Variable threshold algorithm for division of labor analyzed as a dynamical system

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Using the Cross-Entropy Method for Control Optimization: A Case Study of See-and-Avoid on Unmanned Aerial Vehicles

This paper presents an adaptation of the Cross-Entropy (CE) method to optimize fuzzy logic controllers. The CE is a recently developed optimization method based on a general Monte-Carlo approach to combinatorial and continuous multi-extremal optimization and importance sampling. This work shows the application of this optimization method to optimize the inputs gains, the location and size of the different membership functions' sets of each variable, as well as the weight of each rule from the rule's base of a fuzzy logic controller (FLC). The control system approach presented in this work was designed to command the orientation of an unmanned aerial vehicle (UAV) to modify its trajectory for avoiding collisions. An onboard looking forward camera was used to sense the environment of the UAV. The information extracted by the image processing algorithm is the only input of the fuzzy control approach to avoid the collision with a predefined object. Real tests with a quadrotor have been done to corroborate the improved behavior of the optimized controllers at different stages of the optimization process.

Algoritmos genéticos en control activo de ruido

Este proyecto se centra en la implementación de un sistema de control activo de ruido mediante algoritmos genéticos. Para ello, se ha tenido en cuenta el tipo de ruido que se quiere cancelar y el diseño del controlador, parte fundamental del sistema de control. El control activo de ruido sólo es eficaz a bajas frecuencias, hasta los 250 Hz, justo para las cuales los elementos pasivos pierden efectividad, y en zonas o recintos de pequeñas dimensiones y conductos. El controlador ha de ser capaz de seguir todas las posibles variaciones del campo acústico que puedan producirse (variaciones de fase, de frecuencia, de amplitud, de funciones de transferencia electro-acústicas, etc.). Su funcionamiento está basado en algoritmos FIR e IIR adaptativos. La elección de un tipo de filtro u otro depende de características tales como linealidad, causalidad y número de coeficientes. Para que la función de transferencia del controlador siga las variaciones que surgen en el entorno acústico de cancelación, tiene que ir variando el valor de los coeficientes del filtro mediante un algoritmo adaptativo. En este proyecto se emplea como algoritmo adaptativo un algoritmo genético, basado en la selección biológica, es decir, simulando el comportamiento evolutivo de los sistemas biológicos. Las simulaciones se han realizado con dos tipos de señales: ruido de carácter aleatorio (banda ancha) y ruido periódico (banda estrecha). En la parte final del proyecto se muestran los resultados obtenidos y las conclusiones al respecto. Summary. This project is focused on the implementation of an active noise control system using genetic algorithms. For that, it has been taken into account the noise type wanted to be canceled and the controller design, a key part of the control system. The active noise control is only effective at low frequencies, up to 250 Hz, for which the passive elements lose effectiveness, and in small areas or enclosures and ducts. The controller must be able to follow all the possible variations of the acoustic field that might be produced (phase, frequency, amplitude, electro-acoustic transfer functions, etc.). It is based on adaptive FIR and IIR algorithms. The choice of a kind of filter or another depends on characteristics like linearity, causality and number of coefficients. Moreover, the transfer function of the controller has to be changing filter coefficients value thought an adaptive algorithm. In this project a genetic algorithm is used as adaptive algorithm, based on biological selection, simulating the evolutionary behavior of biological systems. The simulations have been implemented with two signal types: random noise (broadband) and periodic noise (narrowband). In the final part of the project the results and conclusions are shown.

Optimal Control Using Feedback Linearization for a Generalized T-S Model

In this paper, a fuzzy feedback linearization is used to control nonlinear systems described by Takagi-Suengo (T-S) fuzzy systems. In this work, an optimal controller is designed using the linear quadratic regulator (LQR). The well known weighting parameters approach is applied to optimize local and global approximation and modelling capability of T-S fuzzy model to improve the choice of the performance index and minimize it. The approach used here can be considered as a generalized version of T-S method. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the proposed optimal LQR algorithm.

