Optimizing Control Action Online Using a Neural Model and the Solver of an Electronic Worksheet

Fujiki, Tatiana Lie; Sanzovo, Márcia R.G.; Leite, Manuela Souza; Silva, Flávio V.; Fileti, Ana Maria Frattini

doi:10.1016/s1570-7946(09)70634-0

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…Biological processes are becoming more frequent nowadays due to the wide variety of products obtained from them [1] and their possibility of making some processes environmentally friendly while high standard products are obtained [2,3]. e fed-batch operation mode is which most interest awake for its main benefits [4,5].…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Control for Bioprocesses with Model Uncertainties and External Disturbances

Fernández

Pantano

Rodríguez

et al. 2021

Mathematical Problems in Engineering

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In this paper, a new alternative for profiles tracking control considering additive uncertainties is proposed. Based on a previously presented work about a nonlinear and multivariable controller design for a fed-batch bioethanol production, parametric uncertainty and process disturbance are taken into account to find a more reliable control strategy for a successful industrial implementation. To decrease the uncertainties effect, an approach based on the error estimation using Newton’s backward interpolation is included in the design equations. The proposed modification assures the error convergence to zero (demonstration is shown) despite the uncertainties, which is one of the main contributions of this work. A comparison between the new, the original proposal, and another methodology is exposed.

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Section: Introductionmentioning

confidence: 99%

Nonlinear Control for Bioprocesses with Model Uncertainties and External Disturbances

Fernández

Pantano

Rodríguez

et al. 2021

Mathematical Problems in Engineering

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“…The worldwide market requirements for high standard products, as well as safe and environmentally friendly processes, force chemical industries to look for optimization methods and controllers that can afford nonlinearities and transient behavior of chemical and biochemical processes (Fujiki et al, 2009). On the one hand, many scientists have established optimization methods to find the best feed rate profile for different processes involving fed-batch fermentations (for some examples see: Ye et al, 2014;Kookos, 2004;del Rio-Chanona et al, 2016 andDai et al, 2014, as this issue is beyond the aim of this paper).…”

Section: Introductionmentioning

confidence: 99%

State Estimation and Trajectory Tracking Control for a Nonlinear and Multivariable Bioethanol Production System

Fernández¹,

Pantano²,

Rossomando³

et al. 2019

Braz. J. Chem. Eng.

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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.

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Optimizing Control Action Online Using a Neural Model and the Solver of an Electronic Worksheet

Cited by 2 publications

References 4 publications

Nonlinear Control for Bioprocesses with Model Uncertainties and External Disturbances

Nonlinear Control for Bioprocesses with Model Uncertainties and External Disturbances

State Estimation and Trajectory Tracking Control for a Nonlinear and Multivariable Bioethanol Production System

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