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[Resumen] El desperdicio alimentario supone un gran problema de sostenibilidad. El pescado, en concreto, es un producto especialmente perecedero, degradándose con mucha rapidez cuando la temperatura de almacenamiento no se controla adecuadamente. Los modelos matemáticos son herramientas útiles para predecir la evolución de la calidad del pescado durante el transporte y almacenamiento. Conocer la dinámica de la degradación con antelación también nos permitirá definir estrategias para reducir el desperdicio alimentario y aumentar el valor añadido del pescado. En este trabajo se presenta una nueva metodología para la descripción de la evolución de calidad de filetes de merluza (Merluccius merluccius) envasada en atmósferas modificadas durante el transporte y almacenamiento. Dicha metodología consta de dos partes: un modelo basado en los mecanismos del proceso que describe la evolución de dos de los indicadores de calidad más utilizados (contenido bacteriano y bases volátiles), y un modelo de aprendizaje automático que permite correlacionar dichos indicadores con un indicador sensorial, el QIM (del inglés, Quality Index Method). Para la evolución de las bases volátiles se propone un nuevo modelo basado en la ley de potencias. Además, en este trabajo, los parámetros desconocidos del modelo se estiman utilizando datos experimentales. En el caso de los modelos de aprendizaje automático, se comparan técnicas de redes neuronales y árboles de decisión utilizando diferentes indicadores del error. El modelo combinado supone un avance en la predicción de calidad, ya que permite predecir el QIM a partir, exclusivamente, de datos de temperatura y obtener resultados satisfactorios., [Abstract] Food waste is a significant sustainability problem. Fish, in particular, is a very perishable product. In fact, spoilage increases rapidly when the storage temperature is not adequately controlled. Mathematical models are useful tools to predict fish quality evolution during transport and storage. This knowledge will help to develop strategies to reduce food waste and to increase the product value. In this work, we propose a new methodology to predict the evolution of quality, during transport and storage, of hake fillets packed in modified atmospheres. It consists of two parts: a model based on the process mechanisms to describe the evolution of two highly used quality indicators (bacterial content and volatile bases), and a machine learning model to correlate such indicators with one of the most employed sensory indexes: the Quality Index Method (QIM). Moreover, we propose a Power Law model to describe volatile bases evolution. We estimate the unknown parameters using experimental data. In the machine learning part, we compare random forest models and neural networks using several statistical techniques. Overall, this methodology is an improvement in fish quality prediction because it makes QIM prediction using just temperature data with promising results.

[Resumen] Las autoridades de seguridad alimentaria en los últimos años están demandando avances en el modelado y simulación de la lavado de frutas y verduras que permitan diseñar modos de operación sostenible (mínimo consumo de agua) garantizando la seguridad final del alimento Se requiere, además, evitar que los residuos y patógenos se trasladen del agua de lavado al alimento (contaminación cruzada). En este estudio, se simula el proceso de lavado y desinfección en un tanque industrial en régimen turbulento. Para modelar el transporte de especies (desinfectante, patógenos y materia orgánica), se considera la ecuación de advección-difusión. Para describir la inactivación de los patógenos en el agua, se incluye el modelo de reacción describiendo las interacciones entre las distintas especies. Los resultados revelan que, aunque un incremento en las velocidades del flujo (aumento de la turbulencia) genera mayor homogeneidad en la distribución de desinfectante, el tiempo característico del proceso resulta insuficiente para inactivar eficazmente los patógenos en el agua., [Abstract] Food safety authorities in recent years are demanding advances in modeling and simulating the washing of fruits and vegetables to support the development of sustainable operation designs (minimum water use) and guaranteeing final product safety. It is required, moreover, to avoid the transference of residues and pathogens from the wash water to the food (cross-contamination). In this study, we simulate an industrial washing and disinfection process in a tank in a turbulent regime. We consider the advectiondiffusion equation to model the species (disinfectant, pathogens, and organic matter) transport, and we include the reaction model between the different species to describe pathogen inactivation in the wash water. The results reveal that, although increasing flow velocities (increased turbulence) generates greater homogeneity in the disinfectant distribution, the characteristic time of the process becomes insufficient to inactivate pathogens in the water.

[Resumen] El rápido avance de la resistencia bacteriana a los antimicrobianos continúa fomentando la investigación en torno al modelado matemático de los mecanismos que conducen a la emergencia, transmisión y selección de resistencia. El enfoque más extendido para explicar las dinámicas de una población tratada con antimicrobiano consiste en clasificar las bacterias en sensibles y resistentes. Sin embargo, en la realidad existen infinidad de grados de resistencia intermedios en la población, lo que se conoce como heterorresistencia. En este trabajo, se propone un modelo matemático para explicar las dinámicas de una población heterorresistente, introduciendo el grado de resistencia como una variable aleatoria indicadora de la efectividad del antimicrobiano sobre la población. Se analizan las capacidades del modelo y se establecen, además, su observabilidad e identificabilidad estructurales., [Abstract] The rapid development of bacterial antimicrobial resistance still promotes the research on mathematical modelling of the mechanisms leading to the emergence, transmission and selection of resistance. The most common approach to explain the dynamics of an antimicrobial-treated population is to classify bacteria into sensitive and resistant. In reality, however, we can find infinite resistance degrees in the population, known as heteroresistance. In this paper, we propose a mathematical model to explain the dynamics of a heteroresistant population, introducing the resistance degree as a random variable indicating the effectiveness of the antimicrobial. We analyse the model’s capabilities and establish its structural observability and identifiability.

