DocumentCode :
2961509
Title :
GA-based iterative learning control applications to the weighing system of large asphalt mixing plant
Author :
Song, S.L. ; Yan, J. ; Zhang, Q. ; Zhou, Q.C. ; Li, W.L. ; Zuo, D.W. ; Xiao, C.Y.
Author_Institution :
Inst. of Eng., Univ. of Sci. & Tech., Nanjing
fYear :
2008
fDate :
5-8 Aug. 2008
Firstpage :
943
Lastpage :
946
Abstract :
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.
Keywords :
asphalt; genetic algorithms; iterative methods; learning systems; mixing; GA-based iterative learning control applications; large asphalt mixing plant; mathematical model; weighing system; Aggregates; Algorithm design and analysis; Asphalt; Computer simulation; Control systems; Genetic algorithms; Mathematical model; Performance analysis; Roads; Weight control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation, 2008. ICMA 2008. IEEE International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
978-1-4244-2631-7
Electronic_ISBN :
978-1-4244-2632-4
Type :
conf
DOI :
10.1109/ICMA.2008.4798885
Filename :
4798885
Link To Document :
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