Inverse Design of Three-Dimensional Frequency Selective Structures and Metamaterials using Multi-Objective Lazy Ant Colony Optimization

With the rise of big data and the “internet of things,” wireless signals permeate today’s environment more than ever before. As the demand for information and security continues to expand, the need for filtering a crowded signal space will become increasingly important. Although existing devices can achieve this with additional components, such as in-line filters and low noise amplifiers, these approaches introduce additional bulk, cost and complexity. An alternative, low-cost solution to filtering these signals can be achieved through the use of Frequency Selective Surfaces (FSSs), which are commonly used in antennas, polarizers, radomes, and intelligent architecture. FSSs typically consist of a doubly-periodic array of unit cells, which acts as a spatial electromagnetic filter that selectively rejects or transmits electromagnetic waves, based on the unit cell’s geometry and material properties. Unlike traditional analog filters, spatial filters must also account for the polarization and incidence angle of signals; thus, an ideal FSS maintains a given frequency response for all polarizations and incidence angles. Traditional FSS designs have ranged from planar structures with canonical shapes to miniaturized and multi-layer designs using fractals and other space-filling geometries. More recently, FSS research has expanded into three-dimensional (3D) designs, which have demonstrated enhanced fields of view over traditional planar and multi-layer designs. To date, nearly all FSSs still suffer from significant shifts in resonant frequencies or onset of grating lobes at incidence angles beyond 60 degrees in one or more polarizations. Additionally, while recent advances in additive manufacturing techniques have made fully 3D FSS designs increasingly popular, design tools to exploit these fabrication methods to develop FSSs with ultra-wide Fields of View (FOV) do not currently exist. In this dissertation, a Multi-Objective Lazy Ant Colony Optimization (MOLACO) scheme will be introduced and applied to the problem of 3D FSS design for extreme FOVs. The versatility of this algorithm will further be demonstrated through application to the design of meander line antennas, optical antennas, and phase-gradient metasurfaces

Contributions to the development of the CRO-SL algorithm: Engineering applications problems

This Ph.D. thesis discusses advanced design issues of the evolutionary-based algorithm \textit{"Coral Reef Optimization"}, in its Substrate-Layer (CRO-SL) version, for optimization problems in Engineering Applications. The problems that can be tackled with meta-heuristic approaches is very wide and varied, and it is not exclusive of engineering. However we focus the Thesis on it area, one of the most prominent in our time. One of the proposed application is battery scheduling problem in Micro-Grids (MGs). Specifically, we consider an MG that includes renewable distributed generation and different loads, defined by its power profiles, and is equipped with an energy storage device (battery) to address its programming (duration of loading / discharging and occurrence) in a real scenario with variable electricity prices. Also, we discuss a problem of vibration cancellation over structures of two and four floors, using Tuned Mass Dampers (TMD's). The optimization algorithm will try to find the best solution by obtaining three physical parameters and the TMD location. As another related application, CRO-SL is used to design Multi-Input-Multi-Output Active Vibration Control (MIMO-AVC) via inertial-mass actuators, for structures subjected to human induced vibration. In this problem, we will optimize the location of each actuator and tune control gains. Finally, we tackle the optimization of a textile modified meander-line Inverted-F Antenna (IFA) with variable width and spacing meander, for RFID systems. Specifically, the CRO-SL is used to obtain an optimal antenna design, with a good bandwidth and radiation pattern, ideal for RFID readers. Radio Frequency Identification (RFID) has become one of the most numerous manufactured devices worldwide due to a reliable and inexpensive means of locating people. They are used in access and money cards and product labels and many other applications.Comment: arXiv admin note: text overlap with arXiv:1806.02654 by other author

Una contribución a las técnicas de diseño asistido por ordenador para antenas y dispositivos pasivos de microondas basadas en el método de los elemententos finitos

