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

Brazilian Archives of Biology and Technology

Eduardo Eyng²  Flávio Vasconcelos Da Silva²  Fernando Palú¹  Ana Maria Frattini Fileti² 

[1] ,Universidade Estadual de Campinas Faculdade de Engenharia Química Campinas SP ,Brasil

关键词: Absorption column;    Artificial neural network;    Feedforward control;   

DOI  :  10.1590/S1516-89132009000400020

来源: SciELO

【 摘 要 】

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.

【 授权许可】

CC BY-NC   
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