Multiphase Design and Control Techniques Applied to a Forward Micro-Inverter

En la última década la potencia instalada de energía solar fotovoltaica ha crecido una media de un 49% anual y se espera que alcance el 16%del consumo energético mundial en el año 2050. La mayor parte de estas instalaciones se corresponden con sistemas conectados a la red eléctrica y un amplio porcentaje de ellas son instalaciones domésticas o en edificios. En el mercado ya existen diferentes arquitecturas para este tipo de instalaciones, entre las que se encuentras los módulos AC. Un módulo AC consiste en un inversor, también conocido como micro-inversor, que se monta en la parte trasera de un panel o módulo fotovoltaico. Esta tecnología ofrece modularidad, redundancia y la extracción de la máxima potencia de cada panel solar de la instalación. Además, la expansión de esta tecnología posibilitará una reducción de costes asociados a las economías de escala y a la posibilidad de que el propio usuario pueda componer su propio sistema. Sin embargo, el micro-inversor debe ser capaz de proporcionar una ganancia de tensión adecuada para conectar el panel solar directamente a la red, mientras mantiene un rendimiento aceptable en un amplio rango de potencias. Asimismo, los estándares de conexión a red deber ser satisfechos y el tamaño y el tiempo de vida del micro-inversor son factores que han de tenerse siempre en cuenta. En esta tesis se propone un micro-inversor derivado de la topología “forward” controlado en el límite entre los modos de conducción continuo y discontinuo (BCM por sus siglas en inglés). El transformador de la topología propuesta mantiene la misma estructura que en el convertidor “forward” clásico y la utilización de interruptores bidireccionales en el secundario permite la conexión directa del inversor a la red. Asimismo el método de control elegido permite obtener factor de potencia cercano a la unidad con una implementación sencilla. En la tesis se presenta el principio de funcionamiento y los principales aspectos del diseño del micro-inversor propuesto. Con la idea de mantener una solución sencilla y de bajo coste, se ha seleccionado un controlador analógico que está originalmente pensado para controlar un corrector del factor de potencia en el mismo modo de conducción que el micro-inversor “forward”. La tesis presenta las principales modificaciones necesarias, con especial atención a la detección del cruce por cero de la corriente (ZCD por sus siglas en inglés) y la compatibilidad del controlador con la inclusión de un algoritmo de búsqueda del punto de máxima potencia (MPPT por sus siglas en inglés). Los resultados experimentales muestran las limitaciones de la implementación elegida e identifican al transformador como el principal contribuyente a las pérdidas del micro-inversor. El principal objetivo de esta tesis es contribuir a la aplicación de técnicas de control y diseño de sistemas multifase en micro-inversores fotovoltaicos. En esta tesis se van a considerar dos configuraciones multifase diferentes aplicadas al micro-inversor “forward” propuesto. La primera consiste en una variación con conexión paralelo-serie que permite la utilización de transformadores con una relación de vueltas baja, y por tanto bien acoplados, para conseguir una ganancia de tensión adecuada con un mejor rendimiento. Esta configuración emplea el mismo control BCM cuando la potencia extraída del panel solar es máxima. Este método de control implica que la frecuencia de conmutación se incrementa considerablemente cuando la potencia decrece, lo que compromete el rendimiento. Por lo tanto y con la intención de mantener unos bueno niveles de rendimiento ponderado, el micro-inversor funciona en modo de conducción discontinuo (DCM, por sus siglas en inglés) cuando la potencia extraía del panel solar es menor que la máxima. La segunda configuración multifase considerada en esta tesis es la aplicación de la técnica de paralelo con entrelazado. Además se han considerado dos técnicas diferentes para decidir el número de fases activas: dependiendo de la potencia continua extraída del panel solar y dependiendo de la potencia instantánea demandada por el micro-inversor. La aplicación de estas técnicas es interesante en los sistemas fotovoltaicos conectados a la red eléctrica por la posibilidad que brindan de obtener un rendimiento prácticamente plano en un amplio rango de potencia. Las configuraciones con entrelazado se controlan en DCM para evitar la necesidad de un control de corriente, lo que es importante cuando el número de fases es alto. Los núcleos adecuados para todas las configuraciones multifase consideradas se seleccionan usando el producto de áreas. Una vez seleccionados los núcleos se ha realizado un diseño detallado de cada uno de los transformadores. Con la información obtenida de los diseños y los resultados de simulación, se puede analizar el impacto que el número de transformadores utilizados tiene en el tamaño y el rendimiento de las distintas configuraciones. Los resultados de este análisis, presentado en esta tesis, se utilizan posteriormente para comparar las distintas configuraciones. Muchas otras topologías se han presentado en la literatura para abordar los diferentes aspectos a considerar en los micro-inversores, que han sido presentados anteriormente. La mayoría de estas topologías utilizan un transformador de alta frecuencia para solventar el salto de tensión y evitar problemas de seguridad y de puesta a tierra. En cualquier caso, es interesante evaluar si topologías sin aislamiento galvánico son aptas para su utilización como micro-inversores. En esta tesis se presenta una revisión de inversores con capacidad de elevar tensión, que se comparan bajo las mismas especificaciones. El objetivo es proporcionar la información necesaria para valorar si estas topologías son aplicables en los módulos AC. Las principales contribuciones de esta tesis son: • La aplicación del control BCM a un convertidor “forward” para obtener un micro-inversor de una etapa sencillo y de bajo coste. • La modificación de dicho micro-inversor con conexión paralelo-series de transformadores que permite reducir la corriente de los semiconductores y una ganancia de tensión adecuada con transformadores altamente acoplados. • La aplicación de técnicas de entrelazado y decisión de apagado de fases en la puesta en paralelo del micro-inversor “forward”. • El análisis y la comparación del efecto en el tamaño y el rendimiento del incremento del número de transformadores en las diferentes configuraciones multifase. • La eliminación de las medidas y los lazos de control de corriente en las topologías multifase con la utilización del modo de conducción discontinuo y un algoritmo MPPT sin necesidad de medida de corriente. • La recopilación y comparación bajo las mismas especificaciones de topologías inversoras con capacidad de elevar tensión, que pueden ser adecuadas para la utilización como micro-inversores. Esta tesis está estructurada en seis capítulos. El capítulo 1 presenta el marco en que se desarrolla la tesis así como el alcance de la misma. En el capítulo 2 se recopilan las topologías existentes de micro-invesores