Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks
Nonlinear system identification is becoming an important tool which can be used to improve control performance and achieve robust fault-tolerant behavior. Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Science and Technology of Nuclear Installations |
| Online Access: | http://dx.doi.org/10.1155/2014/854569 |
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| author | Dede Sutarya Benyamin Kusumoputro |
| author_facet | Dede Sutarya Benyamin Kusumoputro |
| author_sort | Dede Sutarya |
| collection | DOAJ |
| description | Nonlinear system identification is becoming an important tool which can be used to improve control performance and achieve robust fault-tolerant behavior. Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the academia, but also in industrial application. An identification scheme of nonlinear systems for sintering furnace temperature in nuclear fuel fabrication using neural network autoregressive with exogenous inputs (NNARX) model investigated in this paper. The main contribution of this paper is to identify the appropriate model and structure to be applied in control temperature in the sintering process in nuclear fuel fabrication, that is, a nonlinear dynamical system. Satisfactory agreement between identified and experimental data is found with normalized sum square error 1.9e-03 for heating step and 6.3859e-08 for soaking step. That result shows the model successfully predict the evolution of the temperature in the furnace. |
| format | Article |
| id | doaj-art-c31078299b3b4df9a49681fbebf265dd |
| institution | Kabale University |
| issn | 1687-6075 1687-6083 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Science and Technology of Nuclear Installations |
| spelling | doaj-art-c31078299b3b4df9a49681fbebf265dd2025-02-03T01:01:57ZengWileyScience and Technology of Nuclear Installations1687-60751687-60832014-01-01201410.1155/2014/854569854569Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural NetworksDede Sutarya0Benyamin Kusumoputro1Department of Electrical Engineering, University of Indonesia, Kampus Baru UI, Depok 16424, IndonesiaDepartment of Electrical Engineering, University of Indonesia, Kampus Baru UI, Depok 16424, IndonesiaNonlinear system identification is becoming an important tool which can be used to improve control performance and achieve robust fault-tolerant behavior. Among the different nonlinear identification techniques, methods based on neural network model are gradually becoming established not only in the academia, but also in industrial application. An identification scheme of nonlinear systems for sintering furnace temperature in nuclear fuel fabrication using neural network autoregressive with exogenous inputs (NNARX) model investigated in this paper. The main contribution of this paper is to identify the appropriate model and structure to be applied in control temperature in the sintering process in nuclear fuel fabrication, that is, a nonlinear dynamical system. Satisfactory agreement between identified and experimental data is found with normalized sum square error 1.9e-03 for heating step and 6.3859e-08 for soaking step. That result shows the model successfully predict the evolution of the temperature in the furnace.http://dx.doi.org/10.1155/2014/854569 |
| spellingShingle | Dede Sutarya Benyamin Kusumoputro Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks Science and Technology of Nuclear Installations |
| title | Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks |
| title_full | Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks |
| title_fullStr | Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks |
| title_full_unstemmed | Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks |
| title_short | Identification of Industrial Furnace Temperature for Sintering Process in Nuclear Fuel Fabrication Using NARX Neural Networks |
| title_sort | identification of industrial furnace temperature for sintering process in nuclear fuel fabrication using narx neural networks |
| url | http://dx.doi.org/10.1155/2014/854569 |
| work_keys_str_mv | AT dedesutarya identificationofindustrialfurnacetemperatureforsinteringprocessinnuclearfuelfabricationusingnarxneuralnetworks AT benyaminkusumoputro identificationofindustrialfurnacetemperatureforsinteringprocessinnuclearfuelfabricationusingnarxneuralnetworks |