En esta tesis doctoral desarrollamos una nueva metodología de diseño que permite la obtención de circuitos pasivos de microondas tipo plano-H o con simetría de revolución con perfiles arbitrarios. El proceso de diseño culmina con un resultado óptimo independiente del punto de partida. Para obtener una respuesta eléctrica con suficiente eficiencia como para ser utilizada en un ciclo iterativo, hemos desarrollado un método de onda completa basado en el Método de los Elementos Finitos (M.E.F.). Éste, analiza en dos dimensiones (2-D) estas estructuras, agilizando enormemente el proceso de cálculo respecto al caso 3-D. Hemos combinado la segmentación de circuitos, el barrido en frecuencia (a través de método de Padè via Lanczos) y el M.E.F. en 2-D, y lo hemos bautizado con sus siglas en inglés como S.F.E.L.P. 2-D. La versión de S.F.E.L.P. 2-D para circuitos plano-H permite analizar estructuras en guíaonda como desfasadores, codos, divisores de potencia, dipleores, etc... . Además, pueden incluirse materiales dieléctricos mientras preserven la simetría de la estructura. Los accesos a estos circuitos se hace a través de puertas planas rectangulares y/o puertas radiales. Incluyendo el número de modos preciso en cada puerta, S.F.E.L.P. obtiene la Matriz de Dispersión Generalizada (M.D.G.). A partir de esta matriz conocemos todos los parámetros de interés del dispositivo como las pérdidads de retorno, desfases, etc... . La versión de S.F.E.L.P. 2-D para circuitos con simetría de revolución permite analizar resonadores y diversos tipos de antenas como monopolos, reflectores y bocinas (incluidas aquellas cargadas con diélectrico o corrugadas). Cerramos el dominio de análisis con una puerta esférica sobre la que se imprime una expansión modal. De la misma manera que antes, obtenemos una M.D.G. que nos proporciona directamente el coeficientede reflexión y, a través de la propagación de modos esféricos, el diagrama de radiación y la directividad. Hemos desarrollado una técnica que permite desplazar puertas esféricas que, utilizada junto con la técnica de segmentación, permite el análisis eficiente de reflectores con S.F.E.L.P. 2-D. También hemos desarrollado un algoritmo de optimización que permite encontrar una solución globalmente óptima al problema electromagnético, teniendo en cuenta las restricciones tecnológicas de la técnica de fabricación con la que vayamos a construir el dispositivo. Empleamos una versión de Simulated Annealing (S.A.) que modifica todos sus parámetros de control a través del muestreo de algunos valores estadísticos. Hemos establecido una condición de parada que detiene el proceso en el menor número de iteraciones y, a la vez, permite obtener un diseño robusto frente a errores en su fabricación. Con esta herramienta hemos diseñado y fabricado un codo de 90 grados de longitud mínima y bajo coeficiente de reflexión en banda ancha. Además,hemos diseñado otros circuitos plano-H como desfasadores, divisores de potencia y un diplexor. Por último, hemos diseñado bocinas cargadas con dieléctrico con simetría de revolución en diferentes configuraciones, una bocina corrugada y un reflector parabólico. Todo esto para demostrar la bondad de este método de diseño constituido por S.F.E.L.P. 2-D y S.A.

SYNTHESIS OF ANALOG FILTER USING EVOLUTIONARY STRATEGIES

This project is designed to mimic automation of analog filter analysis to examine some efficient algorithm useful in filter synthesis. The process involves formation of MNA matrix to create symbolic transfer functions in s domain, continuous and discrete sizing of LC components using evolutionary algorithms; and finally, the performance of each algorithm is studied based on fixed error criterion and adaptability to discrete problem. Efficiency of the clever algorithms in optimizing piecewise filter response is ultimately dependent on the quality of the fitness function. A unique measure of error called Sum of Maximum Deviation (SMD) is implemented which evaluates the performance of global optimizer by weighing important details per unit sampled frequency. From global optimization point of view, it is certain that discrete evolutionary algorithms lacks the absoluteness of brute force analysis; however, the general continuous optimization is stretched to accommodate a new proximity estimator alongside its elementary constraint

