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...
| Authors: | , , , , |
|---|---|
| Format: | article |
| Status: | Published version |
| Publication Date: | 2019 |
| Country: | Argentina |
| Institution: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repository: | CONICET Digital (CONICET) |
| Language: | English |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/124802 |
| Online Access: | http://hdl.handle.net/11336/124802 |
| Access Level: | Open access |
| Keyword: | 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 |
| Summary: | 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. |
|---|