con aislamiento y aquellas sin aislamiento cuya implementación en un módulo AC es factible. Asimismo se presenta la comparación entre estas topologías bajo las mismas especificaciones. El capítulo 3 se centra en el micro-inversor “forward” que se propone originalmente en esta tesis. La aplicación de las técnicas multifase se aborda en los capítulos 4 y 5, en los que se presentan los análisis en función del número de transformadores. El capítulo está orientado a la propuesta paralelo-serie mientras que la configuración con entrelazado se analiza en el capítulo 5. Por último, en el capítulo 6 se presentan las contribuciones de esta tesis y los trabajos futuros. ABSTRACT In the last decade the photovoltaic (PV) installed power increased with an average growth of 49% per year and it is expected to cover the 16% of the global electricity consumption by 2050. Most of the installed PV power corresponds to grid-connected systems, with a significant percentage of residential installations. In these PV systems, the inverter is essential since it is the responsible of transferring into the grid the extracted power from the PV modules. Several architectures have been proposed for grid-connected residential PV systems, including the AC-module technology. An AC-module consists of an inverter, also known as micro-inverter, which is attached to a PV module. The AC-module technology offers modularity, redundancy and individual MPPT of each module. In addition, the expansion of this technology will enable the possibility of economies of scale of mass market and “plug and play” for the user, thus reducing the overall cost of the installation. However, the micro-inverter must be able to provide the required voltage boost to interface a low voltage PV module to the grid while keeping an acceptable efficiency in a wide power range. Furthermore, the quality standards must be satisfied and size and lifetime of the solutions must be always considered. In this thesis a single-stage forward micro-inverter with boundary mode operation is proposed to address the micro-inverter requirements. The transformer in the proposed topology remains as in the classic forward converter and bidirectional switches in the secondary side allows direct connection to the grid. In addition the selected control strategy allows high power factor current with a simple implementation. The operation of the topology is presented and the main design issues are introduced. With the intention to propose a simple and low-cost solution, an analog controller for a PFC operated in boundary mode is utilized. The main necessary modifications are discussed, with the focus on the zero current detection (ZCD) and the compatibility of the controller with a MPPT algorithm. The experimental results show the limitations of the selected analog controller implementation and the transformer is identified as a main losses contributor. The main objective of this thesis is to contribute in the application of control and design multiphase techniques to the PV micro-inverters. Two different multiphase configurations have been applied to the forward micro-inverter proposed in this thesis. The first one consists of a parallel-series connected variation which enables the use of low turns ratio, i.e. well coupled, transformers to achieve a proper voltage boost with an improved performance. This multiphase configuration implements BCM control at maximum load however. With this control method the switching frequency increases significantly for light load operation, thus jeopardizing the efficiency. Therefore, in order to keep acceptable weighted efficiency levels, DCM operation is selected for low power conditions. The second multiphase variation considered in this thesis is the interleaved configuration with two different phase shedding techniques: depending on the DC power extracted from the PV panel, and depending on the demanded instantaneous power. The application of interleaving techniques is interesting in PV grid-connected inverters for the possibility of flat efficiency behavior in a wide power range. The interleaved variations of the proposed forward micro-inverter are operated in DCM to avoid the current loop, which is important when the number of phases is large. The adequate transformer cores for all the multiphase configurations are selected according to the area product parameter and a detailed design of each required transformer is developed. With this information and simulation results, the impact in size and efficiency of the number of transformer used can be assessed. The considered multiphase topologies are compared in this thesis according to the results of the introduced analysis. Several other topological solutions have been proposed to solve the mentioned concerns in AC-module application. The most of these solutions use a high frequency transformer to boost the voltage and avoid grounding and safety issues. However, it is of interest to assess if the non-isolated topologies are suitable for AC-module application. In this thesis a review of transformerless step-up inverters is presented. The compiled topologies are compared using a set benchmark to provide the necessary information to assess whether non-isolated topologies are suitable for AC-module application. The main contributions of this thesis are: • The application of the boundary mode control with constant off-time to a forward converter, to obtain a simple and low-cost single-stage forward micro-inverter. • A modification of the forward micro-inverter with primary-parallel secondary-series connected transformers to reduce the current stress and improve the voltage gain with highly coupled transformers. •The application of the interleaved configuration with different phase shedding strategies to the proposed forward micro-inverter. • An analysis and comparison of the influence in size and efficiency of increasing the number of transformers in the parallel-series and interleaved multiphase configurations. • Elimination of the current loop and current measurements in the multiphase topologies by adopting DCM operation and a current sensorless MPPT. • A compilation and comparison with the same specifications of suitable non-isolated step-up inverters. This thesis is organized in six chapters. In Chapter 1 the background of single-phase PV-connected systems is discussed and the scope of the thesis is defined. Chapter 2 compiles the existing solutions for isolated micro-inverters and transformerless step-up inverters suitable for AC-module application. In addition, the most convenient non-isolated inverters are compared using a defined benchmark. Chapter 3 focuses on the originally proposed single-stage forward micro-inverter. The application of multiphase techniques is addressed in Chapter 4 and Chapter 5, and the impact in different parameters of increasing the number of phases is analyzed. In Chapter 4 an original primary-parallel secondary-series variation of the forward micro-inverter is presented, while Chapter 5 focuses on the application of the interleaved configuration. Finally, Chapter 6 discusses the contributions of the thesis and the future work.