[Resumen] El morbidostato es un dispositivo de control asistido por ordenador diseñado para estudiar, en tiempo real, la dinámica fenotípica y genotípica de la adaptación y resistencia bacterianas. Dicho sistema incorpora un mecanismo encargado de activar o desactivar el flujo de cierta sustancia antimicrobiana hacia una serie de microreactores, dependiendo de mediciones en línea de la densidad óptica de la población, con el fin de mantener una concentración bacteriana estable en los diferentes cultivos. Así, por medio del componente de control, el morbidostato ejerce una presión constante sobre la selección de las bacterias y su resistencia a la sustancia antimicrobiana que se estudia. La ley de control a integrar en el morbidostato que se propone habitualmente en la literatura consiste en un algoritmo muy básico basado en dos reglas condicionales para determinar cuando se hace necesaria la incorporación de antimicrobiano al sistema. En este trabajo, se muestran dos resultados principales en este contexto: (1) desempeño de simulaciones para la extracción de condiciones bajo las cuales el control del morbidostato no logra estabilizar la población de microorganismos en la concentración objetivo y (2) el control, en tiempo real con estabilización rápida al punto de consigna, de la población bacteriana cuando se aplican técnicas de control predictivo basado en modelo., [Abstract] A morbidostat is a computer-aided control device to study phenotypic and genotypicreal-time dynamics of bacteria adaptation and resistance. This system includes a control mechanism to activate or deactivate the inflow of an antimicrobial substance into a series of microreactors, depending on online measurements of the population’s optical density, thus maintaining a steadystate bacterial concentration across the different cultures. In other words, the morbidostat actuates through the control component to maintain a constant drug selection pressure sufficient for bacterial adaptation or resistance to the antimicrobial substance under study. The morbidostat control law used so far in the literature consists of a fairly simple algorithm incorporating two conditional rules to determine when the addition of the antimicrobial to the system is necessary. In this work, we show two main results in this context: (1) to carry out simulations and extract conditions under which simple control in morbidostat cannot stabilize the concentration of microorganisms to the target concentration and (2) the realtime control, with stabilization to the target point, of the bacterial concentration using model predictive control.

[Resumen] En la industria alimentaria la calidad y la seguridad del alimento, así como los procesos implicados en su producción, envasado y transporte, se optimizan acudiendo a la microbiología predictiva. Esta disciplina modela el comportamiento de microorganismos, tales como bacterias, empleando modelos primarios para describir su crecimiento. Uno de los mayores retos en este contexto es modelar y simular el crecimiento cuando el número inicial de bacterias (inóculo) es reducido, ya que la población se comporta estocásticamente. Existen distintas alternativas de modelado, dependiendo de (1) el grado de detalle de la solución requerida, (2) los tiempos de cálculo y (3) la facilidad de calibración de sus parámetros. En este trabajo se comparan las soluciones y tiempos de cálculo, a la vez que se discute la identificabilidad estructural, cuando se aborda el problema desde una escala microscópica, con modelado basado en individuos, o desde una escala mesoscópica, mediante la derivación de la equivalente ecuación de Fokker–Planck modificada., [Abstract] Quality and safety in the food industry, as well as the processes involved in the production, packaging, and transport of food, may be optimised using predictive microbiology. This discipline models the behaviour of microorganisms and uses the socalled primary models to describe bacterial growth. One of the main challenges consists of explaining and simulating the growth when the number of initial bacteria (inoculum) is reduced because of the stochastic behaviour. There exist different alternatives to modelling such stochastic processes depending on: (1) the required level of detail for the solution; (2) the computational time; and (3) the possibility of estimating parameters from fast and inexpensive measurements. In this work, we compare the solutions, computational times and structural identifiability obtained using different alternatives: (1) microscopic scale considering individual-based models; and (2) mesoscopic scale considering the modified Fokker-Planck equation.

On‐land transport/storage of fresh fishery products (FFP) for up to 3 days in ‘tubs’ of three‐layered poly‐ethylene filled with freshwater and ice was compared to the currently authorised practice (fish boxes of high‐density poly‐ethylene filled with ice). The impact on the survival and growth of biological hazards in fish and the histamine production in fish species associated with a high amount of histidine was assessed. In different modelling scenarios, the FFP are stored on‐board in freshwater or seawater/ice (in tubs) and once on‐land they are ‘handled’ (i.e. sorted or gutted and/or filleted) and transferred to either tubs or boxes. The temperature of the FFP was assumed to be the most influential factor affecting relevant hazards. Under reasonably foreseeable ‘abusive’ scenarios and using a conservative modelling approach, the growth of the relevant hazards (i.e. Listeria monocytogenes, Aeromonas spp. and non‐proteolytic Clostridium botulinum), is expected to be <0.2 log10 units higher in tubs than in boxes after 3 days when the initial temperature of the fish is 0°C (‘keeping’ process). Starting at 7°C (‘cooling‐keeping’ process), the expected difference in the growth potential is higher (<1 log10 for A. hydrophila and <0.5 log10 for the other two hazards) due to the poorer cooling capacity of water and ice (tub) compared with ice (box). The survival of relevant hazards is not or is negligibly impacted. Histamine formation due to growth of Morganella psychrotolerans under the ‘keeping’ or ‘cooling‐keeping’ process can be up to 0.4 ppm and 1.5 ppm higher, respectively, in tubs as compared to boxes after 3 days, without reaching the legal limit of 100 ppm. The water uptake associated with the storage of the FFP in tubs (which may be up to 6%) does not make a relevant contribution to the differences in microbial growth potential compared to boxes.

