Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms.

Pressure management in water distribution systems: current status, proposals, and future trends

Pressure management (PM) is commonly used in water distribution systems (WDSs). In the last decade, a strategic objective in the field has been the development of new scientific and technical methods for its implementation. However, due to a lack of systematic analysis of the results obtained in practical cases, progress has not always been reflected in practical actions. To address this problem, this paper provides a comprehensive analysis of the most innovative issues related to PM. The methodology proposed is based on a case-study comparison of qualitative concepts that involves published work from 140 sources. The results include a qualitative analysis covering four aspects: (1) the objectives yielded by PM; (2) types of regulation, including advanced control systems through electronic controllers; (3) new methods for designing districts; and (4) development of optimization models associated with PM. The evolution of the aforementioned four aspects is examined and discussed. Conclusions regarding the current status of each factor are drawn and proposals for future research outlined

Predictor paramétrico de glucosa subcutánea

La diabetes mellitus es una enfermedad que se caracteriza por la nula o insuficiente producción de insulina, o la resistencia del organismo a la misma. La insulina es una hormona que ayuda a que la glucosa (por ejemplo la obtenida a partir de los alimentos ingeridos) llegue a los tejidos periféricos y al sistema nervioso para suministrar energía. Hoy en día la tecnología actual permite abordar el desarrollo del llamado “páncreas endocrino artificial”, que consta de un sensor continuo de glucosa subcutánea, una bomba de infusión subcutánea de insulina y un algoritmo de control en lazo cerrado que calcule la dosis de insulina requerida por el paciente en cada momento, según la medida de glucosa obtenida por el sensor y según unos objetivos. El mayor problema que presentan los sistemas de control en lazo cerrado son los retardos, el sensor de glucosa subcutánea mide la glucosa del líquido intersticial, que representa la que hubo en la sangre un tiempo atrás, por tanto, un cambio en los niveles de glucosa en la sangre, debidos por ejemplo, a una ingesta, tardaría un tiempo en ser detectado por el sensor. Además, una dosis de insulina suministrada al paciente, tarda un tiempo aproximado de 20-30 minutos para la llegar a la sangre. Para evitar trabajar en la medida que sea posible con estos retardos, se intenta predecir cuál será el nivel de glucosa en un futuro próximo, para ello se utilizara un predictor de glucosa subcutánea, con la información disponible de glucosa e insulina. El objetivo del proyecto es diseñar una metodología para estimar el valor futuro de los niveles de glucosa obtenida a partir de un sensor subcutáneo, basada en la identificación recursiva del sistema glucorregulatorio a través de modelos lineales y determinando un horizonte de predicción óptimo de trabajo y analizando la influencia de la insulina en los resultados de la predicción. Se ha implementado un predictor paramétrico basado en un modelo autorregresivo ARX que predice con mejor precisión y con menor RMSE que un predictor ZOH a un horizonte de predicción de treinta minutos. Utilizar información relativa a la insulina no tiene efecto en la predicción. El preprocesado, postprocesado y el tratamiento de la estabilidad tienen un efecto muy beneficioso en la predicción. Diabetes mellitusis a group of metabolic diseases in which a person has high blood sugar, either because the body does not produce enough insulin, or because cells do not respond to the insulin produced. The insulin is a hormone that helps the glucose to reach to outlying tissues and the nervous system to supply energy. Nowadays, the actual technology allows raising the development of the “artificial endocrine pancreas”. It involves a continuous glucose sensor, an insulin bump, and a full closed loop algorithm that calculate the insulin units required by patient at any time, according to the glucose measure obtained by the sensor and any target. The main problem of the full closed loop systems is the delays, the glucose sensor measures the glucose in the interstitial fluid that represents the glucose was in the blood some time ago. Because of this, a change in the glucose in blood would take some time to be detected by the sensor. In addition, insulin units administered by a patient take about 20-30 minutes to reach the blood stream. In order to avoid this effect, it will try to predict the glucose level in the near future. To do that, a subcutaneous glucose predictor is used to predict the future glucose with the information about insulin and glucose. The goal of the proyect is to design a method in order to estimate the future valor of glucose obtained by a subcutaneous sensor. It is based on the recursive identification of the regulatory system through the linear models, determining optimal prediction horizon and analyzing the influence of insuline on the prediction results. A parametric predictor based in ARX autoregressive model predicts with better precision and with lesser RMSE than ZOH predictor in a thirty minutes prediction horizon. Using the relative insulin information has no effect in the prediction. The preprocessing, the postprocessing and the stability treatment have many advantages in the prediction.