Desarrollo de software de control y medida para goniofotómetro de tipo B

El proyecto trata del desarrollo de un software para realizar el control de la medida de la distribución de intensidad luminosa en luminarias LED. En el trascurso del proyecto se expondrán fundamentos teóricos sobre fotometría básica, de los cuales se extraen las condiciones básicas para realizar dicha medida. Además se realiza una breve descripción del hardware utilizado en el desarrollo de la máquina, el cual se basa en una placa de desarrollo Arduino Mega 2560, que, gracias al paquete de Labview “LIFA” (Labview Interface For Arduino”), será posible utilizarla como tarjeta de adquisición de datos mediante la cual poder manejar tanto sensores como actuadores, para las tareas de control. El instrumento de medida utilizado en este proyecto es el BTS256 de la casa GigaHerzt-Optik, del cual se dispone de un kit de desarrollo tanto en lenguaje C++ como en Labview, haciendo posible programar aplicaciones basadas en este software para realizar cualquier tipo de adaptación a las necesidades del proyecto. El software está desarrollado en la plataforma Labview 2013, esto es gracias a que se dispone del kit de desarrollo del instrumento de medida, y del paquete LIFA. El objetivo global del proyecto es realizar la caracterización de luminarias LED, de forma que se obtengan medidas suficientes de la distribución de intensidad luminosa. Los datos se recogerán en un archivo fotométrico específico, siguiendo la normativa IESNA 2002 sobre formato de archivos fotométricos, que posteriormente será utilizado en la simulación y estudio de instalaciones reales de la luminaria. El sistema propuesto en este proyecto, es un sistema basado en fotometría tipo B, utilizando coordenadas VH, desarrollando un algoritmo de medida que la luminaria describa un ángulo de 180º en ambos ejes, con una resolución de 5º para el eje Vertical y 22.5º para el eje Horizontal, almacenando los datos en un array que será escrito en el formato exigido por la normativa. Una vez obtenidos los datos con el instrumento desarrollado, el fichero generado por la medida, es simulado con el software DIALux, obteniendo unas medidas de iluminación en la simulación que serán comparadas con las medidas reales, intentando reproducir en la simulación las condiciones reales de medida. ABSTRACT. The project involves the development of software for controlling the measurement of light intensity distribution in LEDs. In the course of the project theoretical foundations on basic photometry, of which the basic conditions for such action are extracted will be presented. Besides a brief description of the hardware used in the development of the machine, which is based on a Mega Arduino plate 2560 is made, that through the package Labview "LIFA" (Interface For Arduino Labview "), it is possible to use as data acquisition card by which to handle both sensors and actuators for control tasks. The instrument used in this project is the BTS256 of GigaHerzt-Optik house, which is available a development kit in both C ++ language as LabView, making it possible to program based on this software applications for any kind of adaptation to project needs. The software is developed in Labview 2013 platform, this is thanks to the availability of the SDK of the measuring instrument and the LIFA package. The overall objective of the project is the characterization of LED lights, so that sufficient measures the light intensity distribution are obtained. Data will be collected on a specific photometric file, following the rules IESNA 2002 on photometric format files, which will then be used in the simulation and study of actual installations of the luminaire. The proposed in this project is a system based on photometry type B system using VH coordinates, developing an algorithm as the fixture describe an angle of 180 ° in both axes, with a resolution of 5 ° to the vertical axis and 22.5º for the Horizontal axis, storing data in an array to be written in the format required by the regulations. After obtaining the data with the instrument developed, the file generated by the measure, is simulated with DIALux software, obtaining measures of lighting in the simulation will be compared with the actual measurements, trying to play in the simulation the actual measurement conditions .

Automated wordlength optimization framework for multi-source statistical interval-based analysis of nonlinear systems with control-flow structures

