Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.

Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers

Los Centros de Datos se encuentran actualmente en cualquier sector de la economía mundial. Están compuestos por miles de servidores, dando servicio a los usuarios de forma global, las 24 horas del día y los 365 días del año. Durante los últimos años, las aplicaciones del ámbito de la e-Ciencia, como la e-Salud o las Ciudades Inteligentes han experimentado un desarrollo muy significativo. La necesidad de manejar de forma eficiente las necesidades de cómputo de aplicaciones de nueva generación, junto con la creciente demanda de recursos en aplicaciones tradicionales, han facilitado el rápido crecimiento y la proliferación de los Centros de Datos. El principal inconveniente de este aumento de capacidad ha sido el rápido y dramático incremento del consumo energético de estas infraestructuras. En 2010, la factura eléctrica de los Centros de Datos representaba el 1.3% del consumo eléctrico mundial. Sólo en el año 2012, el consumo de potencia de los Centros de Datos creció un 63%, alcanzando los 38GW. En 2013 se estimó un crecimiento de otro 17%, hasta llegar a los 43GW. Además, los Centros de Datos son responsables de más del 2% del total de emisiones de dióxido de carbono a la atmósfera. Esta tesis doctoral se enfrenta al problema energético proponiendo técnicas proactivas y reactivas conscientes de la temperatura y de la energía, que contribuyen a tener Centros de Datos más eficientes. Este trabajo desarrolla modelos de energía y utiliza el conocimiento sobre la demanda energética de la carga de trabajo a ejecutar y de los recursos de computación y refrigeración del Centro de Datos para optimizar el consumo. Además, los Centros de Datos son considerados como un elemento crucial dentro del marco de la aplicación ejecutada, optimizando no sólo el consumo del Centro de Datos sino el consumo energético global de la aplicación. Los principales componentes del consumo en los Centros de Datos son la potencia de computación utilizada por los equipos de IT, y la refrigeración necesaria para mantener los servidores dentro de un rango de temperatura de trabajo que asegure su correcto funcionamiento. Debido a la relación cúbica entre la velocidad de los ventiladores y el consumo de los mismos, las soluciones basadas en el sobre-aprovisionamiento de aire frío al servidor generalmente tienen como resultado ineficiencias energéticas. Por otro lado, temperaturas más elevadas en el procesador llevan a un consumo de fugas mayor, debido a la relación exponencial del consumo de fugas con la temperatura. Además, las características de la carga de trabajo y las políticas de asignación de recursos tienen un impacto importante en los balances entre corriente de fugas y consumo de refrigeración. La primera gran contribución de este trabajo es el desarrollo de modelos de potencia y temperatura que permiten describes estos balances entre corriente de fugas y refrigeración; así como la propuesta de estrategias para minimizar el consumo del servidor por medio de la asignación conjunta de refrigeración y carga desde una perspectiva multivariable. Cuando escalamos a nivel del Centro de Datos, observamos un comportamiento similar en términos del balance entre corrientes de fugas y refrigeración. Conforme aumenta la temperatura de la sala, mejora la eficiencia de la refrigeración. Sin embargo, este incremente de la temperatura de sala provoca un aumento en la temperatura de la CPU y, por tanto, también del consumo de fugas. Además, la dinámica de la sala tiene un comportamiento muy desigual, no equilibrado, debido a la asignación de carga y a la heterogeneidad en el equipamiento de IT. La segunda contribución de esta tesis es la propuesta de técnicas de asigación conscientes de la temperatura y heterogeneidad que permiten optimizar conjuntamente la asignación de tareas y refrigeración a los servidores. Estas estrategias necesitan estar respaldadas por modelos flexibles, que puedan trabajar en tiempo real, para describir el sistema desde un nivel de abstracción alto. Dentro del ámbito de las aplicaciones de nueva generación, las decisiones tomadas en el nivel de aplicación pueden tener un impacto dramático en el consumo energético de niveles de abstracción menores, como por ejemplo, en el Centro de Datos. Es importante considerar las relaciones entre todos los agentes computacionales implicados en el problema, de forma que puedan cooperar para conseguir el objetivo común de reducir el coste energético global del sistema. La tercera contribución de esta tesis es el desarrollo de optimizaciones energéticas para la aplicación global por medio de la evaluación de los costes de ejecutar parte del procesado necesario en otros niveles de abstracción, que van