Tracking Control of Optimal Profiles in a Nonlinear Fed-Batch Bioprocess under Parametric Uncertainty and Process Disturbances (original) (raw)
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Industrial & Engineering Chemistry Research, 2017
This paper aims to solve the problem of tracking optimal profiles for a nonlinear multivariable fedbatch 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.
An algebra approach for nonlinear multivariable fed-batch bioprocess control
International Journal of Industrial and Systems Engineering, 2019
In this paper, a linear algebra-based controller design is proposed. This technique allows tracking, with minimum error, predefined optimal profiles in nonlinear and multivariable systems. To achieve this, control actions are obtained by solving a linear equation system. The controller parameters are selected with a Monte Carlo algorithm. The methodology is applied in a fed-batch penicillin production process, where the control action is the feed flow rate and the tracked profiles are the concentration of biomass, product and subtract inside the reactor. Different tests are shown to prove the good performance of the controller adding: parametric uncertainty and perturbations in the control action and in the initial conditions
Nonlinear Control for Bioprocesses with Model Uncertainties and External Disturbances
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. e 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.
Trajectory Tracking Controller for a Nonlinear Fed-batch Bioprocess
2017
El objetivo de este trabajo es desarrollar una tecnica de control simple pero eficiente, basada en un enfoque del algebra lineal para el seguimiento de perfiles optimos de un bioproceso fed-batch, multivariable y no lineal. La metodologia propuesta permite, conociendo los estados deseados, encontrar las acciones de control adecuadas mediante la resolucion de un sistema de ecuaciones lineales. La principal ventaja es que el error de seguimiento tiende a cero. La eficiencia del controlador propuesto es verificada a traves de varias simulaciones. Los parametros optimos del controlador se seleccionan mediante un algoritmo de Montecarlo bajo la condicion de minimizar un cierto indice de costo.
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Ingeniería Electrónica, Automática y Comunicaciones, 2017
This paper aims to develop a simple but efficient control technique based on a linear algebra approach for tracking optimal profiles of a nonlinear multivariable fed-batch bioprocess. The methodology proposed allows, knowing the desired states, to find the values for the control actions by solving a system of linear equations. Its main advantage is that the condition for the tracking error tends to zero. The efficiency of the proposed controller is tested through several simulations. The optimal controller parameters are selected through Montecarlo Randomized Algorithm in order to minimize a cost index.
Optimal fed-batch bioprocess control. An advanced approach
Computer Aided Chemical Engineering, 2007
Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.
Quality Fed-Batch Bioprocess Control A Case Study
World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering, 2009
Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate. Keywords—Fed batch bioprocess; mass-balance model; fuzzy control
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Key Engineering Materials, 2011
Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. For this kind of bioprocess where the mathematical model contains many structured and unstructured uncertainties, we try to combine different intelligent techniques based on natural syllogisms of these techniques. In order to obtain a high bioprocess productivity it is essential to accord the benefits of the classical control strategy (i.e. the analytical determination of the optimum) with the subjective bioprocess characterization (due to the human expert) in order to diminish the on line information scarcity. The research objective of this study was to develop an appropriate control method for a new complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate..
Quality Fed-Batch Bioprocess Control A Case
2011
Abstract—Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate. Keywords—Fed batch bioprocess; mass-balance model; fuzzy control I.
Open-loop optimization and trajectory tracking of a fed-batch bioreactor
Chemical Engineering and Processing: Process Intensification, 2008
This paper deals first with the open-loop optimization of a fed-batch bioreactor, using an approach combining direct transcription and collocation techniques. The proposed strategy avoids taking into account singular arcs as it transforms the optimization problem into a nonlinear programming problem (NLP). The state and control variables are both discretized and optimized through classical direct optimization methods. The optimal feeding law is thus computed being less sensitive to initialization of the algorithm. In a second time, the control law is synthesised to provide an optimal tracking of the previous trajectory. This is carried out using a linearizing state-feedback control in an inner loop, in addition to a controller in an outer loop to guarantee a good stability and accuracy. Finally, some numerical results on two case studies are given to illustrate the efficiency of the proposed optimisation and control strategies.