El uso de aritmética de punto fijo es una opción de diseño muy extendida en sistemas con fuertes restricciones de área, consumo o rendimiento. Para producir implementaciones donde los costes se minimicen sin impactar negativamente en la precisión de los resultados debemos llevar a cabo una asignación cuidadosa de anchuras de palabra. Encontrar la combinación óptima de anchuras de palabra en coma fija para un sistema dado es un problema combinatorio NP-hard al que los diseñadores dedican entre el 25 y el 50 % del ciclo de diseño. Las plataformas hardware reconfigurables, como son las FPGAs, también se benefician de las ventajas que ofrece la aritmética de coma fija, ya que éstas compensan las frecuencias de reloj más bajas y el uso más ineficiente del hardware que hacen estas plataformas respecto a los ASICs. A medida que las FPGAs se popularizan para su uso en computación científica los diseños aumentan de tamaño y complejidad hasta llegar al punto en que no pueden ser manejados eficientemente por las técnicas actuales de modelado de señal y ruido de cuantificación y de optimización de anchura de palabra. En esta Tesis Doctoral exploramos distintos aspectos del problema de la cuantificación y presentamos nuevas metodologías para cada uno de ellos: Las técnicas basadas en extensiones de intervalos han permitido obtener modelos de propagación de señal y ruido de cuantificación muy precisos en sistemas con operaciones no lineales. Nosotros llevamos esta aproximación un paso más allá introduciendo elementos de Multi-Element Generalized Polynomial Chaos (ME-gPC) y combinándolos con una técnica moderna basada en Modified Affine Arithmetic (MAA) estadístico para así modelar sistemas que contienen estructuras de control de flujo. Nuestra metodología genera los distintos caminos de ejecución automáticamente, determina las regiones del dominio de entrada que ejercitarán cada uno de ellos y extrae los momentos estadísticos del sistema a partir de dichas soluciones parciales. Utilizamos esta técnica para estimar tanto el rango dinámico como el ruido de redondeo en sistemas con las ya mencionadas estructuras de control de flujo y mostramos la precisión de nuestra aproximación, que en determinados casos de uso con operadores no lineales llega a tener tan solo una desviación del 0.04% con respecto a los valores de referencia obtenidos mediante simulación. Un inconveniente conocido de las técnicas basadas en extensiones de intervalos es la explosión combinacional de términos a medida que el tamaño de los sistemas a estudiar crece, lo cual conlleva problemas de escalabilidad. Para afrontar este problema presen tamos una técnica de inyección de ruidos agrupados que hace grupos con las señales del sistema, introduce las fuentes de ruido para cada uno de los grupos por separado y finalmente combina los resultados de cada uno de ellos. De esta forma, el número de fuentes de ruido queda controlado en cada momento y, debido a ello, la explosión combinatoria se minimiza. También presentamos un algoritmo de particionado multi-vía destinado a minimizar la desviación de los resultados a causa de la pérdida de correlación entre términos de ruido con el objetivo de mantener los resultados tan precisos como sea posible. La presente Tesis Doctoral también aborda el desarrollo de metodologías de optimización de anchura de palabra basadas en simulaciones de Monte-Cario que se ejecuten en tiempos razonables. Para ello presentamos dos nuevas técnicas que exploran la reducción del tiempo de ejecución desde distintos ángulos: En primer lugar, el método interpolativo aplica un interpolador sencillo pero preciso para estimar la sensibilidad de cada señal, y que es usado después durante la etapa de optimización. En segundo lugar, el método incremental gira en torno al hecho de que, aunque es estrictamente necesario mantener un intervalo de confianza dado para los resultados finales de nuestra búsqueda, podemos emplear niveles de confianza más relajados, lo cual deriva en un menor número de pruebas por simulación, en las etapas iniciales de la búsqueda, cuando todavía estamos lejos de las soluciones optimizadas. Mediante estas dos aproximaciones demostramos que podemos acelerar el tiempo de ejecución de los algoritmos clásicos de búsqueda voraz en factores de hasta x240 para problemas de tamaño pequeño/mediano. Finalmente, este libro presenta HOPLITE, una infraestructura de cuantificación automatizada, flexible y modular que incluye la implementación de las técnicas anteriores y se proporciona de forma pública. Su objetivo es ofrecer a desabolladores e investigadores un entorno común para prototipar y verificar nuevas metodologías de cuantificación de forma sencilla. Describimos el flujo de trabajo, justificamos las decisiones de diseño tomadas, explicamos su API pública y hacemos una demostración