The EKF Senorless Control Strategy of Permanent Magnet Synchronous Motor Adaptive Backstepping Control System

Article Preview

Abstract:

For the unsatisfactory of the traditional linear control methods, on the basis of the mathematical model of PMSM, a combination of backstepping control method based on the Lyapunov function and adaptive control method is used in the speed control system of PMSM. A method of estimating the rotor position and speed based in extended Kalman filter (EKF) for PMSM is proposed. A simulation model of PMSM using the designed adaptive backstepping controller with EKF is built. The results of simulation using the control method show the preferably dynamic and stable-static performance of the system, and prove its effectiveness.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1166-1172

Citation:

Online since:

December 2012

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] J.Z. Cheng, D.F. Hong, Y.X. Shen. Indirect model reference adaptive control on the permanent magnet synchronous motor speed servo system [J]. Small & Special Machines, 2004, 8: 21-23.

DOI: 10.1109/icems12746.2007.4412099

Google Scholar

[2] P.G. Zhou, P.G. Wang. Real-time nonlinear adaptive back stepping speed control for a PM synchronous motor [J]. Control Engineering Practice, 2005, 13(10): 1259-1269.

DOI: 10.1016/j.conengprac.2004.11.007

Google Scholar

[3] X.Z. Zhang, Y.N. Wang, X.F. Yuan. Adaptive fuzzy sliding-mode control for PM synchronous motor [J]. China Mechanical Engineering, 2010, 2(21): 206-211.

Google Scholar

[4] Y. Li, F.Y. He, S.M. Gu. Study on sliding mode speed control with RBF network approach for PMSM drives[C]. 2009 International Conference on Control and Automation, ICCA2009, Dec. 9-11, 2009. Christchurch, New Zealand.

DOI: 10.1109/icca.2009.5410490

Google Scholar

[5] Z.G. Liu, J.Z. Wang, J.B. Zhao. Neural network adaptive sliding mode control for permanent magnet synchronous motor [J]. Electric Machines and Control, 2009, 13(2): 290-295.

Google Scholar

[6] Z. Wang, B.D. Qu. Application of BP neural network in PMSM [J]. Computer Simulation, 2009, 8: 155-157.

Google Scholar

[7] Y.X. Shen, Z.C. Ji. Passivity-based fuzzy sliding-mode control system and experiment research for permanent magnet synchronous motors [J]. Journal of System Simulation, 2007, 19(17): 4012-4016.

DOI: 10.1007/978-3-540-74282-1_146

Google Scholar

[8] JEAN JACQUES E. SLOTINE, WEIPING LI. Applied nonlinear control [M]. Beijing: Mechanical Industry Press. 2004. 4-11.

Google Scholar

[9] Peroutka Zdenek. Design considerations for senorless control of PMSM drive based on extended kalman filter[C]. 2005 European Conference on Power Electronics and Application. 2005: 1656-1659.

DOI: 10.1109/epe.2005.219469

Google Scholar

[10] P. Borsje, T.F. Chan, Y.K. Wong, et al. A comparative study of Kalman filtering for sensorless control of a permanent magnet synchronous motor drive [C]. 2005 IEEE International Conference on Electric Machines and Drives, 2005: 815-822.

DOI: 10.1109/iemdc.2005.195816

Google Scholar