A set-membership state estimation algorithm based on DC programming

This paper presents a new approach to guaranteed state estimation for nonlinear discrete-time systems with a bounded description of noise and parameters. The sets of states that are consistent with the evolution of the system, the measured outputs and bounded noise and parameters are represented by zonotopes. DC programming and intersection operations are used to obtain a tight bound. An example is given to illustrate the proposed algorithm.Ministerio de Ciencia y Tecnología DPI2006-15476-C02-01Ministerio de Ciencia y Tecnología DPI2007-66718-C04-01

On the computation of invariant sets for constrained nonlinear systems: An interval arithmetic approach

This paper deals with the computation of control invariant sets for constrained nonlinear systems. The proposed approach is based on the computation of an inner approximation of the one step set, that is, the set of states that can be steered to a given target set by an admissible control action. Based on this procedure, control invariant sets can be computed by recursion. We present a method for the computation of the one-step set using interval arithmetic. The proposed specialized branch and bound algorithm provides an inner approximation with a given bound of the error; this makes it possible to achieve a trade off between accuracy of the computed set and computational burden. Furthermore an algorithm to approximate the one step set by an inner bounded polyhedron is also presented; this allows us to relax the complexity of the obtained set, and to make easier the recursion and storage of the sets.Ministerio de Ciencia y Tecnología DPI2004-07444-c04-01Ministerio de Ciencia y Tecnología DPI2003-04375-c03-01Ministerio de Ciencia y Tecnología DPI2003-07146-c02-0

Calculating the profits of an economic MPC applied to CSP plants with thermal storage system

Electricity producers participating in a day-ahead energy market aim to maximize profits derived from electricity sales. The daily generation schedule has to be offered in advance, usually the previous day before a certain moment in time. The development of an economically-optimal generation schedule is the core of the generation scheduling problem. To solve this problem, renewable energy plant owners need, besides energy prices forecast, weather prediction. Among renewable energy sources, concentrated solar power (CSP) plants with thermal energy storage (TES) may find it easier to participate in electricity markets due to their semi-dispatchable generation. In any case, the limited accuracy of forecasting solar resource brings about the risk of penalties that may be imposed to CSP plants for deviation from the submitted schedule. This paper proposes a model-based predictive control (MPC) approach with an economic objective function to tackle the scheduling problem in CSP plants with TES. By this approach, the most recent forecast and the current status of plant can be used by the proposed economic MPC approach to reschedule the generation conveniently at regular time intervals. On the other hand, a more feasible generation schedule for the next day is performed at the appropriate time thanks to the use of short-term forecast. The proposed approach is applied, in a simulation context, to a 50 MW parabolic trough collector-based CSP plant with TES under the assumptions of perfect price forecasts and participation in the Spanish day-ahead energy market. A case study based on a half-year period to test several meteorological conditions is performed. In this study, an economic analysis is carried out using actual values of energy price, penalty cost, solar resource data and its day-ahead forecast. Results show an economic improvement in comparison with a traditional day-ahead scheduling strategy, especially in periods with a bad weather forecast. To overcome the lack of short-term weather forecast data for this study, a synthetic short-term predictor, whose accuracy level can be tuned by means of a parameter, is used. Sweeping this accuracy level between the situation with no forecast improvement and perfect shortterm forecast, the MPC strategy reaches an improvement in total profits during the six months period between 13.9% and 33.3% of the maximum room for improvement. This maximum ideal improvement is defined as the difference in profits between the MPC strategy with perfect forecasts and the dayahead scheduling strategy.This research has been supported by DPI2016-76493-C3-2-R Project of Ministerio de Economía y Competitividad (Spain). The authors would like to thank Acciona Energa S.A. for expressing interest in the projec

Predictor intervalar basado en hiperplano soporte

En este trabajo se aborda el problema de construir un modelo predictor. Dicho modelo debe ser capaz de predecir la salida futura de un sistema dinámico, haciendo uso de información pasada guardada en históricos. Este trabajo se centra en el estudio de modelos predictores que proporcionan una predicción de tipo intervalar. Una predicción intervalar está compuesta por un límite inferior y otro superior. La salida del sistema debe estar comprendida entre ambos límites del intervalo. Dado un conjunto de datos obtenidos del sistema dinámico, la predicción intervalar se calcula utilizando hiperplanos soporte a dichos datos. Cualquier punto dentro del intervalo se puede utilizar como predicción puntual. En concreto, en este trabajo se propone la utilización del punto central entre hiperplanos soporte. La principal bondad del predictor propuesto es su capacidad de proporcionar predicciones donde el tamaño del intervalo y el error de la predicción puntual están balanceados. Un parámetro de diseño incluido en el predictor permite compensar dichos objetivos. Además el trabajo propone una metodología basada en validación cruzada para realizar el ajuste de dicho parámetro. El trabajo incluye un ejemplo con datos reales con el fin de ilustrar el comportamiento del predictor.Ministerio de Educación y Ciencia (España) DPI2013-48243-C2-2-RMinisterio de Educación y Ciencia (España) DPI2016-76493-C3-1-RMinisterio de Educación y Ciencia (España) DPI2016-76493-C3-2-

