Neural network based control of an absorption column in the process of bioethanol production

Author(s)

Eyng, Eduardo ^[1] ; da Silva, Flavio Vasconcelos ^[1] ; Palu, Fernando ^[2] ; Frattini Fileti, Ana Maria ^[1]

Affiliation

^[1] Univ Estadual Campinas, Fac Engn Quim, BR-13083970 Campinas, SP - Brazil

^[2] Univ Estadual Oeste do Parana, BR-85903000 Toledo, PR - Brazil

• Document type: Journal article
• Source: Brazilian Archives of Biology and Technology; v. 52, n. 4, p. 961-972, JUL-AUG 2009.
• Web of Science Citations: 1

Abstract

Gaseous ethanol may be recovered from the effluent gas mixture of the sugar cane fermentation process using a staged absorption column. In the present work, the development of a nonlinear controller, based on a neural network inverse model (ANN controller), was proposed and tested to manipulate the absorbent flow rate in order to control the residual ethanol concentration in the effluent gas phase. Simulation studies were carried out, in which a noise was applied to the ethanol concentration signals from the rigorous model. The ANN controller outperformed the dynamic matrix control (DMC) when step disturbances were imposed to the gas mixture composition. A security device, based on a conventional feedback algorithm, and a digital filter were added to the proposed strategy to improve the system robustness when unforeseen operating and environmental conditions occured. The results demonstrated that ANN controller was a robust and reliable tool to control the absorption column. (AU)

• FAPESP's process: 05/02536-9 - Control via neural networks of absorption columns in the production process of ethanol by fermentation
• Grantee: Eduardo Eyng
• Support Opportunities: Scholarships in Brazil - Doctorate