Modélisation et commande robuste des systèmes biologiques : exemple de la production d’acide lactique en fermenteur industriel

This PhD thesis focuses on the optimization of the bioprocess of lactic acid production from wheat flour. Indeed, lactic acid has received much attention for the production of PLA (Poly Lactic Acid), a biopolymer, since different inexpensive raw material such as wheat flour are now used as carbon source for its production. This work was performed in three main steps. In the first step, an innovative wheat transformation process is proposed, whose main steps are the following: a liquefaction followed by a simultaneous saccharification, proteins hydrolysis (SSPH) and and a final simultaneous saccharification, proteins hydrolysis and fermentation (SSPHF). Secondly, the modeling of the SSPHF (limiting step) in a continuous bioreactor is considered. The determination and validation of model parameters is performed by means of experimental campaigns in a 5 L bioreactor.In the last step, the development of control strategies to maintain the process at its optimal operating point is considered. To do so, due to the absence of sensors for real-time measurement of the concentrations of key variables of the bioreactor, estimators of these concentrations and of the lactic acid production rate are first developed. Then, control strategies for regulating the lactic acid concentration at its optimal value are designed and compared in simulation. An adaptive control combining a state feedback linearizing control and an estimator of the lactic acid production rate is finally chosen to be experimentally validated on an instrumented reactor. This strategy showed good robustness features with respect to modeling mismatches and was able during experiments to increase twice the lactic acid productivity.Cette thèse de doctorat porte sur l’optimisation du bioprocédé de production d’acide lactique à partir de la farine de blé. L'acide lactique s’avère en effet de plus en plus attractif pour la production de PLA (acide poly lactique), un bio polymère, d’autant plus que différentes matières premières peu coûteuses comme la farine de blé sont désormais utilisées comme sources de carbone pour sa production. Cette thèse comprend trois parties principales. Une première partie propose pour l’optimisation du procédé de transformation du blé un schéma innovant composé de trois étapes successives : une liquéfaction, suivi d’une étape de saccharification et hydrolyse des protéines simultanées (SSPH) et une étape finale de saccharification, hydrolyse des protéines et fermentation simultanées (SSPHF). La deuxième partie s’intéresse à la modélisation de l’étape SSPHF (étape limitante) dans un bioréacteur continu. La détermination des paramètres du modèle ainsi que leur validation sont réalisées à l’aide de campagnes d’essais sur un bioréacteur de 5 L.Enfin, la dernière partie développe la mise en oeuvre de stratégies de commande permettant de maintenir le bioprocédé à son point optimal de fonctionnement. Pour ce faire, du fait de l’absence de capteurs pour la mesure en temps réel des concentrations des variables clé dans le bioréacteur, des estimateurs de ces concentrations ainsi que du taux de production en acide lactique sont tout d’abord élaborés. Des stratégies de commande régulant la concentration d’acide lactique à sa valeur optimale sont ensuite synthétisées et comparées en simulation. Une commande adaptative combinant une commande linéarisante par retour d’état et un estimateur du taux de production en acide lactique est finalement retenue et validée expérimentalement sur un réacteur instrumenté. Cette dernière s’est avérée robuste vis-à-vis des erreurs de modélisation et a permis lors des expériences de doubler la productivité de l’acide lactique

Model-based strategies for computer-aided operation of recombinant E. coli fermentation