[Abstract] Common dynamic models of active packaging are focused on the mass transfer of the antimicrobial agents. Nevertheless, the interaction of the antimicrobial agent with the food microorganisms is usually neglected, despite being critical to optimize the food safety and quality. In this work, we propose a dynamic model simulating the dynamics of carvacrol and its inhibition by Listeria monocytogenes in an active packaging system. Carvacrol is an antimicrobial agent allowed as a food additive and Listeria monocytogenes is the major psychrotrophic pathogen in food. The model can be exploited to study different aspects of the food quality and safety, such for example the maximum load of Listeria before packaging and the concentration of carvacrol to guarantee food quality and safety standards., [Resumen] Los modelos dinámicos comunes de envasado activo se centran en la transferencia masiva de los agentes antimicrobianos. Sin embargo, la interacción del agente antimicrobiano con los microorganismos de los alimentos suele descuidarse, a pesar de ser crítica para optimizar la seguridad y la calidad de los alimentos. En este trabajo, proponemos un modelo dinámico que simula la dinámica del carvacrol y su inhibición por Listeria monocytogenes en un sistema de empaquetado activo. El carvacrol es un agente antimicrobiano permitido como aditivo alimentario y Listeria monocytogenes es el principal patógeno psicotrófico en los alimentos. El modelo puede ser explotado para estudiar diferentes aspectos de la calidad y seguridad de los alimentos, como por ejemplo la carga máxima de Listeria antes del envasado y la concentración de carvacrol para garantizar los estándares de calidad y seguridad de los alimentos.

Calcium ions act as messengers in a broad range of processes such as learning, apoptosis, and muscular movement. The transient profile and the temporal accumulation of calcium signals have been suggested as the two main characteristics in which calcium cues encode messages to be forwarded to downstream pathways. We address the analytical quantification of calcium temporal-accumulation in a long, thin section of a nonexcitable cell by solving a boundary value problem. In these expressions we note that the cytosolic Ca2þ accumulation is independent of every intracellular calcium flux and depends on the Ca2þ exchange across the membrane, cytosolic calcium diffusion, geometry of the cell, extracellular calcium perturbation, and initial concentrations. In particular, we analyse the time-integrated response of cytosolic calcium due to i) a localised initial concentration of cytosolic calcium and ii) transient extracellular perturbation of calcium. In these scenarios, we conclude that i) the range of calcium progression is confined to the vicinity of the initial concentration, thereby creating calcium microdomains; and ii) we observe a low-pass filtering effect in the response driven by extracellular Ca2þ perturbations. Additionally, we note that our methodology can be used to analyse a broader range of stimuli and scenarios.

Calcium ions act as messengers in a broad range of processes such as learning, apoptosis, and muscular movement. The transient profile and the temporal accumulation of calcium signals have been suggested as the two main characteristics in which calcium cues encode messages to be forwarded to downstream pathways. We address the analytical quantification of calcium temporal-accumulation in a long, thin section of a nonexcitable cell by solving a boundary value problem. In these expressions we note that the cytosolic Ca2þ accumulation is independent of every intracellular calcium flux and depends on the Ca2þ exchange across the membrane, cytosolic calcium diffusion, geometry of the cell, extracellular calcium perturbation, and initial concentrations. In particular, we analyse the time-integrated response of cytosolic calcium due to i) a localised initial concentration of cytosolic calcium and ii) transient extracellular perturbation of calcium. In these scenarios, we conclude that i) the range of calcium progression is confined to the vicinity of the initial concentration, thereby creating calcium microdomains; and ii) we observe a low-pass filtering effect in the response driven by extracellular Ca2þ perturbations. Additionally, we note that our methodology can be used to analyse a broader range of stimuli and scenarios.

Parkinsonian and essential tremor can often be effectively treated by deep brain stimulation. We propose a novel explanation for the mechanism by which this technique ameliorates tremor: a reduction of the delay in the relevant motor control loops via preferential antidromic blockade of slow axons. The antidromic blockade is preferential because the pulses more rapidly clear fast axons, and the distribution of axonal diameters, and therefore velocities, in the involved tracts, is sufficiently long-tailed to make this effect quite significant. The preferential blockade of slow axons, combined with gain adaptation, results in a reduction of the mean delay in the motor control loop, which serves to stabilize the feedback system, thus ameliorating tremor. This theory, without any tuning, accounts for several previously perplexing phenomena, and makes a variety of novel predictions.