paso a paso de su funcionamiento. Además mostramos, a través de un ejemplo sencillo, la forma en que conectar nuevas extensiones a la herramienta con las interfaces ya existentes para poder así expandir y mejorar las capacidades de HOPLITE. ABSTRACT Using fixed-point arithmetic is one of the most common design choices for systems where area, power or throughput are heavily constrained. In order to produce implementations where the cost is minimized without negatively impacting the accuracy of the results, a careful assignment of word-lengths is required. The problem of finding the optimal combination of fixed-point word-lengths for a given system is a combinatorial NP-hard problem to which developers devote between 25 and 50% of the design-cycle time. Reconfigurable hardware platforms such as FPGAs also benefit of the advantages of fixed-point arithmetic, as it compensates for the slower clock frequencies and less efficient area utilization of the hardware platform with respect to ASICs. As FPGAs become commonly used for scientific computation, designs constantly grow larger and more complex, up to the point where they cannot be handled efficiently by current signal and quantization noise modelling and word-length optimization methodologies. In this Ph.D. Thesis we explore different aspects of the quantization problem and we present new methodologies for each of them: The techniques based on extensions of intervals have allowed to obtain accurate models of the signal and quantization noise propagation in systems with non-linear operations. We take this approach a step further by introducing elements of MultiElement Generalized Polynomial Chaos (ME-gPC) and combining them with an stateof- the-art Statistical Modified Affine Arithmetic (MAA) based methodology in order to model systems that contain control-flow structures. Our methodology produces the different execution paths automatically, determines the regions of the input domain that will exercise them, and extracts the system statistical moments from the partial results. We use this technique to estimate both the dynamic range and the round-off noise in systems with the aforementioned control-flow structures. We show the good accuracy of our approach, which in some case studies with non-linear operators shows a 0.04 % deviation respect to the simulation-based reference values. A known drawback of the techniques based on extensions of intervals is the combinatorial explosion of terms as the size of the targeted systems grows, which leads to scalability problems. To address this issue we present a clustered noise injection technique that groups the signals in the system, introduces the noise terms in each group independently and then combines the results at the end. In this way, the number of noise sources in the system at a given time is controlled and, because of this, the combinato rial explosion is minimized. We also present a multi-way partitioning algorithm aimed at minimizing the deviation of the results due to the loss of correlation between noise terms, in order to keep the results as accurate as possible. This Ph.D. Thesis also covers the development of methodologies for word-length optimization based on Monte-Carlo simulations in reasonable times. We do so by presenting two novel techniques that explore the reduction of the execution times approaching the problem in two different ways: First, the interpolative method applies a simple but precise interpolator to estimate the sensitivity of each signal, which is later used to guide the optimization effort. Second, the incremental method revolves on the fact that, although we strictly need to guarantee a certain confidence level in the simulations for the final results of the optimization process, we can do it with more relaxed levels, which in turn implies using a considerably smaller amount of samples, in the initial stages of the process, when we are still far from the optimized solution. Through these two approaches we demonstrate that the execution time of classical greedy techniques can be accelerated by factors of up to ×240 for small/medium sized problems. Finally, this book introduces HOPLITE, an automated, flexible and modular framework for quantization that includes the implementation of the previous techniques and is provided for public access. The aim is to offer a common ground for developers and researches for prototyping and verifying new techniques for system modelling and word-length optimization easily. We describe its work flow, justifying the taken design decisions, explain its public API and we do a step-by-step demonstration of its execution. We also show, through an example, the way new extensions to the flow should be connected to the existing interfaces in order to expand and improve the capabilities of HOPLITE.

