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Méthode d'optimisation mixte bio-inspirée : application à l'imagerie multi-spectrale et à la mesure d'audience / Mixed bio-inspired optimization method : Application to multispectral image processing and audience measurementMartin, Benoit 26 October 2018 (has links)
Cette thèse propose une nouvelle méthode d’optimisation bio-inspirée basée sur le GWO avec pour but de pouvoir résoudre des problèmes d’optimisation dits mixtes, c’est-à-dire des problèmes composés de variables continues et discrètes. Cette nouvelle méthode baptisée mixed GWO est ensuite appliquée à 2 problématiques distincts.Tout d’abord, le mixed GWO pourra permettre d’améliorer la qualité de la classification d’image par SVM. En effet, la fiabilité d’un SVM va dépendre de ses paramètres d’entraînement, et il n’existe pas de méthode non empirique et non exhaustive permettant de définir ces paramètres pour un problème de classification donné. Le mixed GWO se propose comme une solution à ce problème de paramétrage. La classification doit permettre à l’entreprise IntuiSense d’ajouter une brique de reconnaissance de genre à son outil de mesure d’audience ISAM.Ensuite, le mixedGWO est employé pour faire du débruitage et du démêlage de spectres en simultanée sur des images multi-spectrales ou hyper-spectrales. En effet, la qualité du démêlage des spectres va être particulièrement dépendant de la qualité du débruitage de l’image : faire ces 2 étapes simultanément permet donc un gain de temps et une fiabilité des résultats bien plus intéressants que les faire l’une après l’autre. / This thesis proposes a novel bio-inspired optimization method based on the GWOalgorithm, with the purpose of solving mixed optimization problems, i.e. problems with bothcontinuous and discrete variables. This novel method is named mixedGWO and is applied to2 distinct problematics.Firstly, the mixedGWO should permit to improve the quality of image classification bySVM. Indeed, a SVM accuracy will depend of its training parameters, and there is nonempirical and non exhaustive method to define these parameters for a given classificationproblem. Therefore, the mixedGWO can be used as a solution to this parametring problem.The improve classification should allow the company IntuiSense to add the gender recognition feature to its audience measurement tool ISAM.Secondly, the mixedGWO is used for joint denoising and unmixing of spectra in multispectral and hyper-spectral image processing. Indeed, the unmixing’s quality is stronglydependent of the denoising quality : doing these 2 steps simultaneously permits a gain oftime and a results’ accuracy way better than if they are done one after the other.
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Otimização da relação custo benefício de projetos de eficiência energética do tipo baixa rendaMota, Jorge Felipe Barbosa 09 September 2016 (has links)
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Previous issue date: 2016-09-09 / As concessionárias de energia são obrigadas a aplicar parte de sua receita operacional líquida na execução de projetos de eficiência energética, de acordo com a Agência Nacional de Energia Elétrica (ANEEL). O projeto do tipo baixa renda é parte desse portfólio de projetos possíveis e capta a maior parte dessa aplicação. Dessa forma, torna-se de suma importância a criação de uma metodologia para dimensionar os projetos dessa tipologia e direcionar as tomadas de decisões das concessionárias de energia do Brasil. Métodos de otimização bioinspirados tratam de problemas combinatórios e não lineares, caso do equacionamento matemático do cálculo da relação custo benefício de projetos de eficiência energética de tipologia baixa renda. O presente trabalho propõe a aplicação de dois métodos de otimização reconhecidos, a otimização por colônia de formigas, ou Ant Colony Optimization (ACO), e a otimização por enxame de partículas, ou Particle Swarm Optimization (PSO), para calcular e otimizar a relação custo benefício de projetos de eficiência energética regulatórios do tipo baixa renda. Sendo assim, aplica métodos computacionais bioinspirados no dimensionamento dos projetos de eficiência energética, além de otimizar esses projetos, obtendo o melhor resultado operacional, do ponto de vista da eficiência energética, com o melhor custo para a sociedade. / The electricity utilities are required to invest part of its net operating income in the implementation of energy efficiency projects, according to the National Electric Energy Agency (ANEEL). The low-income type design is part of portfolio of possible projects and captures most of this application. Thus, it becomes very important to create a methodology to scale projects of this type and direct decision making of utilities in Brazil. Bioinspired optimization methods deal with combinatorial and nonlinear problems, if the mathematical equations for calculating the cost benefit rate of energy efficiency projects in low-income type. This paper proposes two recognized bioinspired optimization methods, the Ant Colony Optimization (ACO) and the Particle Swarm Optimization (PSO) to calculate and optimize the cost effectiveness of energy efficiency regulatory projects, the low-income type. Thus, propose a scientific methods of sizing of the energy efficiency projects, while optimizing these projects, obtaining the best operating result, from the point of view of energy efficiency with the best cost to society.
