Thesis: State Estimation and Model Predictive Control of the Anaerobic Digestion Process for the Optimization of Biogas Production
| datacite.subject.fos | Engineering and technology | |
| dc.contributor.correferente | Otro | |
| dc.contributor.department | Departamento de Electrónica | |
| dc.contributor.guia | Otro | |
| dc.coverage.spatial | Campus Casa Central Valparaíso | |
| dc.creator | Azúa Poblete, Michel Andrés | |
| dc.date.accessioned | 2025-09-16T13:33:20Z | |
| dc.date.available | 2025-09-16T13:33:20Z | |
| dc.date.issued | 2025-07-29 | |
| dc.description.abstract | This thesis focuses on the optimization of the anaerobic digestion (AD) process. A discrete mathematical model (AM2), inspired by the ADM1 model, was developed to accurately represent the specific dynamics of the process under study. This model was calibrated and validated using simulated data obtained from the ADM1 model. By implementing a nonlinear predictive control (NMPC) and an extended Kalman filter (EKF), it was possible to significantly control and optimize the performance of the process with the objective of maximizing biogas production. This research contributes to the advancement of chemical process control, offering valuable tools for industrial and environmental applications. | en_US |
| dc.description.abstract | Esta tesis se centra en la optimización del proceso de digestión anaeróbica (DA). Se desarrolló un modelo matemático discreto (AM2), inspirado en el modelo ADM1, para representar de manera precisa las dinámicas específicas del proceso en estudio. Este modelo fue calibrado y validado utilizando datos simulados obtenidos del modelo ADM1. Mediante la implementación de un control predictivo no lineal (NMPC) y un filtro de Kalman extendido (EKF), se logró controlar y optimizar significativamente el desempeño del proceso con el objetivo de maximizar la producción de biogás. Esta investigación contribuye al avance en el control de procesos químicos, ofreciendo herramientas valiosas para aplicaciones industriales y ambientales. | es |
| dc.description.degree | Magíster en Ciencias de la Ingeniería Electrónica | |
| dc.driver | info:eu-repo/semantics/masterThesis | |
| dc.format.extent | 77 páginas. | |
| dc.identifier.doi | 10.71959/aaba-w435 | |
| dc.identifier.uri | https://cris.usm.cl/handle/123456789/4125 | |
| dc.identifier.uri | https://doi.org/10.71959/aaba-w435 | |
| dc.language.iso | en | |
| dc.publisher | Universidad Técnica Federico Santa María | |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | NMPC | |
| dc.subject | EKF | |
| dc.subject | Anaerobic Digestion | |
| dc.subject | Observers | |
| dc.subject | Parameter Identification | |
| dc.subject | Integral Action | |
| dc.subject.ods | 7 Energía asequible y no contaminante | |
| dc.subject.ods | 9 Industria, innovación e infraestructura | |
| dc.title | State Estimation and Model Predictive Control of the Anaerobic Digestion Process for the Optimization of Biogas Production | |
| dspace.entity.type | Tesis |
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