desde los nodos hasta el Centro de Datos, por medio de técnicas de balanceo de carga. Como resumen, el trabajo presentado en esta tesis lleva a cabo contribuciones en el modelado y optimización consciente del consumo por fugas y la refrigeración de servidores; el modelado de los Centros de Datos y el desarrollo de políticas de asignación conscientes de la heterogeneidad; y desarrolla mecanismos para la optimización energética de aplicaciones de nueva generación desde varios niveles de abstracción. ABSTRACT Data centers are easily found in every sector of the worldwide economy. They consist of tens of thousands of servers, serving millions of users globally and 24-7. In the last years, e-Science applications such e-Health or Smart Cities have experienced a significant development. The need to deal efficiently with the computational needs of next-generation applications together with the increasing demand for higher resources in traditional applications has facilitated the rapid proliferation and growing of data centers. A drawback to this capacity growth has been the rapid increase of the energy consumption of these facilities. In 2010, data center electricity represented 1.3% of all the electricity use in the world. In year 2012 alone, global data center power demand grew 63% to 38GW. A further rise of 17% to 43GW was estimated in 2013. Moreover, data centers are responsible for more than 2% of total carbon dioxide emissions. This PhD Thesis addresses the energy challenge by proposing proactive and reactive thermal and energy-aware optimization techniques that contribute to place data centers on a more scalable curve. This work develops energy models and uses the knowledge about the energy demand of the workload to be executed and the computational and cooling resources available at data center to optimize energy consumption. Moreover, data centers are considered as a crucial element within their application framework, optimizing not only the energy consumption of the facility, but the global energy consumption of the application. The main contributors to the energy consumption in a data center are the computing power drawn by IT equipment and the cooling power needed to keep the servers within a certain temperature range that ensures safe operation. Because of the cubic relation of fan power with fan speed, solutions based on over-provisioning cold air into the server usually lead to inefficiencies. On the other hand, higher chip temperatures lead to higher leakage power because of the exponential dependence of leakage on temperature. Moreover, workload characteristics as well as allocation policies also have an important impact on the leakage-cooling tradeoffs. The first key contribution of this work is the development of power and temperature models that accurately describe the leakage-cooling tradeoffs at the server level, and the proposal of strategies to minimize server energy via joint cooling and workload management from a multivariate perspective. When scaling to the data center level, a similar behavior in terms of leakage-temperature tradeoffs can be observed. As room temperature raises, the efficiency of data room cooling units improves. However, as we increase room temperature, CPU temperature raises and so does leakage power. Moreover, the thermal dynamics of a data room exhibit unbalanced patterns due to both the workload allocation and the heterogeneity of computing equipment. The second main contribution is the proposal of thermal- and heterogeneity-aware workload management techniques that jointly optimize the allocation of computation and cooling to servers. These strategies need to be backed up by flexible room level models, able to work on runtime, that describe the system from a high level perspective. Within the framework of next-generation applications, decisions taken at this scope can have a dramatical impact on the energy consumption of lower abstraction levels, i.e. the data center facility. It is important to consider the relationships between all the computational agents involved in the problem, so that they can cooperate to achieve the common goal of reducing energy in the overall system. The third main contribution is the energy optimization of the overall application by evaluating the energy costs of performing part of the processing in any of the different abstraction layers, from the node to the data center, via workload management and off-loading techniques. In summary, the work presented in this PhD Thesis, makes contributions on leakage and cooling aware server modeling and optimization, data center thermal modeling and heterogeneityaware data center resource allocation, and develops mechanisms for the energy optimization for next-generation applications from a multi-layer perspective.

