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Journal of Control Science and Engineering
Volume 2015, Article ID 353712, 6 pages
http://dx.doi.org/10.1155/2015/353712
Research Article

Predictive Variable Gain Iterative Learning Control for PMSM

1The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
2School of Energy and Power Engineering, North China Electric Power University, Baoding 071003, China

Received 10 June 2015; Revised 2 September 2015; Accepted 11 October 2015

Academic Editor: Zoltan Szabo

Copyright © 2015 Huimin Xu 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.

Abstract

A predictive variable gain strategy in iterative learning control (ILC) is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.