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.

Logic-Based Outer-Approximation Algorithm for Solving Discrete-Continuous Dynamic Optimization Problems

We present an extension of the logic outer-approximation algorithm for dealing with disjunctive discrete-continuous optimal control problems whose dynamic behavior is modeled in terms of differential-algebraic equations. Although the proposed algorithm can be applied to a wide variety of discrete-continuous optimal control problems, we are mainly interested in problems where disjunctions are also present. Disjunctions are included to take into account only certain parts of the underlying model which become relevant under some processing conditions. By doing so the numerical robustness of the optimization algorithm improves since those parts of the model that are not active are discarded leading to a reduced size problem and avoiding potential model singularities. We test the proposed algorithm using three examples of different complex dynamic behavior. In all the case studies the number of iterations and the computational effort required to obtain the optimal solutions is modest and the solutions are relatively easy to find.

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations.

Genetic algorithm-based spinning reserve dispatching in a competitive electricity market

Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses haw been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market.

A lightweight encryption algorithm for mobile online multimedia devices

Online multimedia data needs to be encrypted for access control. To be capable of working on mobile devices such as pocket PC and mobile phones, lightweight video encryption algorithms should be proposed. The two major problems in these algorithms are that they are either not fast enough or unable to work on highly compressed data stream. In this paper, we proposed a new lightweight encryption algorithm based on Huffman error diffusion. It is a selective algorithm working on compressed data. By carefully choosing the most significant parts (MSP), high performance is achieved with proper security. Experimental results has proved the algorithm to be fast. secure: and compression-compatible.

Biologically inspired joint control for a humanoid robot

The GuRm is a 1.2m tall, 23 degree of freedom humanoid consuucted at the University of Queensland for research into humanoid robotics. The key challenge being addressed by the GuRw projcct is the development of appropriate learning strategies for control and coodinadon of the robot’s many joints. The development of learning strategies is Seen as a way to sidestep the inherent intricacy of modeling a multi-DOP biped robot. This paper outlines the approach taken to generate an appmpria*e control scheme for the joinis of the GuRoo. The paper demonsrrates the determination of local feedback control parameters using a genetic algorithm. The feedback loop is then augmented by a predictive modulator that learns a form of feed-fonward control to overcome the irregular loads experienced at each joint during the gait cycle. The predictive modulator is based on thc CMAC architecture. Results from tats on the GuRoo platform show that both systems provide improvements in stability and tracking of joint control.

Neural control of a batch distillation

The purpose of the work reported here was to investigate the application of neural control to a common industrial process. The chosen problem was the control of a batch distillation. In the first phase towards deployment, a complex software simulation of the process was controlled. Initially, the plant was modelled with a neural emulator. The neural emulator was used to train a neural controller using the backpropagation through time algorithm. A high accuracy was achieved with the emulator after a large number of training epochs. The controller converged more rapidly, but its performance varied more widely over its operating range. However, the controlled system was relatively robust to changes in ambient conditions.

Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.