Application of neural network in suppressing mechanical vibration of a permanent magnet linear motor

被引：28

作者：

Yousefi, Hassan ^{[1
]}

Hirvonen, Markus ^{[1
]}

Handroos, Heikki ^{[1
]}

Soleymani, Azita ^{[2
]}

机构：

[1] Lappeenranta Univ Technol, Dept Mech Engn, Inst Mechatron & Virtual Engn, FIN-53851 Lappeenranta, Finland

[2] Lappeenranta Univ Technol, Dept Chem Technol, FIN-53851 Lappeenranta, Finland

来源：

CONTROL ENGINEERING PRACTICE | 2008年 / 16卷 / 07期

关键词：

neural networks; genetic algorithms; velocity control; linear motors; Kalman filters;

D O I：

10.1016/j.conengprac.2007.08.003

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this study, a recurrent neural network compensator for suppressing inechanical vibration in a permanent magnet linear synchronous motor (PMLSM) is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system, respectively. The proposed control method is firstly designed by using a nonlinear simulation model built in Matlab Sitmulink and then implemented in a practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. (C) 2007 Elsevier Ltd. All rights reserved.

引用

页码：787 / 797

页数：11

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