Volume 5, Issue 1 (March 2009)                   IJEEE 2009, 5(1): 60-66 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
K. Malekian, J. Milimonfared, B. Majidi. Performance Improvement of Direct Torque Controlled Interior Permanent Magnet Synchronous Motor Drives Using Artificial Intelligence . IJEEE 2009; 5 (1) :60-66
URL: http://ijeee.iust.ac.ir/article-1-116-en.html
Performance Improvement of Direct Torque Controlled Interior Permanent Magnet Synchronous Motor Drives Using Artificial Intelligence
K. Malekian , J. Milimonfared , B. Majidi
Abstract:   (10933 Views)
The main theme of this paper is to present novel controller, which is a genetic based fuzzy Logic controller, for interior permanent magnet synchronous motor drives with direct torque control. A radial basis function network has been used for online tuning of the genetic based fuzzy logic controller. Initially different operating conditions are obtained based on motor dynamics incorporating uncertainties. At each operating condition, a genetic algorithm is used to optimize fuzzy logic parameters in closed-loop direct torque control scheme. In other words, the genetic algorithm finds optimum input and output scaling factors and optimum number of membership functions. This optimization procedure is utilized to obtain the minimum speed deviation, minimum settling time, zero steady-state error. The control scheme has been verified by simulation tests with a prototype interior permanent magnet synchronous motor.
Keywords: Direct Torque Control , Field Weakening , Interior Permanent Magnet Synchronous Motor , Maximum Torque per Ampere
Full-Text [PDF 177 kb]   (4617 Downloads)    
Type of Study: Research Paper |
Received: 2009/03/16 | Revised: 2009/03/16 | Accepted: 2009/03/16
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.