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Algorithmes bio-inspirés pour la traduction automatique statistique / Bio-inspired Algorithms for Statistical Machine TranslationDouib, Ameur 01 February 2019 (has links)
Différentes composantes des systèmes de traduction automatique statistique sont considérées comme des problèmes d'optimisations. En effet, l'apprentissage du modèle de traduction, le décodage et l'optimisation des poids de la fonction log-linéaire sont trois importants problèmes d'optimisation. Savoir définir les bons algorithmes pour les résoudre est l'une des tâches les plus importantes afin de mettre en place un système de traduction performant. Plusieurs algorithmes d'optimisation sont proposés pour traiter les problèmes d'optimisation du décodeur. Ils sont combinés pour résoudre, d'une part, le problème de décodage qui produit une traduction dans la langue cible d'une phrase source, d'autre part, le problème d'optimisation des poids des scores combinés dans la fonction log-linéaire pour d'évaluation des hypothèses de traduction au cours du décodage. Le système de traduction statistique de référence est basé sur un algorithme de recherche en faisceau pour le décodage, et un algorithme de recherche linéaire pour l'optimisation des poids associés aux scores. Nous proposons un nouveau système de traduction avec un décodeur entièrement basé sur les algorithmes génétiques. Les algorithmes génétiques sont des algorithmes d'optimisation bio-inspirés qui simulent le processus de l'évolution naturelle des espèces. Ils permettent de manipuler un ensemble de solutions à travers plusieurs itérations pour converger vers des solutions optimales. Ce travail, nous permet d'étudier l'efficacité des algorithmes génétiques pour la traduction automatique statistique. L'originalité de notre proposition est de proposer deux algorithmes : un algorithme génétique, appelé GAMaT, comme décodeur pour un système de traduction statistique à base de segments, et un algorithme génétique, appelé GAWO, pour l'optimisation des poids de la fonction log-linéaire afin de l'utiliser comme fonction fitness pour GAMaT. Nous proposons également, une approche neuronale pour définir une nouvelle fonction fitness pour GAMaT. Cette approche consiste à utiliser un réseau de neurones pour l'apprentissage d'une fonction qui combine plusieurs scores, évaluant différents aspects d'une hypothèse de traduction, combinés auparavant dans la fonction log-linéaire, et qui prédit le score BLEU de cette hypothèse de traduction. Ce travail, nous a permis de proposer un nouveau système de traduction automatique statistique ayant un décodeur entièrement basé sur des algorithmes génétiques / Different components of statistical machine translation systems are considered as optimization problems. Indeed, the learning of the translation model, the decoding and the optimization of the weights of the log-linear function are three important optimization problems. Knowing how to define the right algorithms to solve them is one of the most important tasks in order to build an efficient translation system. Several optimization algorithms are proposed to deal with decoder optimization problems. They are combined to solve, on the one hand, the decoding problem that produces a translation in the target language for each source sentence, on the other hand, to solve the problem of optimizing the weights of the combined scores in the log-linear function to fix the translation evaluation function during the decoding. The reference system in statistical translation is based on a beam-search algorithm for the decoding, and a line search algorithm for optimizing the weights associated to the scores. We propose a new statistical translation system with a decoder entirely based on genetic algorithms. Genetic algorithms are bio-inspired optimization algorithms that simulate the natural process of evolution of species. They allow to handle a set of solutions through several iterations to converge towards optimal solutions. This work allows us to study the efficiency of the genetic algorithms for machine translation. The originality of our work is the proposition of two algorithms: a genetic