couplings using adaptive neuro-fuzzy approach," IEEE Trans. Ind. Electron. Vol. 54, No. 1, pp. 228-240, Feb. 2007. https://doi.org/10.1109/TIE.2006.888787
  11. M. R. G. Magali, P. E. M. Almeida, and M. G. Simoes, "A comprehensive review for industrial applicability of artificial neural networks," IEEE Trans. Ind. Electron. Vol. 50, No. 3, Jun. 2003.
  12. B. K. Bose, "Expert system, fuzzy logic, and neural network applications in power electronics and motion control," in Proceeding of IEEE, Vol. 82, pp. 1303-1323, Aug. 1994. https://doi.org/10.1109/5.301690
  13. F. F. M. El-Sousy, "Robust recurrent wavelet interval type-2 fuzzy-neural-network control for dsp-based pmsm servo drive systems," Journal of Power Electronics, Vol. 13, No. 1, pp. 139-160, Jan. 2013. https://doi.org/10.6113/JPE.2013.13.1.139
  14. C. Lucas, D. Shahmirzadi, and N. Sheikholeslami, "Introducing BELBIC: brain emotional learning based intelligent control," International Journal of Intelligent Automation and Soft Computing, Vol. 10, No. 1, PP. 11-22, 2004. https://doi.org/10.1080/10798587.2004.10642862
  15. J. Moren and C. Balkenius "A computational model of emotional learning in the amygdala," From animals to animals 6: in Proceedings of the International conference on the simulation of adaptive behavior"
  16. M. R. Jamali, M. Dehyadegari, A. Arami, C. Lucas, and Z. Navabi, "Real-time embedded emotional controller," J. Neural Comput. Appl., Vol. 19, 507, No. 1, pp. 13-19, Feb. 2010. https://doi.org/10.1007/s00521-008-0227-x
  17. M .A. Rahman, R. M. Milasi, C. Lucas, B. N. Arrabi, T. S. Radwan, "Implementation of emotional controller for interior permanent magnet synchronous motor drive," IEEE Trans. Ind. Applicat., Vol. 44, No. 5, pp. 1466-1476, Sep./Oct. 2008. https://doi.org/10.1109/TIA.2008.2002206
  18. G. R. Arab Markadeh, E. Daryabeigi, M. A. Rahman, and C. Lucas," Speed and flux control of induction motors using emotional intelligent controller," IEEE Trans. Ind. Appl. Vol. 47, No. 3, pp. 1-10, May/Jun. 2011. https://doi.org/10.1109/TIA.2011.2173266
  19. E. Daryabeigi, G. Arab Markade, and C. Lucas, "Simultaneously, speed and flux control of a induction motor, with brain emotional learning based intelligent controller (BELBIC)," in Proceeding of IEEE, IEMDC, pp 894 - 901, May. 2009.
  20. T. S. Radwan, M. A. Rahman, A. M. Osheiba, and A. E. Lashine, "Dynamic analysis of a high performance permanent magnet synchronous motor drive," in proceeding IEEE Canadian Conference in Electrical and Computer Engineering, pp. 611-614, 1996.
  21. Wikipedia-BELBIC-http://en.wikipedia.org/wiki/BELBIC, Oc. 6th, 2013.
  22. A. Khodabakhshian, E. Daryabeigi, and M. Moazzam, "A new optimization approach for multi-machine power system stabilizer design using a smart bacteria foraging algorithm," SIMULATION: TSMSI. Vol. 89, No. 9, pp. 1041-1055, 2013. https://doi.org/10.1177/0037549713495741
  23. Matlab, Simulink User Guide The Math works Inc., Natick, MA, 2003.

피인용 문헌

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