Direct Torque Control System of a Reluctance Synchronous Motor Using a Neural Network

Min-Huei Kim

Direct Torque Control System of a Reluctance Synchronous Motor Using a Neural Network

Min-Huei Kim

Vol. 5, No. 1, pp. 36-44, Jan. 2005

10.6113/JPE.2005.5.1.36

Direct torque control

Neural Network

Reluctance Synchronous Motor

High Performance Control

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Abstract

This paper presents an implementation of high performance control of a reluctance synchronous motor (RSM) using a neural network with a direct torque control. The equivalent circuit in a RSM, which considers iron losses, is theoretically analyzed. Also, the optimal current ratio between torque current and exiting current is analytically derived. In the case of a RSM, unlike an induction motor, torque dynamics can only be maintained by controlling the flux level because torque is directly proportional to the stator current. The neural network is used to efficiently drive the RSM. The TMS320C31 is employed as a control driver to implement complex control algorithms. The experimental results are presented to validate the applicability of the proposed method. The developed control system shows high efficiency and good dynamic response features for a 1.0 [kW] RSM having a 2.57 ratio of d/q.

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Cite this article

[IEEE Style]

M. Kim, "Direct Torque Control System of a Reluctance Synchronous Motor Using a Neural Network," Journal of Power Electronics, vol. 5, no. 1, pp. 36-44, 2005. DOI: 10.6113/JPE.2005.5.1.36.

[ACM Style]

Min-Huei Kim. 2005. Direct Torque Control System of a Reluctance Synchronous Motor Using a Neural Network. Journal of Power Electronics, 5, 1, (2005), 36-44. DOI: 10.6113/JPE.2005.5.1.36.