Parkinsonian and essential tremor can often be effectively treated by deep brain stimulation. We propose a novel explanation for the mechanism by which this technique ameliorates tremor: a reduction of the delay in the relevant motor control loops via preferential antidromic blockade of slow axons. The antidromic blockade is preferential because the pulses more rapidly clear fast axons, and the distribution of axonal diameters, and therefore velocities, in the involved tracts, is sufficiently long-tailed to make this effect quite significant. The preferential blockade of slow axons, combined with gain adaptation, results in a reduction of the mean delay in the motor control loop, which serves to stabilize the feedback system, thus ameliorating tremor. This theory, without any tuning, accounts for several previously perplexing phenomena, and makes a variety of novel predictions.

The physiology of voltage gated ion channels is complex and insights into their gating mechanism is incomplete. Their function is best represented by Markov models with relatively large number of distinct states that are connected by thermodynamically feasible transitions. On the other hand, popular models such as the one of Hodgkin and Huxley have empirical assumptions that are generally unrealistic. Experimental protocols often dictate the number of states in proposed Markov models, thus creating disagreements between various observations on the same channel. Here we aim to propose a limit to the minimum number of states required to model ion channels by employing a paradigm to define stationary conductance in a class of ion-channels. A simple expression is generated using concepts in elementary thermodynamics applied to protein conformational transitions. Further, it matches well many published channel current-voltage characteristics and parameters of the model are found to be identifiable and easily determined from usual experimental protocols.

The physiology of voltage gated ion channels is complex and insights into their gating mechanism is incomplete. Their function is best represented by Markov models with relatively large number of distinct states that are connected by thermodynamically feasible transitions. On the other hand, popular models such as the one of Hodgkin and Huxley have empirical assumptions that are generally unrealistic. Experimental protocols often dictate the number of states in proposed Markov models, thus creating disagreements between various observations on the same channel. Here we aim to propose a limit to the minimum number of states required to model ion channels by employing a paradigm to define stationary conductance in a class of ion-channels. A simple expression is generated using concepts in elementary thermodynamics applied to protein conformational transitions. Further, it matches well many published channel current-voltage characteristics and parameters of the model are found to be identifiable and easily determined from usual experimental protocols.

The IGF-1 mediated AKT/mTOR pathway has been recently proposed as mediator of skeletal muscle growth and a positive feedback between Akt and mTOR was suggested to induce homogenous growth signals along the whole spatial extension of such long cells. Here we develop two biologically justied approximations which we study under the presence of four dierent initial conditions that describe dierent paradigms of IGF-1 receptor{induced Akt/mTOR activation. In rst scenario the activation of the feedback cascade was assumed to be mild or protein turnover considered to be high. In turn, in the second scenario the transcriptional regulation was assumed to maintain dened levels of inactive pro{enzymes. For both scenarios, we were able to obtain closed{form formulas for growth signal progression in time and space and found that a localised initial signal maintains its Gaussian shape, but gets delocalised and exponentially degraded. Importantly, mathematical treatment of the reaction diusion system revealed that diusion ltered out high frequencies of spatially periodic initiator signals suggesting that the muscle cell is robust against uctuations in spatial receptor expression or activation. However, neither scenario was consistent with the presence of stably travelling signal waves. Our study highlights the role of feedback loops in spatiotemporal signal progression and results can be applied to studies in cell proliferation, cell dierentiation and cell death in other spatially extended cells.

In this work a robust nonlinear model predictive controller for nonlinear convection-diusion-reaction systems is presented. The controller makes use of a collection of reduced order approximations of the plant (models) reconstructed on-line by projection methods on POD (Proper Orthogonal Decomposition) basis functions. The model selection and model update step is based on a sucient condition that determines the maximum allowable process-model mismatch to guarantee stable control performance despite process uncertainty and disturbances. Proofs on the existence of a sequence of feasible approximations and control stability are given. Since plant approximations are built on-line based on actual measurements the proposed controller can be interpreted as a multi-model nonlinear predictive control (MMPC). The performance of the MMPC strategy is illustrated by simulation experiments on a problem that involves reactant concentration control of a tubular reactor with recycle.

In this work a robust nonlinear model predictive controller for nonlinear convection-diusion-reaction systems is presented. The controller makes use of a collection of reduced order approximations of the plant (models) reconstructed on-line by projection methods on POD (Proper Orthogonal Decomposition) basis functions. The model selection and model update step is based on a sucient condition that determines the maximum allowable process-model mismatch to guarantee stable control performance despite process uncertainty and disturbances. Proofs on the existence of a sequence of feasible approximations and control stability are given. Since plant approximations are built on-line based on actual measurements the proposed controller can be interpreted as a multi-model nonlinear predictive control (MMPC). The performance of the MMPC strategy is illustrated by simulation experiments on a problem that involves reactant concentration control of a tubular reactor with recycle.

