Paper Title:
Position Sensorless Control Based on Augmented Extended Kalman Filter for Permanent Magnet Linear Synchronous Motor
  Abstract

In order to achieve position sensorless control for PMLSM drive system, speed and position of the motor must be estimated. A novel sensorless position and speed estimation algorithm was designed for PMLSM drive by measuring terminal voltages and currents. That was state augmented extended Kalman filter (AEKF) estimation method. The resistance of the motor was augmented to the state variable. Then, the speed, position and the resistance were estimated simultaneously through extended Kalman filter (EKF). The influence of the resistance on the state estimation results could be reduced. As well as giving a detailed explanation of the new algorithm, experimental results were presented. It shows that the AEKF is capable of estimating system states accurately and reliability, and the proposed sensorless control system has a good dynamic response.

  Info
Periodical
Chapter
Chapter 6: Power and Control Electronics
Edited by
Xingui He, Ertian Hua, Yun Lin and Xiaozhu Liu
Pages
350-354
DOI
10.4028/www.scientific.net/AMM.88-89.350
Citation
H. C. Lu, M. Jiang, L. S. Wei, B. Y. Liu, "Position Sensorless Control Based on Augmented Extended Kalman Filter for Permanent Magnet Linear Synchronous Motor", Applied Mechanics and Materials, Vols. 88-89, pp. 350-354, 2011
Online since
August 2011
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Price
$32.00
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