Optimization of energy extraction in transverse galloping

A numerical method to analyse the stability of transverse galloping based on experimental measurements, as an alternative method to polynomial fitting of the transverse force coefficient Cz, is proposed in this paper. The Glauert–Den Hartog criterion is used to determine the region of angles of attack (pitch angles) prone to present galloping. An analytic solution (based on a polynomial curve of Cz) is used to validate the method and to evaluate the discretization errors. Several bodies (of biconvex, D-shape and rhomboidal cross sections) have been tested in a wind tunnel and the stability of the galloping region has been analysed with the new method. An algorithm to determine the pitch angle of the body that allows the maximum value of the kinetic energy of the flow to be extracted is presented.

Analysis and optimization of trajectories for Ballistic Missiles Interception

Intercontinental Ballistic Missiles are capable of placing a nuclear warhead at more than 5,000 km away from its launching base. With the lethal power of a nuclear warhead a whole city could be wiped out by a single weapon causing millions of deaths. This means that the threat posed to any country from a single ICBM captured by a terrorist group or launched by a 'rogue' state is huge. This threat is increasing as more countries are achieving nuclear and advanced launcher capabilities. In order to suppress or at least reduce this threat the United States created the National Missile Defense System which involved, among other systems, the development of long-range interceptors whose aim is to destroy incoming ballistic missiles in their midcourse phase. The Ballistic Missile Defense is a high-profile topic that has been the focus of political controversy lately when the U.S. decided to expand the Ballistic Missile system to Europe, with the opposition of Russia. However the technical characteristics of this system are mostly unknown by the general public. The Interception of an ICBM using a long range Interceptor Missile as intended within the Ground-Based Missile Defense System by the American National Missile Defense (NMD) implies a series of problems of incredible complexity: - The incoming missile has to be detected almost immediately after launch. - The incoming missile has to be tracked along its trajectory with a great accuracy. - The Interceptor Missile has to implement a fast and accurate guidance algorithm in order to reach the incoming missile as soon as possible. - The Kinetic Kill Vehicle deployed by the interceptor boost vehicle has to be able to detect the reentry vehicle once it has been deployed by ICBM, when it offers a very low infrared signature, in order to perform a final rendezvous manoeuvre. - The Kinetic Kill Vehicle has to be able to discriminate the reentry vehicle from the surrounding debris and decoys. - The Kinetic Kill Vehicle has to be able to implement an accurate guidance algorithm in order to perform a kinetic interception (direct collision) of the reentry vehicle, at relative speeds of more than 10 km/s. All these problems are being dealt simultaneously by the Ground-Based Missile Defense System that is developing very complex and expensive sensors, communications and control centers and long-range interceptors (Ground-Based Interceptor Missile) including a Kinetic Kill Vehicle. Among all the technical challenges involved in this interception scenario, this thesis focuses on the algorithms required for the guidance of the Interceptor Missile and the Kinetic Kill Vehicle in order to perform the direct collision with the ICBM. The involved guidance algorithms are deeply analysed in this thesis in part III where conventional guidance strategies are reviewed and optimal guidance algorithms are developed for this interception problem. The generation of a realistic simulation of the interception scenario between an ICBM and a Ground Based Interceptor designed to destroy it was considered as necessary in order to be able to compare different guidance strategies with meaningful results. As a consequence, a highly representative simulator for an ICBM and a Kill Vehicle has been implemented, as detailed in part II, and the generation of these simulators has also become one of the purposes of this thesis. In summary, the main purposes of this thesis are: - To develop a highly representative simulator of an interception scenario between an ICBM and a Kill Vehicle launched from a Ground Based Interceptor. -To analyse the main existing guidance algorithms both for the ascent phase and the terminal phase of the missiles. Novel conclusions of these analyses are obtained. - To develop original optimal guidance algorithms for the interception problem. - To compare the results obtained using the different guidance strategies, assess the behaviour of the optimal guidance algorithms, and analyse the feasibility of the Ballistic Missile Defense system in terms of guidance (part IV). As a secondary objective, a general overview of the state of the art in terms of ballistic missiles and anti-ballistic missile defence is provided (part I).

