Home            Contact us            FAQs
    
      Journal Home      |      Aim & Scope     |     Author(s) Information      |      Editorial Board      |      MSP Download Statistics

     Research Journal of Applied Sciences, Engineering and Technology


Position Servo Control for a Direct-Drive Actuator Based on Genetic Algorithm

1Baifen Liu and 2Ying GAO
1School of Electrical and Electronic Engineering
2School of Basic Sciences, East China Jiaotong University, Nanchang, China
Research Journal of Applied Sciences, Engineering and Technology  2013  23:5359-5364
http://dx.doi.org/10.19026/rjaset.5.4201  |  © The Author(s) 2013
Received: August 11, 2012  |  Accepted: September 17, 2012  |  Published: May 28, 2013

Abstract

A novel position control strategy for a Brushless DC motor (BLDC) drive is proposed in this paper. Brushless DC motor, which is widely used in the field of Direct Drive servo Actuator (DDA) with superior performance, possesses fast transient response and high accuracy. Nevertheless, there are such uncertainties as unpredictable flow torques and estimated errors of the BLDC model in this system, which may influence the accuracy and the rapid response of the control. So in this paper, genetic algorithm is applied to the position loop. Simultaneously, in order to improve the rapidness of the whole system, position and velocity double closed-loop system is compared with position and current double closed-loop system. Experimental results validate the scheme proposed can attenuate the influences by the uncertainties of the model sharply. The genetic algorithm used in the position loop can ensure the system's stability and the accuracy of the position response. While tracking the same step response the step rise time of the double closed loop structure of the position and current reduced more than 25% compared with that of the double closed loop structure of the position and velocity.

Keywords:

Brushless DC motor (BLDC), Digital Signal Processor (DSP), Direct-Drive Actuator (DDA), doubles loops, Genetic Algorithm (GA), robustness,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
Submit Manuscript
   Information
   Sales & Services
Home   |  Contact us   |  About us   |  Privacy Policy
Copyright © 2024. MAXWELL Scientific Publication Corp., All rights reserved