Validation of a novel approach to subjective quality evaluation of conventional and 3D broadcasted video services

Transmission errors are the main cause of degradation of the quality of real broadcasted video services. Therefore, knowing their impact on the quality of experience of the end users is a crucial issue. For instance, it would help to improve the performance of the distribution systems, and to develop monitoring tools to automatically estimate the quality perceived by the end users. In this paper we validate a subjective evaluation approach specifically designed to obtain meaningful results of the effects of degradations caused by transmission errors. This methodology has been already used in our previous works with monoscopic and stereoscopic videos. The validation is done by comparing the subjective ratings obtained for typical transmission errors with the proposed methodology and with the standard method Absolute Category Rating. The results show that the proposed approach could provide more representative evaluations of the quality of experience perceived by end users of conventional and 3D broadcasted video services.

Tratamientos avanzados de agua potable para eliminación de materia orgánica disuelta : aplicación del BAC

Los procesos de biofiltración por carbón activo biológico se han utilizado desde hace décadas, primeramente en Europa y después en Norte América, sin embargo no hay parámetros de diseño y operación específicos que se puedan utilizar de guía para la biofiltración. Además, el factor coste a la hora de elegir el carbón activo como medio de filtración impacta en el presupuesto, debido al elevado coste de inversión y de regeneración. A la hora de diseñar y operar filtros de carbón activo los requisitos que comúnmente se buscan son eliminar materia orgánica, olor, y sabor de agua. Dentro de la eliminación de materia orgánica se precisa la eliminación necesaria para evitar subproductos en la desinfección no deseados, y reducir los niveles de carbono orgánico disuelto biodegradable y asimilable a valores que consigan la bioestabilidad del agua producto, a fin de evitar recrecimiento de biofilm en las redes de distribución. El ozono se ha utilizado durante años como un oxidante previo a la biofiltración para reducir el olor, sabor, y color del agua, oxidando la materia orgánica convirtiendo los compuestos no biodegradables y lentamente biodegradables en biodegradables, consiguiendo que puedan ser posteriormente eliminados biológicamente en los filtros de carbón activo. Sin embargo la inestabilidad del ozono en el agua hace que se produzcan ácidos carboxilos, alcoholes y aldehídos, conocidos como subproductos de la desinfección. Con esta tesis se pretende dar respuesta principalmente a los siguientes objetivos: análisis de parámetros requeridos para el diseño de los filtros de carbón activo biológicos, necesidades de ozonización previa a la filtración, y comportamiento de la biofiltración en un sistema compuesto de coagulación sobre un filtro de carbón activo biológico. Los resultados obtenidos muestran que la biofiltración es un proceso que encaja perfectamente con los parámetros de diseño de plantas con filtración convencional. Aunque la capacidad de eliminación de materia orgánica se reduce a medida que el filtro se satura y entra en la fase biológica, la biodegradación en esta fase se mantienen estable y perdura a lo lago de los meses sin preocupaciones por la regeneración del carbón. Los valores de carbono orgánico disuelto biodegradable se mantienen por debajo de los marcados en la literatura existente para agua bioestable, lo que hace innecesaria la dosificación de ozono previa a la biofiltración. La adición de la coagulación con la corrección de pH sobre el carbón activo consigue una mejora en la reducción de la materia orgánica, sin afectar a la biodegradación del carbón activo, cumpliendo también con los requerimientos de turbidez a la salida de filtración. Lo que plantea importantes ventajas para el proceso. Granular activated carbon filters have been used for many years to treat and produce drinking water using the adsorption capacity of carbon, replacing it once the carbon lost its adsorption capacity and became saturated. On the other hand, biological activated carbon filters have been studied for decades, firstly in Europe and subsequently in North America, nevertheless are no generally accepted design and operational parameters documented to be used as design guidance for biofiltration. Perhaps this is because of the cost factor; to choose activated carbon as a filtration media requires a significant investment due to the high capital and regeneration costs. When activated carbon filters are typically required it is for the reduction of an organic load, removal of colour, taste and / or odour. In terms of organic matter reduction, the primary aim is to achieve as much removal as possible to reduce or avoid the introduction of disinfection by products, the required removal in biodegradable dissolved organic carbon and assimilable organic carbon to produce a biologically stable potable water which prohibits the regrowth of biofilm in the distribution systems. The ozone has historically been used as an oxidant to reduce colour, taste and odour by oxidizing the organic matter and increasing the biodegradability of the organic matter, enhancing the effectiveness of organic removal in downstream biological activated carbon filters. Unfortunately, ozone is unstable in water and reacts with organic matter producing carboxylic acids, alcohols, and aldehydes, known as disinfection by products. This thesis has the following objectives: determination of the required parameters for the design of the biological activated filters, the requirement of ozonization as a pre-treatment for the biological activated filters, and a performance assessment of biofiltration when coagulation is applied as a pretreatment for biological activated carbon filters. The results show that the process design parameters of biofiltration are compatible with those of conventional filtration. The organic matter removal reduces its effectiveness as soon as the filter is saturated and the biological stage starts, but the biodegradation continues steadily and lasts for a long period of time without the need of carbon regeneration. The removal of the biodegradable dissolved organic carbon is enough to produce a biostable water according to the values shown on the existing literature; therefore ozone is not required prior to the filtration. Furthermore, the addition of coagulant and pH control before the biological activated carbon filter achieves a additional removal of organic matter, without affecting the biodegradation that occurs in the activated carbon whilst also complying with the required turbidity removal.

