(216e) Advanced Control Strategy to a Fermentation Process to Obtain Ethanol

Duarte, E. R., State University of Campinas (UNICAMP)
Ender, L., Regional University of Blumenau
Maciel Filho, R., Separation Process Development Laboratory, Faculty of Chemical Engineering, State University of Campinas (UNICAMP)

Nowadays days with the globalisation, market competitively and environmental concern, there is a real need of products with high quality, low cost and low emission of pollutants. The process control is the main form to reach such objectives. That is the reason for the great advance on researches in the investigation of new methodologies and conceptions about process development and process control in all areas. The several control strategies have been tested and the proposed control algorithm has shown very good results, allowing the system to be operated in a high performance level and safe manner. As a case study it is considered an extractive alcoholic fermentation process. There is a great interest in the optimisation of the ethanol process, especially due the many advantages of using ethanol as fuel. In order to do that, it is necessary an efficient and robust control strategy because the control of biotechnological process is very difficult due to the complex nature of the microbial metabolism, as well as no linearity of its kinetics. The proposed control algorithm has shown to be robust for the analysed disturbances, presenting a great potential to be used in control strategies of large-scale systems. Particularly, the successful application of the proposed algorithm in the case study reveals its potential it's a large number of chemical processes of industrial interest. As a case study an extractive alcoholic fermentation process is considered, it that consists on four interlinked units: fermentor (ethanol production unit), centrifuge (cell separation unit), cell treatment unit, and vacuum vessel (ethanol ?water separation unit), represented a non-linear process. The obtained results showed the potential of the proposed learning strategy for non-linear process.


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