algorithm, called GAMaT, as a decoder for a phrase-based machine translation system, and a second genetic algorithm, called GAWO, for optimizing the weights of the log-linear function in order to use it as a fitness function for GAMaT. We propose also, a neuronal approach to define a new fitness function for GAMaT. This approach consists in using a neural network to learn a function that combines several scores, which evaluate different aspects of a translation hypothesis, previously combined in the log-linear function, and that predicts the BLEU score of this translation hypothesis. This work allowed us to propose a new machine translation system with a decoder entirely based on genetic algorithms
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Alocação de geração distribuída em sistemas de distribuição de energia elétrica via otimização bioinspirada na ecolocalização de morcegosCoelho, Francisco Carlos Rodrigues 16 August 2013 (has links)
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Previous issue date: 2013-08-16 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / A alocação de geração distribuída em sistemas de distribuição de energia elétrica
consiste em definir a localização ótima para instalação de centrais geradoras distribuídas no
sistema e a quantidade de potência que deverá ser injetada por estas centrais, de modo a
minimizar as perdas técnicas inerentes aos sistemas de distribuição. Este é um problema de
otimização de difícil solução e que apresenta implicações ambientais e econômicas.
A técnica de otimização empregada nesta pesquisa para determinar a alocação dos
geradores distribuídos é recente, sendo a mesma bioinspirada. Ela se baseia na ecolocalização
de morcegos e foi desenvolvida em 2010 pelo pesquisador Xin-She Yang. Esta técnica de
otimização agrega em sua constituição conhecimento prévio adquirido por outras técnicas de
otimização, como enxame de partículas e busca harmônica, utilizando assim, as vantagens
inerentes a cada uma destas ferramentas. Esta característica confere à otimização via
ecolocalização uma expectativa de sucesso em problemas de difícil solução, com
características combinatórias, que é o caso do problema em estudo.
Com o intuito de melhorar o desempenho da técnica de otimização em questão, foi
proposta uma etapa adicional em sua constituição. Esta alteração no algoritmo original se
mostrou eficiente nas simulações realizadas, pois o mecanismo de busca modificado alcançou
resultados de melhor qualidade com maior frequência, tanto em sua validação, onde foram
utilizadas funções matemáticas não convexas, como na aplicação do método ao problema
referente à alocação de geração distribuída em sistemas de distribuição de energia elétrica.
Utilizando-se três sistemas teste, de trinta e três, de cinquenta e de sessenta e nove
barras, foram realizados testes com alocação exclusiva de potência ativa e reativa, e também
alocação simultânea destes dois tipos de potência, sendo que os resultados obtidos foram
comparados com resultados presentes na literatura especializada. Além das perdas, fatores
como perfil de tensão resultante nas barras e trajetória de convergência do algoritmo inspirado
na ecolocalização de morcegos foram analisados para a avaliação da metodologia de
otimização empregada nesta pesquisa. / The optimal distributed generation placement in electrical power systems is a complex
problem involving environmental and economical issues. The solution to this problem
consists of choosing the optimum location of distributed power plants, and to define the
amount of power that must be injected by these plants in order to minimize technical losses in
electrical distribution systems.
The optimization technique utilized in this work to determine the placement of
distributed generators is recent. It was developed in 2010 by Xin-She Yang. The optimization
procedure is inspired by the echolocation of bats phenomenon, and uses some previous
knowledge from others techniques, like Particle Swarm Optimization and Harmony Search,
combining their advantages. This feature gives the Bat-Inspired Algorithm an expectation of
success on difficult problems, such as the combinatorial problem under study.