INTELLIGENT METHODS FOR OPTIMUM ONLINE ADAPTIVE COORDINATION OF OVERCURRENT RELAYS

During the operation in a modern power distribution system, some abnormal events may happen, such as over-voltage, faults, under-frequency and overloading, and so on. These abnormal events may cause a power outage in a distribution system or damages on the equipment in a distribution system. Hence these abnormal events should be identified and isolated by protection systems as quickly as possible to make sure we can maintain a stable and reliable distribution system to supply adequate electric power to the largest number of consumers as we can. To sum up, we need stable and reliable protection systems to satisfy this requirement. Chapter 1 of the dissertation is a brief introduction to my research contents. Firstly, the background of a distribution system and the protection systems in a power system will be introduced in the first subchapter. Then there will be a review of existing methods of optimum coordination of overcurrent relays using different optimal techniques. The dissertation outline will be illustrated in the end. Chapter 2 of the dissertation describes a novel method of optimum online adaptive coordination of overcurrent relays using the genetic algorithm. In this chapter, the basic idea of the proposed methods will be explained in the first subchapter. It includes the genetic algorithm concepts and details about how it works as an optimal technique. Then three different types of simulation systems will be used in this part. The first one is a basic distribution system without distributed generations (DGs); the second one is similar to the first one but with load variations; the last simulation system is similar to the first one but with a distributed generation in it. Using three different simulation systems will demonstrate that the coordination of overcurrent relays is influenced by different operating conditions of the distribution system. In Chapter 3, a larger sized distribution system with more distributed generations and loads will be simulated and used for verifying the proposed method in a more realistic environment. In addition, the effects of fault location on the optimum coordination of overcurrent relays will be discussed here. In Chapter 4, the optimal differential evolution (DE) technique will be introduced. Because of the requirement of the online adaptive function, the optimal process needs to be accomplished as soon as possible. Through the comparison between genetic algorithm and differential evolution on the optimum coordination of overcurrent relays, we found that differential evolution is much faster than the genetic algorithm, especially when the size of the distribution system grows. Therefore, the differential evolution optimal technique is more suited than the genetic algorithm to realize online adaptive function. Chapter 5 presents the conclusion of the research work that has been done in this dissertation

Advanced Signal Processing Techniques Applied to Power Systems Control and Analysis

The work published in this book is related to the application of advanced signal processing in smart grids, including power quality, data management, stability and economic management in presence of renewable energy sources, energy storage systems, and electric vehicles. The distinct architecture of smart grids has prompted investigations into the use of advanced algorithms combined with signal processing methods to provide optimal results. The presented applications are focused on data management with cloud computing, power quality assessment, photovoltaic power plant control, and electrical vehicle charge stations, all supported by modern AI-based optimization methods

Contributions to the development of the CRO-SL algorithm: Engineering applications problems

Esta tesis doctoral aborda el diseño del algoritmo evolutivo Coral Reef Optimization, en su versión Substrate-Layer, para la optimización de problemas en diferentes ámbitos de la ingeniería. Los algoritmos evolutivos han sido ampliamente aplicados a problemas de optimización difícilmente abordables de manera analítica, ya sea por tener espacios de búsqueda enormes o por ser no lineales. Si bien la ejecución de estos algoritmos no supone un gran coste computacional hoy en día, sí lo supone las funciones de coste que constantemente deben evaluar. La creciente capacidad de procesamiento en la tecnología le abre las puertas al abordaje de problemas temporalmente costosos por medio de la metaheurística. Uno de los inconvenientes de esta, es que no hay forma de saber a priori cuál de ellos es mejor para un problema específico, y sea cual sea la elección, la ejecución del mismo no te asegura que vayas a obtener el óptimo. Es por este motivo por el cual se ha elegido el algoritmo CRO-SL, ya que permite combinar los procesos de búsqueda más potentes, ayudándose entre ellos para alcanzar el óptimo global. La problemática a la que se puede aplicar la metaheurística es muy variada y no tiene por qué ser exclusiva de la ingeniería, sin embargo en esta tesis sí vamos a centrarla en ella. Una de las aplicaciones que vamos a ver es el diseño de una antena de tipo F invertida (IFA), para sistemas de IDentificación por Radio-Frecuencia (RFID). Estas han sido muy utilizadas en productos a lo largo de todo el mundo tanto en tarjetas de crédito como en etiquetas de productos debido a su pequeño tamaño y a una fabricación sencilla y barata. En concreto, en este trabajo se usarán como conductores láminas de cobre y como dieléctrico, fieltro. Se pretende así, diseñar el ancho y el espaciamiento de estas tiras de cobre para que emita en un ancho de banda determinado con una calidad determinada. También se abordará un problema de control de vibración en estructuras de dos y cuatro pisos mediante el uso de elementos amortiguadores pasivos, TMD's(Tunned Mass Dampers). Esta aplicación viene motivada por la necesidad de mitigar las vibraciones procedentes de la tierra, como pudiera ser en un terremoto. En este caso el algoritmo no sólo intentará optimizar las características físicas de los TMD's sino también su colocación dentro del edificio. En tercer lugar, se realizará un control activo de las vibraciones que generamos los humanos al caminar en una estructura civil, mediante el uso de actuadores de masa inercial. En este problema se tratará de optimizar la localización de los actuadores así como sintonizar las ganancias de control. Por último veremos un problema de optimización de planificación de las baterías en micro-redes(MG). Específicamente, consideramos una MG que incluye generación renovable y diferentes cargas, definidas por sus perfiles de potencia, y está equipada con un dispositivo de almacenamiento de energía (batería) para abordar su programación (duración de carga / descarga y ocurrencia) en un escenario real de precios variables de electricidad. Mediante la aplicación del CRO-SL a estos problemas se pretende cumplir dos objetivos. El primero es comprobar la aptitud del propio algoritmo en las aplicaciones mencionadas. Para ello además se realizarán experimentos con los algoritmos más populares y los resultados podrán ser comparados entre sí. El segundo es promover el uso del CRO-SL como herramienta de comparación entre métodos de exploración. Algunos de los algoritmos metaheurísticos se basan en la iteración de un proceso de búsqueda sobre una población de individuos codificados, que encarnan la solución a un determinado problema. El CRO-SL toma prestado la forma en la que otros algoritmos cambian a sus individuos, y forma nuevas soluciones de manera paralela. Entre los algoritmos evolutivos más conocidos que vamos a ver durante el desarrollo de esta tesis se encuentran los algoritmos Harmony Search, Differential Evolution y Genetic Algorithm. Además se verán otro tipo de mutaciones como la de tipo Gaussiana, mutación simple o cruce multipunto. Por último, durante el desarrollo de esta tesis también se ha probado una nueva forma de búsqueda basada en atractores extraños. Gracias a la capacidad de comparación del CRO-SL podremos ver si esta nueva forma de búsqueda es útil o no

