Fuzzy-Enhanced Modeling of Lignocellulosic Biomass Enzymatic Saccharification

Author(s)

Furlong, Vitor B. ^[1] ; Correa, Luciano J. ^[2] ; Giordano, Roberto C. ^[1] ; Ribeiro, Marcelo P. A. ^[1]

Affiliation

^[1] Univ Fed Sao Carlos, Chem Engn Dept, BR-13565905 Sao Carlos, SP - Brazil

^[2] Univ Fed Lavras, Dept Engn, POB 3037, BR-37200000 Lavras, MG - Brazil

• Document type: Journal article
• Source: ENERGIES; v. 12, n. 11 JUN 1 2019.
• Web of Science Citations: 0

Abstract

The enzymatic hydrolysis of lignocellulosic biomass incorporates many physico-chemical phenomena, in a heterogeneous and complex media. In order to make the modeling task feasible, many simplifications must be assumed. Hence, different simplified models, such as Michaelis-Menten and Langmuir-based ones, have been used to describe batch processes. However, these simple models have difficulties in predicting fed-batch operations with different feeding policies. To overcome this problem and avoid an increase in the complexity of the model by incorporating other phenomenological terms, a Takagi-Sugeno Fuzzy approach has been proposed, which manages a consortium of different simple models for this process. Pretreated sugar cane bagasse was used as biomass in this case study. The fuzzy rule combines two Michaelis-Menten-based models, each responsible for describing the reaction path for a distinct range of solids concentrations in the reactor. The fuzzy model improved fitting and increased prediction in a validation data set. (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