The IGF-1 mediated AKT/mTOR pathway has been recently proposed as mediator of skeletal muscle growth and a positive feedback between Akt and mTOR was suggested to induce homogenous growth signals along the whole spatial extension of such long cells. Here we develop two biologically justied approximations which we study under the presence of four dierent initial conditions that describe dierent paradigms of IGF-1 receptor{induced Akt/mTOR activation. In rst scenario the activation of the feedback cascade was assumed to be mild or protein turnover considered to be high. In turn, in the second scenario the transcriptional regulation was assumed to maintain dened levels of inactive pro{enzymes. For both scenarios, we were able to obtain closed{form formulas for growth signal progression in time and space and found that a localised initial signal maintains its Gaussian shape, but gets delocalised and exponentially degraded. Importantly, mathematical treatment of the reaction diusion system revealed that diusion ltered out high frequencies of spatially periodic initiator signals suggesting that the muscle cell is robust against uctuations in spatial receptor expression or activation. However, neither scenario was consistent with the presence of stably travelling signal waves. Our study highlights the role of feedback loops in spatiotemporal signal progression and results can be applied to studies in cell proliferation, cell dierentiation and cell death in other spatially extended cells.

Deep brain stimulation (DBS) has been used to ameliorate essential and Parkinsonian tremor, however the detailed mechanism by which tremor reduction is achieved remains unclear. We hypothesize that DBS works by reducing time delays in the feedback paths of the motor control loops. In particular, we suggest that antidromic activation of axonal pathways induced by stimulation will preferentially block axons with longer propagation times, reducing time delays in neuronal motor circuits in a stabilising manner. We demonstrate the plausibility of this hypothesis using two simple computational models which account for a variety of experimental results, and allow us to makes a number of testable predictions.

Deep brain stimulation (DBS) has been used to ameliorate essential and Parkinsonian tremor, however the detailed mechanism by which tremor reduction is achieved remains unclear. We hypothesize that DBS works by reducing time delays in the feedback paths of the motor control loops. In particular, we suggest that antidromic activation of axonal pathways induced by stimulation will preferentially block axons with longer propagation times, reducing time delays in neuronal motor circuits in a stabilising manner. We demonstrate the plausibility of this hypothesis using two simple computational models which account for a variety of experimental results, and allow us to makes a number of testable predictions.

This work presents a methodology which exploits the underlying biochemical structure of bioprocesses to estimate concentrations in aerobic fermenters from oxygen measurements. Although a number of estimators have been proposed over the years in the literature, the methodology proposed in this work is able to operate in transient conditions while does not require the knowledge of the growth kinetics. In addition, it can be also applied to fermenters where the spatial distribution of the concentrations is relevant. In this case, we propose a systematic approach to optimally locate the sensors based on the use of reduced order models. This method allows the reconstruction of the oxygen concentrations from a limited number of sensors. Finally, the methodology proposed will be illustrated on a horizontal tubular reactor for the production of gluconic acid by free-growth of Aspergillus niger.

Deep brain stimulation (DBS) has been used to ameliorate essential and Parkinsonian tremor, however the detailed mechanism by which tremor reduction is achieved remains unclear. We hypothesize that DBS works by reducing time delays in the feedback paths of the motor control loops. In particular, we suggest that antidromic activation of axonal pathways induced by stimulation will preferentially block axons with longer propagation times, reducing time delays in neuronal motor circuits in a stabilising manner. We demonstrate the plausibility of this hypothesis using two simple computational models which account for a variety of experimental results, and allow us to makes a number of testable predictions.

This work presents a methodology which exploits the underlying biochemical structure of bioprocesses to estimate concentrations in aerobic fermenters from oxygen measurements. Although a number of estimators have been proposed over the years in the literature, the methodology proposed in this work is able to operate in transient conditions while does not require the knowledge of the growth kinetics. In addition, it can be also applied to fermenters where the spatial distribution of the concentrations is relevant. In this case, we propose a systematic approach to optimally locate the sensors based on the use of reduced order models. This method allows the reconstruction of the oxygen concentrations from a limited number of sensors. Finally, the methodology proposed will be illustrated on a horizontal tubular reactor for the production of gluconic acid by free-growth of Aspergillus niger.

[ES] En este trabajo se presenta una librería de unidades de operación en EcosimPro para la simulación, optimización y control de procesos térmicos en la industria alimentaria. Las plantas de procesamiento de alimentos son buenos ejemplos de sistemas híbridos donde las dinámicas continuas no lineales están acopladas con eventos discretos. El entorno EcosimPro permite trabajar con dichos sistemas de forma eficiente e incorpora una interfaz gráfica de usuario (EcoDiagram) que facilita el manejo de modelos matemáticos complejos a los usuarios no expertos. Para la programación de dichos modelos en el entorno EcosimPro se ha seguido el paradigma de la programación orientada a objetos (POO) que incluye características como la reutilización, herencia, abstracción o encapsulamiento. La librería de componentes se puede utilizar, por ejemplo, para analizar el efecto de tecnologías alternativas en la producción o para diseñar nuevas políticas de operación en el caso de condiciones de suministro fluctuantes. Aunque este trabajo se centra en procesos de la industria conservera, se pueden añadir otras unidades para la simulación de procesos como la pasteurización o secado sin necesidad de modificar los componentes ya existentes. Los modelos han sido validados utilizando una planta piloto instalada en el IIM-CSIC aunque pueden ser aplicados a otras con diferentes especificaciones. Finalmente, algunas de las ventajas de disponer de esta librería de componentes se ilustran en una serie de ejemplos de uso., [EN] In this work a library of operation units for the simulation, optimisation and control of thermal processes in the food industry is presented. Food processing plants are good examples of hybrid systems where continuous dynamics are coupled with discrete events. The library was developed in EcosimPro since it is able to efficiently handle hybrid systems. In addition, it includes a user friendly graphical interface (Ecodiagram) which makes mathematical models accessible to non expert users. The paradigm of object oriented programming (OOP), which includes features such as the inheritance, abstraction or encapsulation, was employed to construct such models in EcosimPro. The library can be employed, for instance, to analyse the effect of alternative production technologies or to design new operation policies in the event of fluctuating supply conditions. Although this work is focused on processes of the canned food industry, new units can be added in order to simulate other processes such as pasteurization or drying without the need of modifying the existing components. The models have been validated using a pilot plant installed at the IIM-CSIC although they can be applied to other plants with different specifications. Finally, some advantages of the library are illustrated through a number of case studies.