Tese de Doutoramento em Engenharia Química e BiológicaThe main objectives of this thesis were the development of model-based strategies for improving the performance of a high-cell density recombinant Escherichia coli fed-batch fermentation. The construction of a mathematical model framework as well as the derivation of optimal and adaptive control laws were used to accomplish these tasks. An on-line data acquisition system was also developed for an accurate characterization of the process and for the implementation of the control algorithms. The mathematical model of the process is composed of mass balance equations to the most relevant state variables of the process. Kinetic equations are based on the three possible metabolic pathways of the microorganism: glucose oxidation, fermentation of glucose and acetate oxidation. A genetic algorithm was used to derive the kinetic structure and to estimate both yield and kinetic coefficients of the model, minimizing the normalized quadratic differences between simulated and real values of the state variables. After parameter estimation, a sensitivity function analysis was applied to evaluate the influence of the various parameters on model behavior. Sensitivity functions revealed the sensitivity of the state variables to variations in each model parameter. Thus, essential parameters were selected and the model could be re-written in a simplified version that could also describe accurately experimental data. A system for the on-line monitoring of the major state variables was also developed. Glucose and acetate concentrations were measured with a developed Flow Injection Analysis system, while the carbon dioxide and oxygen transfer rates were calculated from data obtained with exhaust gas analysis. The fermentation culture weight was also continuously assessed with a balance, allowing the use of more precise mass-based concentrations, while environmental variables like pH, dissolved oxygen and temperatures were controlled and assessed via a Digital Control Unit. The graphical programming environment LabVIEW was used to acquire and integrate these variables in a supervisory computer, allowing the performance of integrated monitoring and control of the process. A model-based adaptive linearizing control law was derived for the regulation of acetate concentration during fermentations. The non-linear model was subjected to transformations in order to obtain a linear behavior for the control loop when a non-linear control is applied. The implementation of the control law was performed through a C script embedded in the supervisory LabVIEW program. Finally, two optimization techniques for the maximization of biomass concentration were compared: a first order gradient method and a stochastic method based on the biological principle of natural evolution, using a genetic algorithm. The former method revealed less efficient concerning to the computed maximum, and dependence on good initial values.A presente tese teve como principais objectivos o desenvolvimento de estratégias baseadas em modelos para melhorar o desempenho da fermentação em modo semi-continuo em altas densidades celulares de Escherichia coil recombinada. Para o efeito, foi construído um modelo matemático representativo do processo e a partir deste foram desenvolvidos algoritmos de controlo óptimo e adaptativo. De forma a possibilitar a implementação de leis de controlo em linha e a caracterização do processo fermentativo, foi desenvolvido um sistema informático de aquisição e envio de dados. O modelo matemático representativo do processo em estudo foi elaborado tendo por base as equações dinâmicas de balanço mássico para as variáveis de estado mais relevantes, contemplando as três possíveis vias metabólicas do microrganismo. A estrutura cinética, bem como os parâmetros do modelo foram determinados por recurso a uma abordagem sistemática tendo por base a minimização das diferenças quadráticas entra dados reais e dados simulados, com recurso a uma ferramenta de optimização estocástica denominada de Algoritmos Genéticos. Após a etapa de identificação do modelo matemático, foram calculadas as sensibilidades relativas ao longo do tempo das variáveis de estado do modelo relativamente aos vários parâmetros determinados. Os resultados desta análise de sensibilidade possibilitaram avaliar a relevância de cada um dos parâmetros em causa, permitindo propor uma estrutura de modelo menos complexa, por exclusão dos parâmetros menos importantes. O sistema elaborado para a aquisição e envio em linha de dados da fermentação inclui um sistema de FIA (Flow Injection Analysis) desenvolvido para a medição das concentrações de acetato e glucose, uma unidade de controlo digital que controla as variáveis físicas mais relevantes para o processo, e um equipamento de Espectrometria de Massas para analisar as correntes gasosas de entrada e saída do fermentador. O sistema dispõe ainda de duas balanças, uma das quais para a aferição em linha do peso do caldo de fermentação, permitindo o use de concentrações mássicas que proporcionam resultados mais exactos. A aquisição e integração destas variáveis medidas são, efectuadas através de um software de supervisão elaborado no ambiente de programação gráfico LabVIEW. Adicionalmente, foi elaborada uma lei de controlo adaptativo linearizante para a regulação da concentração de acetato no meio de fermentação. A síntese da lei de controlo não linear foi efectuada por técnicas de geometria diferencial com linearização do sistema por retroacção de estado. A adaptação foi feita tendo por base a estimação de parâmetros variáveis no tempo, nos quais se concentram as incertezas do modelo. A implementação ao processo real da referida lei de controlo foi efectuada por recurso a um programa elaborado em C incluindo no programa supervisor elaborado em LabVIEW. Finalmente, para a optimização da quantidade de biomassa formada no final da fermentação por manipulação do caudal de alimentação, foram estudadas duas ferramentas de optimização: um método de gradiente e uma ferramenta baseada em Algoritmos Genéticos. Esta última revelou-se mais eficaz tanto na convergência para o valor óptimo, como na estimativa inicial fornecida.Fundação para a Ciência e a Tecnologia (FCT) – PRAXIS XXI/16961/98.União Europeia - Fundo Social Europeu (FSE) – III Quadro Comunitário de Apoio (QCA III).Fundação Calouste Gulbenkian (FCQ) - Educação e Bolsas.Agência de Inovação (ADI) - PROTEXPRESS

Development of advanced monitoring and control tools for rAAV production in the insect cell system

"Since the first publication introducing the concept in 1972, gene therapy has had a series of success stories and setbacks. However, the recent rise of awareness, public interest, promising results in clinical trials and recent market approvals indicate that gene therapy has come to stay. Currently there is a growing interest from the biopharmaceutical industry in gene and cell therapy, mostly using viral vectors. (...)

