Reaction rate reconstruction from biomass concentration measurement in bioreactors using modified second-order sliding mode algorithms

This paper deals with the estimation of unknown signals in bioreactors using sliding observers. Particular attention is drawn to estimate the specific growth rate of microorganisms from measurement of biomass concentration. In a recent article, notions of high-order sliding modes have been used to derive a growth rate observer for batch processes. In this paper we generalize and refine these preliminary results. We develop a new observer with a different error structure to cope with other types of processes. Furthermore, we show that these observers are equivalent, under coordinate transformations and time scaling, to the classical super-twisting differentiator algorithm, thus inheriting all its distinctive features. The new observers’ family achieves convergence to timevarying unknown signals in finite time, and presents the best attainable estimation error order in the presence of noise. In addition, the observers are robust to modeling and parameter uncertainties since they are based on minimal assumptions on bioprocess dynamics. In addition, they have interesting applications in fault detection and monitoring. The observers performance in batch, fed-batch and continuous bioreactors is assessed by experimental data obtained from the fermentation of Saccharomyces Cerevisiae on glucose.This work was supported by the National University of La Plata (Project 2012-2015), the Agency for the Promotion of Science and Technology ANPCyT (PICT2007-00535) and the National Research Council CONICET (PIP112-200801-01052) of Argentina; the Technical University of Valencia (PAID-02-09), the CICYT (DPI2005-01180) and AECID (A/024186/09) of Spain; and by the project FEDER of the European Union.De Battista, H.; Picó Marco, JA.; Garelli, F.; Navarro Herrero, JL. (2012). 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A procedure for the estimation over time of metabolic fluxes in scenarios where measurements are uncertain and/or insufficient

<p>Abstract</p> <p>Background</p> <p>An indirect approach is usually used to estimate the metabolic fluxes of an organism: couple the available measurements with known biological constraints (e.g. stoichiometry). Typically this estimation is done under a static point of view. Therefore, the fluxes so obtained are only valid while the environmental conditions and the cell state remain stable. However, estimating the evolution over time of the metabolic fluxes is valuable to investigate the dynamic behaviour of an organism and also to monitor industrial processes. Although Metabolic Flux Analysis can be successively applied with this aim, this approach has two drawbacks: i) sometimes it cannot be used because there is a lack of measurable fluxes, and ii) the uncertainty of experimental measurements cannot be considered. The Flux Balance Analysis could be used instead, but the assumption of optimal behaviour of the organism brings other difficulties.</p> <p>Results</p> <p>We propose a procedure to estimate the evolution of the metabolic fluxes that is structured as follows: 1) measure the concentrations of extracellular species and biomass, 2) convert this data to measured fluxes and 3) estimate the non-measured fluxes using the Flux Spectrum Approach, a variant of Metabolic Flux Analysis that overcomes the difficulties mentioned above without assuming optimal behaviour. We apply the procedure to a real problem taken from the literature: estimate the metabolic fluxes during a cultivation of CHO cells in batch mode. We show that it provides a reliable and rich estimation of the non-measured fluxes, thanks to considering measurements uncertainty and reversibility constraints. We also demonstrate that this procedure can estimate the non-measured fluxes even when there is a lack of measurable species. In addition, it offers a new method to deal with inconsistency.</p> <p>Conclusion</p> <p>This work introduces a procedure to estimate time-varying metabolic fluxes that copes with the insufficiency of measured species and with its intrinsic uncertainty. The procedure can be used as an off-line analysis of previously collected data, providing an insight into the dynamic behaviour of the organism. It can be also profitable to the on-line monitoring of a running process, mitigating the traditional lack of reliable on-line sensors in industrial environments.</p

State observation of a nonlinear system: Application to (bio)chemical processes

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Continuous-discrete-time observers for a class of uniformly observable systems

International audienceThis chapter addresses the observer design problem for a class of continuous-time dynamical systems with nonuniformly sampled measurements. More specifically, an observer is proposed that runs in continuous-time with an output error correction term that is updated in a mixed continuous-discrete fashion. The proposed observer is actually an impulsive system as it is described by a set of differential equations with instantaneous state impulses corresponding to the measured samples and their estimates. In addition, it is shown that such an impulsive system can be put under the form of a hybrid system composed of a continuous-time high gain observer coupled with an inter-sample output predictor. The proposed observer present two design features that are worth noting: First, the observer calibration is achieved through the tuning of a scalar design parameter. Second, the exponential convergence to zero of the observation error is established under a well-defined condition on the maximum value of the sampling partition diameter. Simulations results dealing with a flexible joint robot arm are given in order to highlight the performance of the proposed observer

Nonlinear estimation strategies for parameter estimation in chemical reactors

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Embryonic expression of AMPK γ subunits and the identification of a novel γ2 transcript variant in adult heart

AMP-activated protein kinase (AMPK), the key sensor and regulator of cellular energy status, is a heterotrimeric enzyme with multiple isoforms for each subunit (α1/α 2; β1/β2; γ1/γ2/γ3). Mutations in PRKAG2, which encodes the γ2 regulatory subunit, cause a cardiomyopathy characterized by hypertrophy and conduction abnormalities. The two reported PRKAG2 transcript variants, γ2-short and γ2-long (encoding 328 and 569 amino acids respectively), are both widely expressed in adult tissues. We show that both γ2 variants are also expressed during cardiogenesis in mouse embryos; expression of the γ3 isoform was also detected unexpectedly at this stage. As neither γ2 transcript is cardiac specific nor differentially expressed during embryogenesis, it is paradoxical that the disease is largely restricted to the heart. However, a recently annotated γ2 transcript, termed γ2-3B as transcription starts at an alternative exon 3b, has been identified; it is spliced in-frame to exon 4 thus generating a protein of 443 residues in mouse with the first 32 residues being unique. It is increasingly expressed in the developing mouse heart and quantitative PCR analysis established that γ2-3B is the major PRKAG2 transcript (~. 60%) in human heart. Antibody against the novel N-terminal sequence showed that γ2-3B is predominantly expressed in the heart where it is the most abundant γ2 protein. The abundance of γ2-3B and its tissue specificity indicate that γ2-3B may have non-redundant role in the heart and hence mediate the predominantly cardiac phenotype caused by PRKAG2 mutations. © 2012 Elsevier Ltd

Production of hepatitis B virus surface antigen in normal and immortalized transgenic mouse hepatocytes

Hepatocytes of transgenic mice containing hepatitis B virus DNA were cultured as primary cells or were immortalized with SV 40. Under defined culture conditions, expression of factors specific for mature hepatocytes and HBsAg could maintained for several weeks. After immortalization with SV 40, although the cells kept several of their differentiated functions, production of HBsAg was lost. Analysis of the RNA revealed the presence of a 1-kb species hybridizing specifically to the X gene in addition to the 2.1-kb SmRNA. (ITA

Nonlinear estimation strategies for parameter estimation in chemical reactors

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