[ES] En este trabajo se presenta una librería de unidades de operación en EcosimPro para la simulación, optimización y control de procesos térmicos en la industria alimentaria. Las plantas de procesamiento de alimentos son buenos ejemplos de sistemas híbridos donde las dinámicas continuas no lineales están acopladas con eventos discretos. El entorno EcosimPro permite trabajar con dichos sistemas de forma eficiente e incorpora una interfaz gráfica de usuario (EcoDiagram) que facilita el manejo de modelos matemáticos complejos a los usuarios no expertos. Para la programación de dichos modelos en el entorno EcosimPro se ha seguido el paradigma de la programación orientada a objetos (POO) que incluye características como la reutilización, herencia, abstracción o encapsulamiento. La librería de componentes se puede utilizar, por ejemplo, para analizar el efecto de tecnologías alternativas en la producción o para diseñar nuevas políticas de operación en el caso de condiciones de suministro fluctuantes. Aunque este trabajo se centra en procesos de la industria conservera, se pueden añadir otras unidades para la simulación de procesos como la pasteurización o secado sin necesidad de modificar los componentes ya existentes. Los modelos han sido validados utilizando una planta piloto instalada en el IIM-CSIC aunque pueden ser aplicados a otras con diferentes especificaciones. Finalmente, algunas de las ventajas de disponer de esta librería de componentes se ilustran en una serie de ejemplos de uso., [EN] In this work a library of operation units for the simulation, optimisation and control of thermal processes in the food industry is presented. Food processing plants are good examples of hybrid systems where continuous dynamics are coupled with discrete events. The library was developed in EcosimPro since it is able to efficiently handle hybrid systems. In addition, it includes a user friendly graphical interface (Ecodiagram) which makes mathematical models accessible to non expert users. The paradigm of object oriented programming (OOP), which includes features such as the inheritance, abstraction or encapsulation, was employed to construct such models in EcosimPro. The library can be employed, for instance, to analyse the effect of alternative production technologies or to design new operation policies in the event of fluctuating supply conditions. Although this work is focused on processes of the canned food industry, new units can be added in order to simulate other processes such as pasteurization or drying without the need of modifying the existing components. The models have been validated using a pilot plant installed at the IIM-CSIC although they can be applied to other plants with different specifications. Finally, some advantages of the library are illustrated through a number of case studies.

[ES] En este trabajo se presenta una librería de unidades de operación en EcosimPro para la simulación, optimización y control de procesos térmicos en la industria alimentaria. Las plantas de procesamiento de alimentos son buenos ejemplos de sistemas híbridos donde las dinámicas continuas no lineales están acopladas con eventos discretos. El entorno EcosimPro permite trabajar con dichos sistemas de forma eficiente e incorpora una interfaz gráfica de usuario (EcoDiagram) que facilita el manejo de modelos matemáticos complejos a los usuarios no expertos. Para la programación de dichos modelos en el entorno EcosimPro se ha seguido el paradigma de la programación orientada a objetos (POO) que incluye características como la reutilización, herencia, abstracción o encapsulamiento. La librería de componentes se puede utilizar, por ejemplo, para analizar el efecto de tecnologías alternativas en la producción o para diseñar nuevas políticas de operación en el caso de condiciones de suministro fluctuantes. Aunque este trabajo se centra en procesos de la industria conservera, se pueden añadir otras unidades para la simulación de procesos como la pasteurización o secado sin necesidad de modificar los componentes ya existentes. Los modelos han sido validados utilizando una planta piloto instalada en el IIM-CSIC aunque pueden ser aplicados a otras con diferentes especificaciones. Finalmente, algunas de las ventajas de disponer de esta librería de componentes se ilustran en una serie de ejemplos de uso., [EN] In this work a library of operation units for the simulation, optimisation and control of thermal processes in the food industry is presented. Food processing plants are good examples of hybrid systems where continuous dynamics are coupled with discrete events. The library was developed in EcosimPro since it is able to efficiently handle hybrid systems. In addition, it includes a user friendly graphical interface (Ecodiagram) which makes mathematical models accessible to non expert users. The paradigm of object oriented programming (OOP), which includes features such as the inheritance, abstraction or encapsulation, was employed to construct such models in EcosimPro. The library can be employed, for instance, to analyse the effect of alternative production technologies or to design new operation policies in the event of fluctuating supply conditions. Although this work is focused on processes of the canned food industry, new units can be added in order to simulate other processes such as pasteurization or drying without the need of modifying the existing components. The models have been validated using a pilot plant installed at the IIM-CSIC although they can be applied to other plants with different specifications. Finally, some advantages of the library are illustrated through a number of case studies.