A new supervised method for blood vessel segmentation in retinal images by using gray-level and moment invariants-based features

This paper presents a new supervised method for blood vessel detection in digital retinal images. This method uses a neural network (NN) scheme for pixel classification and computes a 7-D vector composed of gray-level and moment invariants-based features for pixel representation. The method was evaluated on the publicly available DRIVE and STARE databases, widely used for this purpose, since they contain retinal images where the vascular structure has been precisely marked by experts. Method performance on both sets of test images is better than other existing solutions in literature. The method proves especially accurate for vessel detection in STARE images. Its application to this database (even when the NN was trained on the DRIVE database) outperforms all analyzed segmentation approaches. Its effectiveness and robustness with different image conditions, together with its simplicity and fast implementation, make this blood vessel segmentation proposal suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy detection

Role of age and comorbidities in mortality of patients with infective endocarditis

[Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

Empirical models of the solar field in concentrated solar thermal plants. An application to scheduling

[Resumen] Uno de los bloques fundamentales de una planta termosolar de concentración es el campo solar. En este bloque, la energía del recurso solar se captura y concentra sobre un fluido para su posterior utilización como energía térmica. La estimación de la potencia térmica disponible en el campo solar a partir de valores del recurso solar es una información de gran utilidad en diversas aplicaciones. Esta estimación se puede conseguir utilizando un modelo del campo solar diseñado en base a primeros principios. Sin embargo la construcción de un modelo de este tipo puede ser complejo y requerir la participación de un experto con un conocimiento en profundidad del campo solar a modelar. En este trabajo se propone como alternativa la utilización de modelos empíricos del campo solar. En este caso, el modelo se obtiene a partir de un conjunto de medidas realizadas en el campo solar. Se proponen dos tipos de modelos empíricos: paramétrico y orientado a datos. Con el fin de estudiar la aplicabilidad de los modelos propuestos se ha considerado su utilización en el problema de la gerneración óptima auto-planificada en una planta CSP que participa en un mercado eléctrico a un día. En un contexto de simulación y con el objeto de comparar diferentes opciones, se ha realizado un estudio económico donde se evalúan varias estrategias de planificación en una planta basada en colectores cilindro-parabólicos de 50 MW con almacenamiento térmico. Las estrategias de planificación se diferencian únicamente en el modelo del campo solar utilizado. Los resultados muestran que las estrategias que utilizan los modelos empíricos del campo solar proporcionan resultados competitivos y que por tanto, se pueden utilizar como una alternativa viable a los basados en primeros principios. La utilización de modelos empíricos simplifica significativamente el diseño del planificador de producción.[Abstract] An important block of a concentrated solar thermal plant is the solar field. In this block, the solar energy is concentrated as thermal energy in a fluid. An estimation of the available thermal power based on the available solar resource is a useful information in several applications. This estimation can be obtained using a solar field model based on first-principles. However, to build a model of this kind, can be complex and requires a human expert with in depth knowledge of the solar filed to be modeled. This work proposes an alternative, to use empirical models of the solar field. In this case, the model is obtained using a set of measurements from the solar field. Two kind of empirical models are proposed: parametric and data-driven models. In order to study the applicability of the proposed models, the optimal self-scheduling generation problem in a concentrated solar thermal plant is considered. Several sche- duling strategies with dffeerent solar field models are compared in a simulation context. The simulations show that the strategies with empirical models of the solar field provides competitive results and then, can be considered as an alternative to the strategies based on first-principles models. The empirical models simplify the development of a generation scheduler.Ministerio de Economía y Competitividad; DPI2016-76493-C3-2-

Diseño gráfico con Corel Draw. Aplicaciones prácticas

Manual para el aprendizaje de Corel Draw. En él se incluye cómo escanear fotografías y realizar retoques fotográficos, cómo combinar los elementos gráficos en una publicación, cómo crear gráficos optimizados para Internet, mapas de imágenes, cómo exportar imágenes, cómo utilizar todo tipo de sofware gráfico especializado, cómo usar correctamente las tipografías en folletos, posters, etc. cómo diseñar animaciones y realizar el rodaje final, cómo comprender los diferentes sistemas de posproducción e impresión y cómo crear y componer escenas en 3D.ExtremaduraES