| dc.creator | Meleiro L.A.C. | |
| dc.creator | Maciel Filho R. | |
| dc.date | 2000 | |
| dc.date | 2015-06-30T19:48:06Z | |
| dc.date | 2015-11-26T14:46:30Z | |
| dc.date | 2015-06-30T19:48:06Z | |
| dc.date | 2015-11-26T14:46:30Z | |
| dc.date.accessioned | 2018-03-28T21:56:16Z | |
| dc.date.available | 2018-03-28T21:56:16Z | |
| dc.identifier | | |
| dc.identifier | Computers And Chemical Engineering. Elsevier Science Ltd, Exeter, United Kingdom, v. 24, n. 02/07/15, p. 925 - 930, 2000. | |
| dc.identifier | 981354 | |
| dc.identifier | | |
| dc.identifier | http://www.scopus.com/inward/record.url?eid=2-s2.0-0342322861&partnerID=40&md5=23d305a8f4b4d5967584e84cf30a8f80 | |
| dc.identifier | http://www.repositorio.unicamp.br/handle/REPOSIP/106971 | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/106971 | |
| dc.identifier | 2-s2.0-0342322861 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1252867 | |
| dc.description | In this work, a multivariable adaptive self-tuning controller (STC) was developed for a biotechnological process application. Due to the difficulties involving the measurements or the excessive amount of variables normally found in industrial process, it is highly recommended to develop 'soft-sensors' which, in this work, were based fundamentally on artificial neural networks (ANN). These methods are especially suitable for the identification of time-varying and nonlinear models. An advanced control strategy based on STC was applied to a fermentation process to produce ethanol (ethyl alcohol) in industrial scale. The reaction rate considered for substratum consumption, cells and ethanol productions are validated with industrial data for typical operating conditions. The results obtained show that the procedure proposed in this work has a great potential for application. (C) 2000 Elsevier Science Ltd.In this work, a multivariable adaptive self-tuning controller (STC) was developed for a biotechnological process application. Due to the difficulties involving the measurements or the excessive amount of variables normally found in industrial process, it is highly recommended to develop 'soft-sensors' which, in this work, were based fundamentally on artificial neural networks (ANN). These methods are especially suitable for the identification of time-varying and nonlinear models. An advanced control strategy based on STC was applied to a fermentation process to produce ethanol (ethyl alcohol) in industrial scale. The reaction rate considered for substratum consumption, cells and ethanol productions are validated with industrial data for typical operating conditions. The results obtained show that the procedure proposed in this work has a great potential for application. | |
| dc.description | 24 | |
| dc.description | 02/07/15 | |
| dc.description | 925 | |
| dc.description | 930 | |
| dc.description | Andrieta, S.R., (1994) Modelagem, Simulação e Controle de Fermentação Alcoólica Continua em Escala Industrial, , Ph.D. thesis. Brazil: FEA/UNICAMP | |
| dc.description | Assis, A.J., (1996) Projeta de Controladores Adaptativos Auto-ajustáveis, , M.Sc. thesis, São Paulo, Brasil: Chemical Engineering School, State University of Campinas | |
| dc.description | Åström, K., Wittenmark, B., (1995) Adaptive Control (2nd Ed.), , Reading, MA: Addison-Wesley | |
| dc.description | Cunha, C.C.F., De Souza Jr., M.B., Biomass estimation in a Bacillus thuringiensis fed-batch culture (1998) Annals of the 12th Brazilian Congress of Chemical Engineering | |
| dc.description | Dechechi, E.C., (1998) Controle Avançado Preditivo Adaptativa-DMC Multivariável Adaptativo, , Campinas, São Paulo, Brasil | |
| dc.description | Tese de Doutorado, DPQ/FEQ/UNICAMP | |
| dc.description | Palavajjhala, S., Motard, R.L., Joseph, B., Process identification using discrete wavelet transforms: Design of prefilters (1996) American Institute of Chemical Engineering Journal, 42 (3), pp. 777-790 | |
| dc.description | Psichogios, D.C., Ungar, L.H., A hybrid neural network-first principles approach to the modeling (1992) American Institute of Chemical Engineering Journal, 38 (10), p. 1992 | |
| dc.description | Zhang, Q., Reid, J.F., Litchfield, J.B., Ren, J., Chang, S.-W., A prototype neural network supervised control system for Bacillus thuringiensis fermentations (1994) Biotechnology & Bioengineering, 43, pp. 483-489 | |
| dc.language | en | |
| dc.publisher | Elsevier Science Ltd, Exeter, United Kingdom | |
| dc.relation | Computers and Chemical Engineering | |
| dc.rights | fechado | |
| dc.source | Scopus | |
| dc.title | A Self-tuning Adaptive Control Applied To An Industrial Large Scale Ethanol Production | |
| dc.type | Actas de congresos | |
