Sensorless control of the permanent magnet synchronous motor using neural networks

Author

Ünal, Sencer ; Özdemír, Mehmet

Author_Institution

Dept. of Electr. & Electron. Eng., Firat Univ., Elazig

fYear

2007

fDate

10-12 Sept. 2007

Firstpage

638

Lastpage

642

Abstract

In this paper, a neural network based rotor position control and speed estimation method for permanent magnet synchronous motor (PMSM) is proposed. The proposed method has three recurrent neural networks. They are used for estimating stator current, rotor speed, and rotor position angle. Each of them is trained in two steps: off-line training for learning dynamic of PMSM and on-line training for realizing parameter adaptation of PMSM. Sensorless control of the permanent magnet synchronous motor using neural networks is simulated in Matlab/Simulink.

Keywords

angular velocity control; control engineering computing; machine control; matrix algebra; neural nets; permanent magnet motors; power engineering computing; sensors; synchronous motors; Matlab-Simulink; neural networks; off-line training; on-line training; parameter adaptation; permanent magnet synchronous motor; rotor position control; sensorless control; speed estimation method; Magnetic sensors; Mathematical model; Neural networks; Permanent magnet motors; Phase estimation; Recurrent neural networks; Rotors; Sensorless control; Stators; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Machines and Power Electronics, 2007. ACEMP '07. International Aegean Conference on

Conference_Location

Bodrum

Print_ISBN

978-1-4244-0890-0

Electronic_ISBN

978-1-4244-0891-7

Type

conf

DOI

10.1109/ACEMP.2007.4510581

Filename

4510581