EM-driven miniaturization of high-frequency structures through constrained optimization

The trends afoot for miniaturization of high-frequency electronic devices require integration of active and passive high-frequency circuit elements within a single system. This high level of accomplishment not only calls for a cutting-edge integration technology but also necessitates accommodation of the corresponding circuit components within a restricted space in applications such as implantable devices, internet of things (IoT), or 5G communication systems. At the same time, size reduction does not remain the only demand. The performance requirements of the abovementioned systems form a conjugate demand to that of the size reduction, yet with a contrasting nature. A compromise can be achieved through constrained numerical optimization, in which two kinds of constrains may exist: equality and inequality ones. Still, the high cost of electromagnetic-based (EM-based) constraint evaluations remains an obstruction. This issue can be partly mitigated by implicit constraint handling using the penalty function approach. Nevertheless, securing its performance requires expensive guess-work-based identification of the optimum setup of the penalty coefficients. An additional challenge lies in allocating the design within or in the vicinity of a thin feasible region corresponding to equality constraints. Furthermore, multimodal nature of constrained miniaturization problems leads to initial design dependency of the optimization results. Regardless of the constraint type and the corresponding treatment techniques, the computational expenses of the optimization-based size reduction persist as a main challenge. This thesis attempts to address the abovementioned issues specifically pertaining to optimization-driven miniaturization of high frequency structures by developing relevant algorithms in a proper sequence. The first proposed approach with automated adjustment of the penalty functions is based on the concept of sufficient constraint violation improvement, thereby eliminating the costly initial trial-and-error stage for the identification of the optimum setup of the penalty factors. Another introduced approach, i.e., correction-based treatment of the equality constraints alleviates the difficulty of allocating the design within a thin feasible region where designs satisfying the equality constraints reside. The next developed technique allows for global size reduction of high-frequency components. This approach not only eliminates the aforementioned multimodality issues, but also accelerates the overall global optimization process by constructing a dimensionality-reduced surrogate model over a pre-identified feasible region as compared to the complete parameter search space. Further to the latter, an optimization framework employing multi-resolution EM-model management has been proposed to address the high cost issue. The said technique provides nearly 50 percent average acceleration of the optimization-based miniaturization process. The proposed technique pivots upon a newly-defined concept of model-fidelity control based on a combination of algorithmic metrics, namely convergence status and constraint violation level. Numerical validation of the abovementioned algorithms has also been provided using an extensive set of high-frequency benchmark structures. To the best of the author´s knowledge, the presented study is the first investigation of this kind in the literature and can be considered a contribution to the state of the art of automated high-frequency design and miniaturization

Optimization of microwave devices

This thesis deals with the optimization techniques for the improvement of the microwave devices performance. In particular, the technique proposed considers the Particle Swarm Optimization algorithm and applies such an algorithm to different devices. Different techniques are developed to connect the optimization with an electromagnetic analysis tool. In the first method the algorithm has been connected to a numerical technique for the evaluation of the device performance (FDFD). The second technique consists on the integration of the algorithm with a 3D Simulation CAD (HFSS, CST). The microwave devices under test are a ridge waveguide (in different configurations), a resonant cavity, a waveguide impedance transformer and an electromagnetic band gap structure. Both the approaches result to be effective for the purpose even in the event that a constraint between conficting requirements is requested