In order to improve the performance of the optimization technique an additional step
was proposed in its search engine. Endowed with this change, the algorithm has achieved
better results more frequently. Nonconvex benchmark mathematical functions were used, as
well as in its application on distributed generation placement.
Using three different bus systems (33, 50 and 69 busses), simulations were performed
placing real and reactive Power separately, and those two kind of Power together. The
produced results were compared to specialized literature. Real power losses, bus voltage and
convergence trajectory indicates the level of success reached by the optimization technique
utilized in this research work.
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Naturanaloge Optimierungsverfahren zur Auslegung von Faserverbundstrukturen / Natural analog optimization methods for the design of fiber composite structuresUlke-Winter, Lars 18 April 2017 (has links) (PDF)
Die vollständige Ausnutzung des Leichtbaupotentials bei der Dimensionierung von mehrschichtigen endlosfaserverstärkten Strukturbauteilen erfordert die Bereitstellung von geeigneten Optimierungswerkzeugen, da bei der Auslegung eine große Anzahl von Entwurfsvariablen zu berücksichtigen sind. In dieser Arbeit werden Optimierungsalgorithmen und -strategien zur Lösung wissenschaftlicher Fragestellungen für industrielle Anwendungen bei der Konstruktion von entsprechenden Faserkunststoffverbunden entwickelt und bewertet. Um das breite Anwendungsspektrum aufzuzeigen, werden drei unterschiedliche repräsentative Problemstellungen bearbeitet. Dabei wird für Mehrschichtverbunde die Festigkeitsoptimierung hinsichtlich eines bruchtypbezogenen Versagenskriteriums vorgenommen, ein Dämpfungsmodell zur Materialcharakterisierung entworfen sowie eine bivalente Optimierungsstrategie zur Auslegung von gewickelten Hochdruckbehältern erstellt. Die Grundlage der entwickelten Methoden bilden dabei jeweils stochastische naturanaloge Optimierungsheuristiken, da die betrachteten Aufgabenstellungen nicht konvex sind und derartige Verfahren flexibel eingesetzt werden können. / The full utilization of the light weight potential in the dimensioning of multilayer fiber reinforced composites requires suitable optimization tools, since a large number of design variables has to be taken into account. In this work, optimization algorithms and strategies for the solution of scientific questions for industrial applications are developed and evaluated in the design of corresponding fiber-plastic composites. In order to show the wide range of applications, three different representative topics have been chosen. It will carry out a strength optimization for multilayer composites with regard to a type-related failure criterion, devolop a damping model for material characterization and established a bivalent optimization strategy for the design of wound high-pressure vessels. The developed methods are based on stochastic natural-analog optimization heuristics, since the considered tasks are not convex and such methods can be used in a very flexible manner.