Analysis and optimization for a hexapod walking robot for planetary missions

La tecnología de las máquinas móviles autónomas ha sido objeto de una gran investigación y desarrollo en las últimas décadas. En muchas actividades y entornos, los robots pueden realizar operaciones que son duras, peligrosas o simplemente imposibles para los humanos. La exploración planetaria es un buen ejemplo de un entorno donde los robots son necesarios para realizar las tareas requeridas por los científicos. La reciente exploración de Marte con robots autónomos nos ha mostrado la capacidad de las nuevas tecnologías. Desde la invención de la rueda, que esta acertadamente considerado como el mayor invento en la historia del transporte humano, casi todos los vehículos para exploración planetaria han empleado las ruedas para su desplazamiento. Las nuevas misiones planetarias demandan maquinas cada vez mas complejas. En esta Tesis se propone un nuevo diseño de un robot con patas o maquina andante que ofrecerá claras ventajas en entornos extremos. Se demostrara que puede desplazarse en los terrenos donde los robots con ruedas son ineficientes, convirtiéndolo en una elección perfecta para misiones planetarias. Se presenta una reseña histórica de los principales misiones espaciales, en particular aquellos dirigidos a la exploración planetaria. A través de este estudio será posible analizar las desventajas de los robots con ruedas utilizados en misiones anteriores. El diseño propuesto de robot con patas será presentado como una alternativa para aquellas misiones donde los robots con ruedas puedan no ser la mejor opción. En esta tesis se presenta el diseño mecánico de un robot de seis patas capaz de soportar las grandes fuerzas y momentos derivadas del movimiento de avance. Una vez concluido el diseño mecánico es necesario realizar un análisis que permita entender el movimiento y comportamiento de una maquina de esta complejidad. Las ecuaciones de movimiento del robot serán validadas por dos métodos: cinemático y dinámico. Dos códigos Matlab® han sido desarrollados para resolver dichos sistemas de ecuaciones y han sido verificados por un tercer método, un modelo de elementos finitos, que también verifica el diseño mecánico. El robot con patas presentado, ha sido diseñado para la exploración planetaria en Marte. El comportamiento del robot durante sus desplazamientos será probado mediante un código de Matlab®, desarrollado para esta tesis, que permite modificar las trayectorias, el tipo de terreno, y el número y altura de los obstáculos. Estos terrenos y requisitos iniciales no han sido elegidos de forma aleatoria, si no que están basados en mi experiencia como miembro del equipo de MSL-NASA que opera un instrumento a bordo del rover Curiosity en Marte. El robot con patas desarrollado y fabricado por el Centro de Astrobiología (INTA-CSIC), esta basado en el diseño mecánico y análisis presentados en esta tesis. ABSTRACT The autonomous machines technology has undergone a major research and development during the last decades. In many activities and environments, robots can perform operations that are tought, dangerous or simply imposible to humans. Planetary exploration is a good example of such environment where robots are needed to perform the tasks required by the scientits. Recent Mars exploration based on autonomous vehicles has shown us the capacity of the new technologies. From the invention of the wheel, which is rightly regarded as the greatest invention in the history of human transportation, nearly all-planetary vehicles are based in wheeled locomotion, but new missions demand new types of machines due to the complex tasks needed to be performed. It will be proposed in this thesis a new design of a legged robot or walking machine, which may offer clear advantages in tough environments. This Thesis will show that the proposed walking machine can travel, were terrain difficulties make wheeled vehicles ineffective, making it a perfect choice for planetary mission. A historical background of the main space missions, in particular those aimed at planetary exploration will be presented. From this study the disadvantages found in the existing wheel rovers will be analysed. The legged robot designed will be introduced as an alternative were wheeled rovers could be no longer the best option for planetary exploration. This thesis introduces the mechanical design of a six-leg robot capable of withstanding high forces and moments due to the walking motion. Once the mechanical design is concluded, and in order to analyse a machine of this complexity an understanding of its movement and behaviour is mandatory. This movement equation will be validated by two methods: kinematics and dynamics. Two Matlab® codes have been developed to solve the systems of equations and validated by a third method, a finite element model, which also verifies the mechanical design. The legged robot presented has been designed for a Mars planetary exploration. The movement behaviour of the robot will be tested in a Matlab® code developed that allows to modify the trajectories, the type of terrain, number and height of obstacles. These terrains and initial requirements have not been chosen randomly, those are based on my experience as a member of the MSL NASA team, which operates an instrument on-board of the Curiosity rover in Mars. The walking robot developed and manufactured by the Center of Astrobiology (CAB) is based in the mechanical design and analysis that will be presented in this thesis.

