info:eu-repo/semantics/article
Multivariable Control for Tracking Optimal Profiles in a Nonlinear Fed-Batch Bioprocess Integrated with State Estimation
Fecha
2017-05Registro en:
Pantano, Maria Nadia; Serrano, Mario Emanuel; Fernández Puchol, María Cecilia; Rossomando, Francisco Guido; Ortiz, Oscar Alberto; et al.; Multivariable Control for Tracking Optimal Profiles in a Nonlinear Fed-Batch Bioprocess Integrated with State Estimation; American Chemical Society; Industrial & Engineering Chemical Research; 56; 20; 5-2017; 6043-6056
0888-5885
CONICET Digital
CONICET
Autor
Pantano, Maria Nadia
Serrano, Mario Emanuel
Fernández Puchol, María Cecilia
Rossomando, Francisco Guido
Ortiz, Oscar Alberto
Scaglia, Gustavo Juan Eduardo
Resumen
This paper aims to solve the problem of tracking optimal profiles for a nonlinear multivariable fed-batch bioprocess by a simple but efficient closed-loop control technique based on a linear algebra approach. In the proposed methodology, the control actions are obtained by solving a system of linear equations without the need for state transformations. The optimal profiles to follow are directly those corresponding to output desired variables, therefore, estimation of states for nonmeasurable variables is considered by employing a neural networks method. The efficiency of the proposed controller is tested through several simulations, including process disturbances and operation under parametric uncertainty. The optimal controller parameters are selected through the Montecarlo Randomized Algorithm. In addition, proof of convergence to zero of tracking errors is analyzed and included in this article.