Instrumentation and control of anaerobic digestion processes: a review and some research challenges

The final publication is available at Springer via http://dx.doi.org/10.1007/s11157-015-9382-6[EN] To enhance energy production from methane or resource recovery from digestate, anaerobic digestion processes require advanced instrumentation and control tools. Over the years, research on these topics has evolved and followed the main fields of application of anaerobic digestion processes: from municipal sewage sludge to liquid mainly industrial then municipal organic fraction of solid waste and agricultural residues. Time constants of the processes have also changed with respect to the treated waste from minutes or hours to weeks or months. Since fast closed loop control is needed for short time constant processes, human operator is now included in the loop when taking decisions to optimize anaerobic digestion plants dealing with complex solid waste over a long retention time. Control objectives have also moved from the regulation of key variables measured online to the prediction of overall process perfor- mance based on global off-line measurements to optimize the feeding of the processes. Additionally, the need for more accurate prediction of methane production and organic matter biodegradation has impacted the complexity of instrumentation and should include a more detailed characterization of the waste (e.g., biochemical fractions like proteins, lipids and carbohydrates)andtheirbioaccessibility andbiodegradability characteristics. However, even if in the literature several methodologies have been developed to determine biodegradability based on organic matter characterization, only a few papers deal with bioaccessibility assessment. In this review, we emphasize the high potential of some promising techniques, such as spectral analysis, and we discuss issues that could appear in the near future concerning control of AD processes.The authors acknowledge the financial support of INRA (the French National Institute for Agricultural Research), the French National Research Agency (ANR) for the "Phycover" project (project ANR-14-CE04-0011) and ADEME for Inter-laboratory assay financial support.Jimenez, J.; Latrille, E.; Harmand, J.; Robles Martínez, Á.; Ferrer Polo, J.; Gaida, D.; Wolf, C.... (2015). Instrumentation and control of anaerobic digestion processes: a review and some research challenges. Reviews in Environmental Science and Biotechnology. 14(4):615-648. doi:10.1007/s11157-015-9382-6S615648144Aceves-Lara CA, Latrille E, Steyer JP (2010) Optimal control of hydrogen production in a continuous anaerobic fermentation bioreactor. 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Novel strategies for process control based on hybrid semi-parametric mathematical systems

Tese de doutoramento. Engenharia Química. Universidade do Porto. Faculdade de Engenharia. 201

A MULTI-SCALE APPROACH TO FED-BATCH BIOREACTOR CONTROL

The rising energy costs, increased global competition in terms of both price and quality, and the need to make products in an environmentally benign manner have paved the way for the biological route towards manufacturing. Many of the products obtained by the biological route either cannot be produced, or are very difficult to obtain, by conventional manufacturing methods. Most of these products fall in the low volume/high value bracket, and it is estimated that the production of therapeutic proteins alone generated sales exceeding $25 billion in 2001. By increasing our understanding of these systems it may be possible to avoid some of the empiricism associated with the operation of (fed-)batch bioreactors. Considerable benefit, in terms of reduced product variability and optimal resource utilization could be achieved, and this work is a step in that direction.Biological reactors typically are governed by highly nonlinear behavior occuring on both a macroscopic reactor scale and a microscopic cellular scale. Reactions taking place at these scales also occur at different rates so that the bioreactor system is multi-scale both spatially and temporally. Since achievable controller performance in a model-based control scheme is dependent on the quality of the process model cite{mor89}, a controller based on a model that captures events occuring at both the reactor and cellular scales should provide superior performance when compared to a controller that employs a uniscale model. In the model considered for this work, the specific growth rate is used as a coupling parameter integrating the behavior of both scales. On the cellular level, flux distributions are used to describe cellular growth and product formation whereas a lumped-parameter reactor model provides the macroscopic process representation.The control scheme for the fed-batch bioreactor is implemented in two stages, and the substrate feed rate serves as the manipulated variable. Initially, a constrained optimal control problem is solved off-line, in order to determine the manipulated variable profile that maximizes the end of batch product concentration for the product of interest, while maintaining apre-specified, fixed final volume. The next step involves tracking of the optimal control trajectory, in closed-loop operation. The Shrinking Horizon Model Predictive Control (SHMPC) framework is used to minimize the projected deviations of the controlled variable from the specified trajectories. At every time step, the original nonlinear model is linearized and the optimization problem is formulated as a quadratic program, that includes constraints on the manipulated input and the final volume. Finally, the performance of the controller is evaluated, and strategies for disturbance compensation are presented. The results of this approach are presented for ethanol production in a baker's yeast fermentation case study