Optimal control of bioreactors: a simultaneous approach for complex systems

Riascos, Carlos A.M.

doi:10.1016/j.cej.2003.09.002

Cited by 34 publications

(34 citation statements)

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“…This approach has been adopted by many earlier studies of the PHB system [1,34,39,40] and other fermentations [42][43][44], which found it useful to explore bioreactor dynamics by generating data by solving a model with laboratory-scale kinetics and nonideal features that mimic real conditions. Finite dispersion in these applications and in the present work was included by employing mass balance equations with dispersion terms expressed by Pe [8,45].…”

Section: Data Generationmentioning

confidence: 99%

Cognitive optimization of microbial PHB production in an optimally dispersed bioreactor by single and mixed cultures

Patnaik

2008

Bioprocess Biosyst Eng

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Cognitive (or intelligent) models are often superior to mechanistic models for nonideal bioreactors. Two kinds of cognitive models--cybernetic and neural--were applied recently to fed-batch fermentation by Ralstonia eutropha in a bioreactor with optimum finite dispersion. In the present work, these models have been applied in simulation studies of co-cultures of R. eutropha and Lactobacillus delbrueckii. The results for both cognitive and mechanistic models have been compared with single cultures. Neural models were the most effective for both types of cultures and mechanistic models the least effective. Simulations with co-culture fermentations predicted more PHB than single cultures with all three types of models. Significantly, the predicted enhancements in PHB concentration by cognitive methods for mixed cultures were four to five times larger than the corresponding increases in biomass concentration. Further improvements are possible through a hybrid combination of all three types of models.

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Section: Data Generationmentioning

confidence: 99%

Cognitive optimization of microbial PHB production in an optimally dispersed bioreactor by single and mixed cultures

Patnaik

2008

Bioprocess Biosyst Eng

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“…Another difficulty arises around switching times where the optimal solution is discontinuous. As a recent example, Riascos et al (2004) showed that discretisation of differential-algebraic equation (DAE) systems by orthogonal collocation in finite elements efficiently transforms dynamic optimisation problems into nonlinear programming (NLP) problems.…”

Section: Subject To the Process Dynamicsmentioning

confidence: 99%

Optimisation of Operating Conditions in Fed-Batch Baker’s Yeast Fermentation

Atasoy¹,

Yüceer²,

Berber³

2013

Chemical and Process Engineering

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TurkeySaccharamyces cerevisia known as baker's yeast is a product used in various food industries. Worldwide economic competition makes it a necessity that industrial processes be operated in optimum conditions, thus maximisation of biomass in production of saccharamyces cerevisia in fedbatch reactors has gained importance. The facts that the dynamic fermentation model must be considered as a constraint in the optimisation problem, and dynamics involved are complicated, make optimisation of fed-batch processes more difficult.In this work, the amount of biomass in the production of baker's yeast in fed-batch fermenters was intended to be maximised while minimising unwanted alcohol formation, by regulating substrate and air feed rates. This multiobjective problem has been tackled earlier only from the point of view of finding optimum substrate rate, but no account of air feed rate profiles has been provided. Control vector parameterisation approach was applied the original dynamic optimisation problem which was converted into a NLP problem. Then SQP was used for solving the dynamic optimisation problem. The results demonstrate that optimum substrate and air feeding profiles can be obtained by the proposed optimisation algorithm to achieve the two conflicting goals of maximising biomass and minimising alcohol formation.

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“…The formerly described model by Ferraz et al 138 was further elaborated and improved by Riascos and Pinto 141 . The authors proposed the use of orthogonal collocation to a simultaneous optimization approach.…”

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confidence: 99%

“…The results of this investigation indicated that "the discretization of differential-algebraic equation systems (DAE) by orthogonal collocation in finite elements efficiently trans forms dynamic optimization problems into non linear programming (NLP) problems". Thus, the solution of complex problems with several control variables satisfied the approximation error tolerance 141 . According to Patnaik 48 ,there is evidence that the results achieved by the model described above are "inferior" to those presented by Gadkar et al 140 .…”

mentioning

confidence: 99%

“…The published cybernetic model of continuous PHB production by Alcaligenes eutrophus 141 (today C. necator) was extended to an industrial two-stage continuous process 142 . This model incorporated three main metabolic pathways -the glycolysis, pentose phosphate, and the TCA cycle pathwaysupposing that glucose and NH 4 + are converted by the cells into precursors required for cell growth and storage materials.…”

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confidence: 99%

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Mathematical Modelling as a Tool for Optimized PHA Production

Novák

Koller

Braunegg

et al. 2015

Chem.Biochem.Eng.Q.

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c ARENA -Association for resource efficient and sustainable technologies, Inffeldgasse 21b, 8010 Graz, AustriaThe potential of poly(hydroxyalkanoates) (PHAs) to replace conventional plastic materials justifies the increasing attention they have drawn both at lab-scale and in industrial biotechnology.The improvement of large-scale productivity and biochemical/genetic properties of producing strains requires mathematical modeling and process/strain optimization procedures. Current models dealing with structurally diversified PHAs, both structured and unstructured, can be divided into formal kinetic, low-structured, dynamic, metabolic (high-structured), cybernetic, neural networks and hybrid models; these attempts are summarized in this review. Characteristic properties of specific groups of models are stressed in light of their benefit to the better understanding of PHA biosynthesis, and their applicability for enhanced productivity. Unfortunately, there is no single type of mathematical model that expresses exactly all the characteristics of producing strains and/or features of industrial-scale plants; in addition, the different requirements for modelling of PHA production by pure cultures or mixed microbial consortia have to be addressed. Therefore, it is crucial to sophisticatedly adapt and fine-tune the modelling approach accordingly to actual processes, as the case arises. For "standard microbial cultivations and everyday practices", formal kinetic models (for simple cases) and "low-structured" models will be appropriate and of great benefit. They are relatively simple and of low computational demand.To overcome the specific weaknesses of different established model types, some authors use hybrid models. Here, satisfying compromises can be achieved by combining mechanistic, cybernetic, and neural and computational fluid dynamics (CFD) models. Therefore, this hybrid modelling approach appears to constitute the most promising solution to generate a holistic picture of the entire PHA production process, encompassing all the benefits of the original modelling strategies. Complex growth media require a higher degree of model structuring. For scientific purposes and advanced development of industrial equipment in the future, real systems will be modelled by highly organized hybrid models.All solutions related to modelling PHA production are discussed in this review.

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Optimal control of bioreactors: a simultaneous approach for complex systems

Cited by 34 publications

References 20 publications

Cognitive optimization of microbial PHB production in an optimally dispersed bioreactor by single and mixed cultures

Cognitive optimization of microbial PHB production in an optimally dispersed bioreactor by single and mixed cultures

Optimisation of Operating Conditions in Fed-Batch Baker’s Yeast Fermentation

Mathematical Modelling as a Tool for Optimized PHA Production

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