STATE ESTIMATION AND TRAJECTORY TRACKING CONTROL FOR A NONLINEAR AND MULTIVARIABLE BIOETHANOL PRODUCTION SYSTEM

AUTOR(ES)

Cecilia Fernández, M.

FONTE

Braz. J. Chem. Eng.

DATA DE PUBLICAÇÃO

15/07/2019

RESUMO

ABSTRACT In this paper a controller is proposed based on linear algebra for a fed-batch bioethanol production process. It involves finding feed rate profiles (control actions obtained as a solution of a linear equations system) in order to make the system follow predefined concentration profiles. 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 defined. 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.

Documentos Relacionados

• State and parameter estimation based on a nonlinear filter applied to an industrial process control of ethanol production
• Multivariable H2 and H∞ control for a wind energy conversion system: a comparison
• Robust Optimal Adaptive Trajectory Tracking Control of Quadrotor Helicopter
• Adaptive control of nonlinear visual servoing systems for 3D cartesian tracking
• Non-linear multivariable predictive control of an alcoholic fermentation process using functional link networks