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

Development of a fuzzy control based self-adaptive system for energy saving in constrained networks for the Internet of Things

Las redes del futuro, incluyendo las redes de próxima generación, tienen entre sus objetivos de diseño el control sobre el consumo de energía y la conectividad de la red. Estos objetivos cobran especial relevancia cuando hablamos de redes con capacidades limitadas, como es el caso de las redes de sensores inalámbricos (WSN por sus siglas en inglés). Estas redes se caracterizan por estar formadas por dispositivos de baja o muy baja capacidad de proceso y por depender de baterías para su alimentación. Por tanto la optimización de la energía consumida se hace muy importante. Son muchas las propuestas que se han realizado para optimizar el consumo de energía en este tipo de redes. Quizás las más conocidas son las que se basan en la planificación coordinada de periodos de actividad e inactividad, siendo una de las formas más eficaces para extender el tiempo de vida de las baterías. La propuesta que se presenta en este trabajo se basa en el control de la conectividad mediante una aproximación probabilística. La idea subyacente es que se puede esperar que una red mantenga la conectividad si todos sus nodos tienen al menos un número determinado de vecinos. Empleando algún mecanismo que mantenga ese número, se espera que se pueda mantener la conectividad con un consumo energético menor que si se empleara una potencia de transmisión fija que garantizara una conectividad similar. Para que el mecanismo sea eficiente debe tener la menor huella posible en los dispositivos donde se vaya a emplear. Por eso se propone el uso de un sistema auto-adaptativo basado en control mediante lógica borrosa. En este trabajo se ha diseñado e implementado el sistema descrito, y se ha probado en un despliegue real confirmando que efectivamente existen configuraciones posibles que permiten mantener la conectividad ahorrando energía con respecto al uso de una potencia de transmisión fija. ABSTRACT. Among the design goals for future networks, including next generation networks, we can find the energy consumption and the connectivity. These two goals are of special relevance when dealing with constrained networks. That is the case of Wireless Sensors Networks (WSN). These networks consist of devices with low or very low processing capabilities. They also depend on batteries for their operation. Thus energy optimization becomes a very important issue. Several proposals have been made for optimizing the energy consumption in this kind of networks. Perhaps the best known are those based on the coordinated planning of active and sleep intervals. They are indeed one of the most effective ways to extend the lifetime of the batteries. The proposal presented in this work uses a probabilistic approach to control the connectivity of a network. The underlying idea is that it is highly probable that the network will have a good connectivity if all the nodes have a minimum number of neighbors. By using some mechanism to reach that number, we hope that we can preserve the connectivity with a lower energy consumption compared to the required one if a fixed transmission power is used to achieve a similar connectivity. The mechanism must have the smallest footprint possible on the devices being used in order to be efficient. Therefore a fuzzy control based self-adaptive system is proposed. This work includes the design and implementation of the described system. It also has been validated in a real scenario deployment. We have obtained results supporting that there exist configurations where it is possible to get a good connectivity saving energy when compared to the use of a fixed transmission power for a similar connectivity.

