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Pregled bibliografske jedinice broj: 501622

Optimizing configurable parameters of model structure using genetic algorithms


Ujević Andrijić, Željka; Bolf, Nenad; Rolich Tomislav
Optimizing configurable parameters of model structure using genetic algorithms // TEDI - International Interdisciplinary Journal of Young Scientists from the Faculty of Textile Technology, 1 (2011), 1; 49-54 (podatak o recenziji nije dostupan, članak, znanstveni)


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Naslov
Optimizing configurable parameters of model structure using genetic algorithms

Autori
Ujević Andrijić, Željka ; Bolf, Nenad ; Rolich Tomislav

Izvornik
TEDI - International Interdisciplinary Journal of Young Scientists from the Faculty of Textile Technology (1847-9545) 1 (2011), 1; 49-54

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
ARMAX; genetic algorithms; linear and nonlinear identification methods; NARX; optimization; soft sensors

Sažetak
Fractionation product properties of crude distillation unit (CDU) need to be monitored and controlled through feedback mechanism. Due to inability of on-line measurement, soft sensors for product quality estimation are developed. Soft sensors for kerosene distillation end point are developed using linear and nonlinear identification methods. Experimental data are acquired from the refinery distributed control system (DCS) and include on-line available continuously measured variables and laboratory assays. In present work development of AutoRegressive Moving Average with eXogenous inputs (ARMAX) and Nonlinear AutoRegressive model with eXogenous inputs (NARX) are presented. To overcome the problem of selecting the best model set parameters by trial and error procedure, genetic algorithms were used for optimizing the best set of model parameters. Genetic algorithms were approved to be suitable method for optimizing ARMAX and NARX model structure in a way to find the best fits for given parameters range. Based on developed soft sensors it is possible to estimate fuel properties continuously by embedding model in DCS on site as well as applying the methods of inferential control.

Izvorni jezik
Engleski

Znanstvena područja
Kemijsko inženjerstvo, Računarstvo



POVEZANOST RADA


Projekt / tema
125-1251963-1964 - Softverski senzori i analizatori za motrenje i vođenje procesa (Nenad Bolf, )
117-0000000-3254 - Evolucijski algoritmi za optimiranje elektromagnetskog opterećenja okoliša (Darko Grundler, )

Ustanove
Tekstilno-tehnološki fakultet, Zagreb,
Fakultet kemijskog inženjerstva i tehnologije, Zagreb

Citiraj ovu publikaciju

Ujević Andrijić, Željka; Bolf, Nenad; Rolich Tomislav
Optimizing configurable parameters of model structure using genetic algorithms // TEDI - International Interdisciplinary Journal of Young Scientists from the Faculty of Textile Technology, 1 (2011), 1; 49-54 (podatak o recenziji nije dostupan, članak, znanstveni)
Ujević Andrijić, Ž., Bolf, N. & Rolich Tomislav (2011) Optimizing configurable parameters of model structure using genetic algorithms. TEDI - International Interdisciplinary Journal of Young Scientists from the Faculty of Textile Technology, 1 (1), 49-54.
@article{article, year = {2011}, pages = {49-54}, keywords = {ARMAX, genetic algorithms, linear and nonlinear identification methods, NARX, optimization, soft sensors}, journal = {TEDI - International Interdisciplinary Journal of Young Scientists from the Faculty of Textile Technology}, volume = {1}, number = {1}, issn = {1847-9545}, title = {Optimizing configurable parameters of model structure using genetic algorithms}, keyword = {ARMAX, genetic algorithms, linear and nonlinear identification methods, NARX, optimization, soft sensors} }