A Vector-Controlled PMSM Drive with a Continually On-Line Learning Hybrid Neural-Network Model-Following Speed Controller

  • EI-Sousy Fayez F. M. (Electronics Research Institute (ERI) Power Electronics & Energy Conversion Department)
  • Published : 2005.04.01

Abstract

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

Keywords

References

  1. P.C. Krause, Analysis of Electric Machinery, New York, McGraw Hill, 1986
  2. B. K. Bose, Modern Power Electronics and AC Drives. Prentice Hall, Upper Saddle River, 2002
  3. Peter Vas, Vector Control of AC Machines, Oxford: Clarendon Press, 1990
  4. Ned Mohan, Advanced Electric Drives: Analysis, control, and Modeling using Simulink, MNPERE Press, USA, 2001
  5. Fayez F. M. EI-Sousy, 'Design and Implementation of 2DOF I-PD Controller for Indirect Field Orientation Control Induction Machine Drive System', ISlE 2001 IEEE International Symposium on Industrial Electronics, Pusan, Korea, June 12-16, pp. 1112-1118, 2001
  6. C. M. Liaw, 'Design of a two-degrees-of-freedom controller for motor drives', IEEE Trans. Automatic Control, Vol. AC-37, No.4, Aug./Sept., pp. 1215-1220, 1992
  7. Fayez F. M. EI-Sousy and Maged N. F. Nashed, 'Robust Fuzzy Logic Current and Speed Controllers for Field-Oriented Induction Motor Drive', The Korean Institute of Power Electronics (KIPE), Journal of Power Electronics (JPE), Vol. 3, No.2, pp. 115-123, April 2003
  8. M. A EI-Sharkawy, 'Neural network application to high performance electric drive system', Proceeding of ICEON'95, pp. 44-496, 1995
  9. Fayez F. M. EI-Sousy and M. M. Salem, 'Simple Neuro-Controllers for Field Oriented Induction Motor Servo Drive System', The Korean Institute of Power Electronics (KIPE), Journal of Power Electronics (JPE), Vol. 4, No. 1, , pp. 28-38, January 2004
  10. K. S. Narenda and K. Parthasarathy, 'Identification and control of dynamical systems using neural networks', IEEE Trans., Neural Network, NN-1, pp. 4-27,1990
  11. T. Fukuda and T. Shibata, 'Theory and applications of neural networks for industrial control systems', IEEE Trans., Ind. Electr., IE-39, pp. 472-491,1992
  12. Yang Yi, D. Mahinda Vilathgamuwa and Azizur Rahman, 'Implementation of an Artificial-Neural-Network-Based Real-Time Adaptive Controller for an Interior Permanent-Magnet Motor Drive', IEEE Trans., Ind. Applic., IA-39, No. 1, pp. 96-104, 2003
  13. Faa-Jeng and Chih-Hong Lin, 'A Permanent-Magnet Synchronous Motor Servo Drive Using Self-Constructing Fuzzy Neural Network Controller', IEEE Trans., Energy Conversion, EC-19, No. 1, pp. 66-72, 2004
  14. Fayez F. M. EI-Sousy and M. M. Salem, 'High Performance Simple Position Neuro-Controller for Field-Oriented Induction Motor Servo Drives', WSEAS Transactions on Systems, Issue 2, Vol. 3, pp. 941-950, April 2004
  15. Fayez F. M. EI-Sousy, 'A High-Performance Induction Motor Drive with 2DOF I-PD Model-Following Speed Controller', The Korean Institute of Power Electronics (KIPE), Journal of Power Electronics (JPE), Vol. 4, No.4, pp. 217-227, October 2004
  16. Matlab Simulink User Guide, The Math Work Inc., 1997
  17. C. M. Ong, Dynamic Simulation of Electric Machinery Using Matlab and Simulink, Printice Hall, 1998