Optimization of multijunction solar cells through indoor energy yield measurements

The variability of the solar spectra in the field may reduce the annual energy yield of multijunction solar cells. It would, therefore, be desirable to implement a cell design procedure based on the maximization of the annual energy yield. In this study, we present a measurement technique to generate maps of the real performance of the solar cell for a range of light spectrum contents using a solar simulator with a computer-controllable spectral content. These performance maps are demonstrated to be a powerful tool for analyzing the characteristics of any given set of annual spectra representative of a site and their influence on the energy yield of any solar cell. The effect of luminescence coupling on buffering against variations of the spectrum and improving the annual energy yield is demonstrated using this method.

Design Parameter Analysis of Point Absorber WEC via an Evolutionary-Algorithm-Based Dimensioning Tool

Wave energy conversion has an essential difference from other renewable energies since the dependence between the devices design and the energy resource is stronger. Dimensioning is therefore considered a key stage when a design project of Wave Energy Converters (WEC) is undertaken. Location, WEC concept, Power Take-Off (PTO) type, control strategy and hydrodynamic resonance considerations are some of the critical aspects to take into account to achieve a good performance. The paper proposes an automatic dimensioning methodology to be accomplished at the initial design project stages and the following elements are described to carry out the study: an optimization design algorithm, its objective functions and restrictions, a PTO model, as well as a procedure to evaluate the WEC energy production. After that, a parametric analysis is included considering different combinations of the key parameters previously introduced. A variety of study cases are analysed from the point of view of energy production for different design-parameters and all of them are compared with a reference case. Finally, a discussion is presented based on the results obtained, and some recommendations to face the WEC design stage are given.

Proceso metodológico para optimizar la toma de decisiones en el proyecto de envolventes arquitectónicas multicapa = Methodological process for the optimization of the decision making in multilayer building envelope projects

