By Topic

GA-based iterative learning control applications to the weighing system of large asphalt mixing plant

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

7 Author(s)
S. L. Song ; Institute of Engineering, University of Sci. & Tech., Nanjing, Jiangsu Province, China ; J. Yan ; Q. Zhang ; Q. C. Zhou
more authors

In large asphalt mixing plant, the matching accuracy and the measuring precision of the material are critical to the final asphalt mixture. This paper firstly deducts the mathematical model of the weighing system of large asphalt mixing plant. Then a genetic algorithms based iterative learning controller for the weighing system is designed. Finally, computer simulation and experimental study are performed. The results demonstrate well in terms of convergent speed and weighing precision. The proposed method could meet the need of the weighing system very well.

Published in:

2008 IEEE International Conference on Mechatronics and Automation

Date of Conference:

5-8 Aug. 2008