State estimation and trajectory tracking control for a nonlinear and multivariable bioethanol production system

In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves fnding feed rate profles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefned concentration profles. A neural networ...

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Detalles Bibliográficos
Autores: Fernández, Maria Cecilia, Pantano, Maria Nadia, Rossomando, Francisco Guido, Ortiz, Oscar Alberto, Scaglia, Gustavo Juan Eduardo
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/124802
Acceso en línea:http://hdl.handle.net/11336/124802
Access Level:acceso abierto
Palabra clave:FED-BATCH BIOPROCESS
NONLINEAR AND MULTIVARIABLE SYSTEM
NUMERICAL METHODS/LINEAR ALGEBRA
PROFLES TRACKING CONTROL
STATE ESTIMATION
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
Descripción
Sumario:In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves fnding feed rate profles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefned concentration profles. A neural network states estimation is designed in order to know those variables that cannot be measured. The controller is tuned using a Monte Carlo experiment for which a cost function that penalizes tracking errors is defned. Moreover, several tests (adding parametric uncertainty and perturbations in the control action) are carried out so as to evaluate the controller performance. A comparison with another controller is made. The demonstration of the error convergence, as well as the stability analysis of the neural network, are included.