La presente tesis doctoral se enmarca dentro del concepto de la sistematización del conocimiento en arquitectura, más concretamente en el campo de las construcciones arquitectónicas y la toma de decisiones en la fase de proyecto de envolventes arquitectónicas multicapa. Por tanto, el objetivo principal es el establecimiento de las bases para una toma de decisiones informadas durante el proyecto de una envolvente multicapa con el fin de colaborar en su optimización. Del mismo modo que la historia de la arquitectura está relacionada con la historia de la innovación en construcción, la construcción está sujeta a cambios como respuesta a los fracasos anteriores. En base a esto, se identifica la toma de decisiones en la fase de proyecto como el estadio inicial para establecer un punto estratégico de reflexión y de control sobre los procesos constructivos. La presente investigación, conceptualmente, define los parámetros intervinientes en el proyecto de envolventes arquitectónicas multicapa a partir de una clasificación y sistematización de todos los componentes (elementos, unidades y sistemas constructivos) utilizados en las fachadas multicapa. Dicha sistematización se materializa en una hoja matriz de datos en la que, dentro de una organización a modo de árbol, se puede acceder a la consulta de cada componente y de su caracterización. Dicha matriz permite la incorporación futura de cualquier componente o sistema nuevo que aparezca en el mercado, relacionándolo con aquellos con los que comparta ubicación, tipo de material, etc. Con base en esa matriz de datos, se diseña la sistematización de la toma de decisiones en la fase de proyecto de una envolvente arquitectónica, en concreto, en el caso de una fachada. Operativamente, el resultado se presenta como una herramienta que permite al arquitecto o proyectista reflexionar y seleccionar el sistema constructivo más adecuado, al enfrentarse con las distintas decisiones o elecciones posibles. La herramienta se basa en las elecciones iniciales tomadas por el proyectista y se estructura, a continuación y sucesivamente, en distintas aproximaciones, criterios, subcriterios y posibilidades que responden a los distintos avances en la definición del sistema constructivo. Se proponen una serie de fichas operativas de comprobación que informan sobre el estadio de decisión y de definición de proyecto alcanzados en cada caso. Asimismo, el sistema permite la conexión con otros sistemas de revisión de proyectos para fomentar la reflexión sobre la normalización de los riesgos asociados tanto al proprio sistema como a su proceso constructivo y comportamiento futuros. La herramienta proporciona un sistema de ayuda para ser utilizado en el proceso de toma de decisiones en la fase de diseño de una fachada multicapa, minimizando la arbitrariedad y ofreciendo una cualificación previa a la cuantificación que supondrá la elaboración del detalle constructivo y de su medición en las sucesivas fases del proyecto. Al mismo tiempo, la sistematización de dicha toma de decisiones en la fase del proyecto puede constituirse como un sistema de comprobación en las diferentes fases del proceso de decisión proyectual y de definición de la envolvente de un edificio. ABSTRACT The central issue of this doctoral Thesis is founded on the framework of the concept of the systematization of knowledge in architecture, in particular, in respect of the field of building construction and the decision making in the design stage of multilayer building envelope projects. Therefore, the main objective is to establish the bases for knowledgeable decision making during a multilayer building envelope design process, in order to collaborate with its optimization. Just as the history of architecture is connected to the history of innovation in construction, construction itself is subject to changes as a response to previous failures. On this basis, the decisions made during the project design phase are identified as the initial state to establish an strategic point for reflection and control, referred to the constructive processes. Conceptually, this research defines the parameters involving the multilayer building envelope projects, on the basis of a classification and systematization for all the components (elements, constructive units and constructive systems) used in multilayer façades. The mentioned systematization is materialized into a data matrix sheet in which, following a tree‐like organization, the access to every single component and its characterization is possible. The above data matrix allows the future inclusion of any new component or system that may appear in the construction market. That new component or system can be put into a relationship with another, which it shares location, type of material,… with. Based on the data matrix, the systematization of the decision making process for a building envelope design stage is designed, more particularly in the case of a façade. Putting this into practice, it is represented as a tool which allows the architect or the designer, to reflect and to select the appropriate building system when facing the different elections or the different options. The tool is based on the initial elections taken by the designer. Then and successively, it is shaped on the form of different operative steps, criteria, sub‐criteria and possibilities which respond to a different progress in the definition of the building construction system. In order to inform about the stage of the decision and the definition reached by the project in every particular case, a range of operative sheets are proposed. Additionally, the system allows the connection with other reviewing methods for building projects. The aim of this last possibility is to encourage the reflection on standardization of the associated risks to the building system itself and its future performance. The tool provides a helping system to be used during the decision making process for a multilayer façade design. It minimizes the arbitrariness and offers a qualification previous to the quantification that will be done with the development of the construction details and their bill of quantities, that in subsequent project stages will be executed. At the same time, the systematization of the mentioned decision making during the design phase, can be found as a checking system in the different stages of the decision making design process and in the different stages of the building envelope definition.

Dynamic weighting in Monte Carlo and optimization

Dynamic importance weighting is proposed as a Monte Carlo method that has the capability to sample relevant parts of the configuration space even in the presence of many steep energy minima. The method relies on an additional dynamic variable (the importance weight) to help the system overcome steep barriers. A non-Metropolis theory is developed for the construction of such weighted samplers. Algorithms based on this method are designed for simulation and global optimization tasks arising from multimodal sampling, neural network training, and the traveling salesman problem. Numerical tests on these problems confirm the effectiveness of the method.

Energy-based de novo protein folding by conformational space annealing and an off-lattice united-residue force field: Application to the 10-55 fragment of staphylococcal protein A and to apo calbindin D9K

The conformational space annealing (CSA) method for global optimization has been applied to the 10-55 fragment of the B-domain of staphylococcal protein A (protein A) and to a 75-residue protein, apo calbindin D9K (PDB ID code 1CLB), by using the UNRES off-lattice united-residue force field. Although the potential was not calibrated with these two proteins, the native-like structures were found among the low-energy conformations, without the use of threading or secondary-structure predictions. This is because the CSA method can find many distinct families of low-energy conformations. Starting from random conformations, the CSA method found that there are two families of low-energy conformations for each of the two proteins, the native-like fold and its mirror image. The CSA method converged to the same low-energy folds in all cases studied, as opposed to other optimization methods. It appears that the CSA method with the UNRES force field, which is based on the thermodynamic hypothesis, can be used in prediction of protein structures in real time.

