| Revista: | Brazilian journal of chemical engineering |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000308713 |
| ISSN: | 0104-6632 |
| Autores: | Santos, V.M.L1 Carvalho, F.R Souza-Junior, M.B. de2 |
| Instituciones: | 1Universidade Federal de Pernambuco, Departamento de Engenharia Quimica, Recife, Pernambuco. Brasil 2Universidade Federal do Rio de Janeiro, Escola de Quimica, Rio de Janeiro. Brasil |
| Año: | 2000 |
| Periodo: | Dic |
| Volumen: | 17 |
| Número: | 4-7 |
| Paginación: | 897-906 |
| País: | Brasil |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | Artificial Neural Networks (ANNs) constitute a technology that has recently become the focus of great attention. The reason for this is due mainly to its capacity to treat complex and nonlinear problems. This work consists of the identification and control of a fluid cracking catalytic unit (FCCU) using techniques based on multilayered ANNs. The FCC unit is a typical example of a complex and nonlinear process, possessing great interaction among the operation variables and many operational constraints to be attended. Model Predictive Control is indicated in these occasions. The FCC model adopted was validated with plant data by Moro (1992); and was used in this work to replace the real process in the generation of data for the identification of the ANNs and to test the predictive control strategy. The results of the identification and control of the process through ANNs indicate the viability of the technique |
| Disciplinas: | Química |
| Palabras clave: | Ingeniería química, Desintegración catalítica de fluidos, Control predictivo, Redes neuronales artificiales |
| Keyword: | Chemistry, Chemical engineering, Fluid catalytic cracking, Predictive control, Artificial neural networks |
| Texto completo: | Texto completo (Ver HTML) |