Experiences on using closed-loop control systems for smoke control

The main objective of ventilation systems in case of fire is the reduction of the possible consequences by achieving the best possible conditions for the evacuation of the users and the intervention of the emergency services. In the last years, the required quick response of the ventilation system, from normal to emergency mode, has been improved by the use of automatic and semi-automatic control systems, what reduces the response times through the support to the operators decision taking, and the use of pre-defined strategies. A further step consists on the use of closedloop algorithms, which takes into account not only the initial conditions but their development (air velocity, traffic situation, etc), optimizing the quality of the smoke control process

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

Application of self-organizing techniques for the distribution of heterogeneous multi-tasks in multi-robot systems

This paper focuses on the general problem of coordinating of multi-robot systems, more specifically, it addresses the self-election of heterogeneous and specialized tasks by autonomous robots. In this regard, it has proposed experimenting with two different techniques based chiefly on selforganization and emergence biologically inspired, by applying response threshold models as well as ant colony optimization. Under this approach it can speak of multi-tasks selection instead of multi-tasks allocation, that means, as the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. It has evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.

Response threshold models and stochastic learning automata for self-coordination of heterogeneous multi-task distribution in multi-robot systems.

This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-selection of heterogeneous specialized tasks by autonomous robots. In this paper we focus on a specifically distributed or decentralized approach as we are particularly interested in a decentralized solution where the robots themselves autonomously and in an individual manner, are responsible for selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario to solve the corresponding multi-task distribution problem and we propose a solution using two different approaches by applying Response Threshold Models as well as Learning Automata-based probabilistic algorithms. We have evaluated the robustness of the algorithms, perturbing the number of pending loads to simulate the robot’s error in estimating the real number of pending tasks and also the dynamic generation of loads through time. The paper ends with a critical discussion of experimental results.