Structure-assisted design of mechanism-based irreversible inhibitors of human rhinovirus 3C protease with potent antiviral activity against multiple rhinovirus serotypes

Human rhinoviruses, the most important etiologic agents of the common cold, are messenger-active single-stranded monocistronic RNA viruses that have evolved a highly complex cascade of proteolytic processing events to control viral gene expression and replication. Most maturation cleavages within the precursor polyprotein are mediated by rhinovirus 3C protease (or its immediate precursor, 3CD), a cysteine protease with a trypsin-like polypeptide fold. High-resolution crystal structures of the enzyme from three viral serotypes have been used for the design and elaboration of 3C protease inhibitors representing different structural and chemical classes. Inhibitors having α,β-unsaturated carbonyl groups combined with peptidyl-binding elements specific for 3C protease undergo a Michael reaction mediated by nucleophilic addition of the enzyme’s catalytic Cys-147, resulting in covalent-bond formation and irreversible inactivation of the viral protease. Direct inhibition of 3C proteolytic activity in virally infected cells treated with these compounds can be inferred from dose-dependent accumulations of viral precursor polyproteins as determined by SDS/PAGE analysis of radiolabeled proteins. Cocrystal-structure-assisted optimization of 3C-protease-directed Michael acceptors has yielded molecules having extremely rapid in vitro inactivation of the viral protease, potent antiviral activity against multiple rhinovirus serotypes and low cellular toxicity. Recently, one compound in this series, AG7088, has entered clinical trials.

How optimization of potential functions affects protein folding.

The relationship between the optimization of the potential function and the foldability of theoretical protein models is studied based on investigations of a 27-mer cubic-lattice protein model and a more realistic lattice model for the protein crambin. In both the simple and the more complicated systems, optimization of the energy parameters achieves significant improvements in the statistical-mechanical characteristics of the systems and leads to foldable protein models in simulation experiments. The foldability of the protein models is characterized by their statistical-mechanical properties--e.g., by the density of states and by Monte Carlo folding simulations of the models. With optimized energy parameters, a high level of consistency exists among different interactions in the native structures of the protein models, as revealed by a correlation function between the optimized energy parameters and the native structure of the model proteins. The results of this work are relevant to the design of a general potential function for folding proteins by theoretical simulations.

Chaperonin-facilitated protein folding: optimization of rate and yield by an iterative annealing mechanism.

We develop a heuristic model for chaperonin-facilitated protein folding, the iterative annealing mechanism, based on theoretical descriptions of "rugged" conformational free energy landscapes for protein folding, and on experimental evidence that (i) folding proceeds by a nucleation mechanism whereby correct and incorrect nucleation lead to fast and slow folding kinetics, respectively, and (ii) chaperonins optimize the rate and yield of protein folding by an active ATP-dependent process. The chaperonins GroEL and GroES catalyze the folding of ribulose bisphosphate carboxylase at a rate proportional to the GroEL concentration. Kinetically trapped folding-incompetent conformers of ribulose bisphosphate carboxylase are converted to the native state in a reaction involving multiple rounds of quantized ATP hydrolysis by GroEL. We propose that chaperonins optimize protein folding by an iterative annealing mechanism; they repeatedly bind kinetically trapped conformers, randomly disrupt their structure, and release them in less folded states, allowing substrate proteins multiple opportunities to find pathways leading to the most thermodynamically stable state. By this mechanism, chaperonins greatly expand the range of environmental conditions in which folding to the native state is possible. We suggest that the development of this device for optimizing protein folding was an early and significant evolutionary event.