[ES] En este trabajo se presenta una librería de unidades de operación en EcosimPro para la simulación, optimización y control de procesos térmicos en la industria alimentaria. Las plantas de procesamiento de alimentos son buenos ejemplos de sistemas híbridos donde las dinámicas continuas no lineales están acopladas con eventos discretos. El entorno EcosimPro permite trabajar con dichos sistemas de forma eficiente e incorpora una interfaz gráfica de usuario (EcoDiagram) que facilita el manejo de modelos matemáticos complejos a los usuarios no expertos. Para la programación de dichos modelos en el entorno EcosimPro se ha seguido el paradigma de la programación orientada a objetos (POO) que incluye características como la reutilización, herencia, abstracción o encapsulamiento. La librería de componentes se puede utilizar, por ejemplo, para analizar el efecto de tecnologías alternativas en la producción o para diseñar nuevas políticas de operación en el caso de condiciones de suministro fluctuantes. Aunque este trabajo se centra en procesos de la industria conservera, se pueden añadir otras unidades para la simulación de procesos como la pasteurización o secado sin necesidad de modificar los componentes ya existentes. Los modelos han sido validados utilizando una planta piloto instalada en el IIM-CSIC aunque pueden ser aplicados a otras con diferentes especificaciones. Finalmente, algunas de las ventajas de disponer de esta librería de componentes se ilustran en una serie de ejemplos de uso., [EN] In this work a library of operation units for the simulation, optimisation and control of thermal processes in the food industry is presented. Food processing plants are good examples of hybrid systems where continuous dynamics are coupled with discrete events. The library was developed in EcosimPro since it is able to efficiently handle hybrid systems. In addition, it includes a user friendly graphical interface (Ecodiagram) which makes mathematical models accessible to non expert users. The paradigm of object oriented programming (OOP), which includes features such as the inheritance, abstraction or encapsulation, was employed to construct such models in EcosimPro. The library can be employed, for instance, to analyse the effect of alternative production technologies or to design new operation policies in the event of fluctuating supply conditions. Although this work is focused on processes of the canned food industry, new units can be added in order to simulate other processes such as pasteurization or drying without the need of modifying the existing components. The models have been validated using a pilot plant installed at the IIM-CSIC although they can be applied to other plants with different specifications. Finally, some advantages of the library are illustrated through a number of case studies.

[ES] En este trabajo se presenta una librería de unidades de operación en EcosimPro para la simulación, optimización y control de procesos térmicos en la industria alimentaria. Las plantas de procesamiento de alimentos son buenos ejemplos de sistemas híbridos donde las dinámicas continuas no lineales están acopladas con eventos discretos. El entorno EcosimPro permite trabajar con dichos sistemas de forma eficiente e incorpora una interfaz gráfica de usuario (EcoDiagram) que facilita el manejo de modelos matemáticos complejos a los usuarios no expertos. Para la programación de dichos modelos en el entorno EcosimPro se ha seguido el paradigma de la programación orientada a objetos (POO) que incluye características como la reutilización, herencia, abstracción o encapsulamiento. La librería de componentes se puede utilizar, por ejemplo, para analizar el efecto de tecnologías alternativas en la producción o para diseñar nuevas políticas de operación en el caso de condiciones de suministro fluctuantes. Aunque este trabajo se centra en procesos de la industria conservera, se pueden añadir otras unidades para la simulación de procesos como la pasteurización o secado sin necesidad de modificar los componentes ya existentes. Los modelos han sido validados utilizando una planta piloto instalada en el IIM-CSIC aunque pueden ser aplicados a otras con diferentes especificaciones. Finalmente, algunas de las ventajas de disponer de esta librería de componentes se ilustran en una serie de ejemplos de uso., [EN] In this work a library of operation units for the simulation, optimisation and control of thermal processes in the food industry is presented. Food processing plants are good examples of hybrid systems where continuous dynamics are coupled with discrete events. The library was developed in EcosimPro since it is able to efficiently handle hybrid systems. In addition, it includes a user friendly graphical interface (Ecodiagram) which makes mathematical models accessible to non expert users. The paradigm of object oriented programming (OOP), which includes features such as the inheritance, abstraction or encapsulation, was employed to construct such models in EcosimPro. The library can be employed, for instance, to analyse the effect of alternative production technologies or to design new operation policies in the event of fluctuating supply conditions. Although this work is focused on processes of the canned food industry, new units can be added in order to simulate other processes such as pasteurization or drying without the need of modifying the existing components. The models have been validated using a pilot plant installed at the IIM-CSIC although they can be applied to other plants with different specifications. Finally, some advantages of the library are illustrated through a number of case studies.

