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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 431734, 10 pages
Research Article

Design and Implementation of Recursive Model Predictive Control for Permanent Magnet Synchronous Motor Drives

National Engineering Technology Research Center of Electric Power Conversion & Control, Hunan University, Changsha, Hunan 410082, China

Received 25 December 2014; Revised 5 April 2015; Accepted 9 April 2015

Academic Editor: Xinggang Yan

Copyright © 2015 Xuan Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In order to control the permanent-magnet synchronous motor system (PMSM) with different disturbances and nonlinearity, an improved current control algorithm for the PMSM systems using recursive model predictive control (RMPC) is developed in this paper. As the conventional MPC has to be computed online, its iterative computational procedure needs long computing time. To enhance computational speed, a recursive method based on recursive Levenberg-Marquardt algorithm (RLMA) and iterative learning control (ILC) is introduced to solve the learning issue in MPC. RMPC is able to significantly decrease the computation cost of traditional MPC in the PMSM system. The effectiveness of the proposed algorithm has been verified by simulation and experimental results.