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Mathematical Problems in Engineering
Volume 2014, Article ID 321892, 7 pages
http://dx.doi.org/10.1155/2014/321892
Research Article

Sensorless Speed Control of Permanent Magnet Synchronous Motors by Neural Network Algorithm

Department of Electrical Engineering, Southern Taiwan University of Science and Technology, 1 Nan-Tai Street, Yung Kang District, Tainan City 710, Taiwan

Received 20 August 2014; Accepted 8 September 2014; Published 25 September 2014

Academic Editor: Stephen D. Prior

Copyright © 2014 Ming-Shyan Wang 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

The sliding mode control has the merits with respect to the variation of the disturbance and robustness. In this paper, the sensorless sliding-mode observer with least mean squared error approach for permanent magnet synchronous motor (PMSM) to detect the rotor position by counter electromotive force and then compute motor speed is designed and implemented. In addition, the neural network control is also used to compensate the PI gain tuning to increase the speed accuracy without regarding the errors of the current measurement and motor noise. In this paper, a digital signal processor TMS320F2812 utilizes its high-speed ADC module to get current feedback information and thus to estimate the rotor position and takes advantage of the built-in modules to achieve SVPWM current control so that the senseless speed control will be accomplished. The correctness and effectiveness of the proposed control system will be verified from the experimental results.