[ES] En este trabajo se presenta una librería de unidades de operación en EcosimPro para la simulación, optimización y control de procesos térmicos en la industria alimentaria. Las plantas de procesamiento de alimentos son buenos ejemplos de sistemas híbridos donde las dinámicas continuas no lineales están acopladas con eventos discretos. El entorno EcosimPro permite trabajar con dichos sistemas de forma eficiente e incorpora una interfaz gráfica de usuario (EcoDiagram) que facilita el manejo de modelos matemáticos complejos a los usuarios no expertos. Para la programación de dichos modelos en el entorno EcosimPro se ha seguido el paradigma de la programación orientada a objetos (POO) que incluye características como la reutilización, herencia, abstracción o encapsulamiento. La librería de componentes se puede utilizar, por ejemplo, para analizar el efecto de tecnologías alternativas en la producción o para diseñar nuevas políticas de operación en el caso de condiciones de suministro fluctuantes. Aunque este trabajo se centra en procesos de la industria conservera, se pueden añadir otras unidades para la simulación de procesos como la pasteurización o secado sin necesidad de modificar los componentes ya existentes. Los modelos han sido validados utilizando una planta piloto instalada en el IIM-CSIC aunque pueden ser aplicados a otras con diferentes especificaciones. Finalmente, algunas de las ventajas de disponer de esta librería de componentes se ilustran en una serie de ejemplos de uso., [EN] In this work a library of operation units for the simulation, optimisation and control of thermal processes in the food industry is presented. Food processing plants are good examples of hybrid systems where continuous dynamics are coupled with discrete events. The library was developed in EcosimPro since it is able to efficiently handle hybrid systems. In addition, it includes a user friendly graphical interface (Ecodiagram) which makes mathematical models accessible to non expert users. The paradigm of object oriented programming (OOP), which includes features such as the inheritance, abstraction or encapsulation, was employed to construct such models in EcosimPro. The library can be employed, for instance, to analyse the effect of alternative production technologies or to design new operation policies in the event of fluctuating supply conditions. Although this work is focused on processes of the canned food industry, new units can be added in order to simulate other processes such as pasteurization or drying without the need of modifying the existing components. The models have been validated using a pilot plant installed at the IIM-CSIC although they can be applied to other plants with different specifications. Finally, some advantages of the library are illustrated through a number of case studies.

In this work, the dissipative nature of spatially distributed process systems is exploited to develop efficient exponential state observers based on a low dimensional dynamic representation of the original set of partial differential equations. The approach we suggest combines standard observer design techniques for reactors where the reaction rates are unknown with efficient model reduction methodologies based on projection of the original concentration and temperature fields on low dimensional subspaces capturing the slow dynamics of the process. The global exponential stability of the resulting observer is derived combining classical Lyapunov analysis with a transformation that allows us to obtain a diffusion system from a diffusionconvection system. In addition aspects related to the location of sensors and their influence on the ability to reconstruct the necessary fields to feed the observer will also be considered.

In this work, the dissipative nature of spatially distributed process systems is exploited to develop efficient exponential state observers based on a low dimensional dynamic representation of the original set of partial differential equations. The approach we suggest combines standard observer design techniques for reactors where the reaction rates are unknown with efficient model reduction methodologies based on projection of the original concentration and temperature fields on low dimensional subspaces capturing the slow dynamics of the process. The global exponential stability of the resulting observer is derived combining classical Lyapunov analysis with a transformation that allows us to obtain a diffusion system from a diffusionconvection system. In addition aspects related to the location of sensors and their influence on the ability to reconstruct the necessary fields to feed the observer will also be considered.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

En este artículo se presenta un modelo neuroborroso de la temperatura de un autoclave industrial, usado para estrategias basadas en Control Predictivo No-Lineal, permitiendo un bajo coste computacional, las cuales son aptas para implementarse en un autómata programable (PLC) de gama media, muy común en la industria. El modelo se ha validado con datos experimentales obtenidos en una planta real.

In this work, the dissipative nature of spatially distributed bioprocess systems is exploited to develop efficient state observers based on a low dimensional dynamic representation of the original set of partial differential equations. The approach we suggest combines standard observer design techniques for bioreactors with efficient model reduction methodologies based on projection of the original concentration fields on low dimensional subspaces capturing the slow dynamics of the process. Aspects related with the location of sensors and their influence on the ability to reconstruct concentration fields will also be considered. Finally, the different aspects of the methodology, as well as the efficiency of the resulting observers will be illustrated on a case study of industrial interest, namely a tubular bioreactor producing gluconic acid by Aspergillus Niger.

In this work, the dissipative nature of spatially distributed bioprocess systems is exploited to develop efficient state observers based on a low dimensional dynamic representation of the original set of partial differential equations. The approach we suggest combines standard observer design techniques for bioreactors with efficient model reduction methodologies based on projection of the original concentration fields on low dimensional subspaces capturing the slow dynamics of the process. Aspects related with the location of sensors and their influence on the ability to reconstruct concentration fields will also be considered. Finally, the different aspects of the methodology, as well as the efficiency of the resulting observers will be illustrated on a case study of industrial interest, namely a tubular bioreactor producing gluconic acid by Aspergillus Niger.