DocumentCode
504711
Title
Evolutionary modeling of a process system
Author
Hayashi, Kayoko ; Kawada, Kazuo ; Yamamoto, Toru
Author_Institution
Dept. of Technol. & Inf. Educ., Hiroshima Univ., Hiroshima, Japan
fYear
2009
fDate
18-21 Aug. 2009
Firstpage
3268
Lastpage
3273
Abstract
In this paper, a genetic algorithm (GA) modeling system is proposed. The GA is an evolutionary computational method that simulates the mechanisms of heredity or evolution of living things, and it is utilized in optimization and in searching for optimized solutions. Most process systems have nonlinearities, so it is necessary to anticipate exactly such systems. However, it is difficult to make a suitable model for nonlinear systems, because most nonlinear systems have a complex structure. Therefore the newly proposed method of modeling for nonlinear systems uses GA. Then according to the newly proposed scheme, the optimal structure and parameters of the nonlinear model are automatically generated.
Keywords
control nonlinearities; delays; genetic algorithms; nonlinear control systems; parameter estimation; search problems; complex structure; control nonlinearity; evolutionary computational method; genetic algorithm modeling system; nonlinear system modeling; optimal structure; optimization; parameter estimation; process system; search problem; time delay; Computational modeling; Genetic algorithms; Nonlinear systems; Optimization methods; GA; Nonlinear System; System Identification; the Evolutionary Computation;
fLanguage
English
Publisher
ieee
Conference_Titel
ICCAS-SICE, 2009
Conference_Location
Fukuoka
Print_ISBN
978-4-907764-34-0
Electronic_ISBN
978-4-907764-33-3
Type
conf
Filename
5334386
Link To Document