| Full text | |
| Author(s): |
Furlong, Vitor B.
[1]
;
Correa, Luciano J.
[2]
;
Lima, Fernando V.
[3]
;
Giordano, Roberto C.
[1, 4]
;
Ribeiro, Marcelo P. A.
[1, 4]
Total Authors: 5
|
| Affiliation: | [1] Univ Fed Sao Carlos, Grad Program Chem Engn, POB 676, BR-13565905 Sao Carlos, SP - Brazil
[2] Univ Fed Lavras, Dept Engn, POB 3037, BR-37200000 Lavras, MG - Brazil
[3] West Virginia Univ, Dept Chem & Biomed Engn, Morgantown, WV 26506 - USA
[4] Univ Fed Sao Carlos, Chem Engn Dept, POB 676, BR-13565905 Sao Carlos, SP - Brazil
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | PROCESSES; v. 8, n. 4 APR 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
Second generation ethanol faces challenges before profitable implementation. Biomass hydrolysis is one of the bottlenecks, especially when this process occurs at high solids loading and with enzymatic catalysts. Under this setting, kinetic modeling and reaction monitoring are hindered due to the conditions of the medium, while increasing the mixing power. An algorithm that addresses these challenges might improve the reactor performance. In this work, a soft sensor that is based on agitation power measurements that uses an Artificial Neural Network (ANN) as an internal model is proposed in order to predict free carbohydrates concentrations. The developed soft sensor is used in a Moving Horizon Estimator (MHE) algorithm to improve the prediction of state variables during biomass hydrolysis. The algorithm is developed and used for batch and fed-batch hydrolysis experimental runs. An alteration of the classical MHE is proposed for improving prediction, using a novel fuzzy rule to alter the filter weights online. This alteration improved the prediction when compared to the original MHE in both training data sets (tracking error decreased 13%) and in test data sets, where the error reduction obtained is 44%. (AU) | |
| FAPESP's process: | 16/10636-8 - From the cell factory to the Biodiesel-Bioethanol integrated biorefinery: a systems approach applied to complex problems in micro and macroscales |
| Grantee: | Roberto de Campos Giordano |
| Support Opportunities: | Program for Research on Bioenergy (BIOEN) - Thematic Grants |