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The determination of optimal feeding profile of fed-batch fermentation requires the solution of a singular optimal control problem. The complexity in obtaining the solution to this singular problem is due to the nonlinear dynamics of the system model, the presence of control variables in linear form and the existence of constraints in both the state and control variables. Traditionally, during the optimization process, uncertainties associated with design variables, control parameters and mathematical model are not considered. In this contribution, a systematic methodology to evaluate uncertainties during the resolution of a singular optimal control problem is proposed. This approach consists of the Multi-objective Optimization Differential Evolution algorithm associated with Effective Mean Concept. The proposed methodology is applied to determine the feed substrate concentration in fed-batch penicillin fermentation process. The robust multi-objective singular optimal control problem consists of maximizing the productivity and minimizing the operation total time.
Gustavo B. Libotte. 2020. \u201cRobust Multi-Objective Singular Optimal Control Ofpenicillin Fermentation Process\u201d. Global Journal of Research in Engineering - J: General Engineering GJRE-J Volume 20 (GJRE Volume 20 Issue J3): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
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Total Score: 104
Country: Brazil
Subject: Global Journal of Research in Engineering - J: General Engineering
Authors: Gustavo B. Libotte, Fran S. Lobato, Gustavo M. Platt, Francisco D. Moura Neto (PhD/Dr. count: 0)
View Count (all-time): 192
Total Views (Real + Logic): 2356
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Publish Date: 2020 06, Wed
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The determination of optimal feeding profile of fed-batch fermentation requires the solution of a singular optimal control problem. The complexity in obtaining the solution to this singular problem is due to the nonlinear dynamics of the system model, the presence of control variables in linear form and the existence of constraints in both the state and control variables. Traditionally, during the optimization process, uncertainties associated with design variables, control parameters and mathematical model are not considered. In this contribution, a systematic methodology to evaluate uncertainties during the resolution of a singular optimal control problem is proposed. This approach consists of the Multi-objective Optimization Differential Evolution algorithm associated with Effective Mean Concept. The proposed methodology is applied to determine the feed substrate concentration in fed-batch penicillin fermentation process. The robust multi-objective singular optimal control problem consists of maximizing the productivity and minimizing the operation total time.
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