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Estudo de vibrações induzidas por linhas férreas / Study of railway-induced vibrationsSilva, Gabriel Gomes 13 March 2017 (has links)
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Previous issue date: 2017-03-13 / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / Vibrations in the soil, induced by the passage of trains on railways, can cause countless effects in the areas bordering the railroads. In most problems, resort to simplified models of the system of interaction between rails foundation and trains for predicting responses that meet certain expectations, especially in order to avoid damaging nearby structures and also avoid discomfort of the people residing in areas surrounding the railway lines. Several soil-foundation interaction models have been developed seeking to get the answer to a foundation when subjected to static and dynamic actions, however, this response depends on multiple factors such as the nature and the mechanical characteristics of the terrain, the geometry of the elements involved, the rigidity of the foundation and the nature of his own excitement. Also of great importance in this type of analysis is the use of optimization techniques in order to obtain projects that are more realistic and safe from an engineering point of view. In this paper, was proposed a study of the effect of vibrations on railway lines, where it aims to model a system coupled between foundations and rails, subject to dynamic actions, in order to simulate the displacement in the time domain and in the domain of the frequency, using optimization for the construction of an optimum design that can attenuate the amplitudes of vibration of the system. / Vibrações transmitidas no solo, induzidas pela passagem de trens sobre vias férreas podem causar inúmeros efeitos nas áreas próximas às ferrovias. Na maioria dos problemas, recorre-se a modelos simplificados do sistema de interação entre trens, trilhos e fundação para a previsão de respostas que atendam a certas expectativas, principalmente, de modo a não danificar estruturas próximas e também evitar desconforto das pessoas que residem em áreas circunvizinhas a linhas férreas. Vários modelos de interação solo-fundação já foram desenvolvidos buscando-se obter a resposta de uma fundação quando sujeita a ações estáticas e dinâmicas, porém, essa resposta depende de múltiplos fatores, como a natureza e as características mecânicas do terreno, a geometria dos elementos envolvidos, a rigidez da fundação e, ainda, a natureza da própria excitação. Também é de grande importância neste tipo de análise, a utilização de técnicas de otimização visando obter projetos mais realistas e seguros do ponto de vista de engenharia. Neste trabalho, propõe-se um estudo acerca do efeito de vibrações em linhas férreas, onde se tem por objetivo modelar um sistema acoplado entre fundações e trilhos, sujeitos a ações dinâmicas, de maneira a simular o deslocamento no domínio do tempo e no domínio da frequência, utilizando-se de otimização para a construção de um projeto ótimo que possa atenuar as amplitudes de vibração do sistema.
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Alocação de capacitores em sistemas de distribuição de energia elétrica utilizando técnica de otimização bio-inspirada / Allocation of capacitors in distribution systems of electric power using optimization technique bio-inspiredDuque, Felipe Gomes 19 July 2016 (has links)
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Previous issue date: 2016-07-19 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho apresenta um algoritmo baseado na técnica de otimização bio-inspirada denominada Monkey Search (MS) para alocação ótima de bancos de capacitores em sistemas de distribuição. O método proposto apresenta modificações e aprimoramentos da técnica MS para representar de forma adequada às características e restrições do problema de alocação de capacitores resultando em um novo algoritmo denominado Modified Monkey Search (MMS). O programa desenvolvido em MATLAB é utilizado para teste em diversos sistemas de distribuição. Os resultados obtidos apontam para um algoritmo com boa eficiência computacional. / This paper presents an algorithm based on bio-inspired optimization technique called Monkey Search (MS) for optimal allocation of capacitors in distribution systems. The proposed method presents modifications and enhancements of the MS technique to represent the characteristics and constraints of the problem related with capacitor allocation resulting in a new algorithm called Modified Monkey Search (MMS). The program developed in MATLAB is used to test multiple distribution systems. The results point to a computational efficient algorithm.
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Projeto de controladores de sistemas de potência utilizando otimização bioinspirada / Power system controllers design using bio-inspired optimizationPeres, Wesley 28 March 2016 (has links)
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Previous issue date: 2016-03-28 / Os Estabilizadores de Sistemas de Potência (ESP) têm sido usados por décadas para fornecer amortecimento às oscilações eletromecânicas através do controle de excitação dos geradores síncronos. No presente trabalho, são propostas metodologias para o projeto de estabilizadores por meio do ajuste de ganho e fase. O ajuste é realizado de forma simultânea (coordenada), considerando múltiplos pontos de operação com o objetivo de garantir a robustez dos controladores. Duas estruturas são consideradas: a descentralizada, que utiliza somente sinais locais, e a hierárquica, que utiliza sinais remotos. A dinâmica do sistema elétrico de potência é modelada em espaço de estados e o procedimento de ajuste é formulado como um problema de otimização para a maximização do coeficiente de amortecimento do autovalor dominante do sistema em malha fechada considerando todos os pontos de operação. As metodologias, aqui abordadas, são baseadas em métodos de otimização bioinspirados no comportamento de enxames: Enxame de Partículas e Eco-localização de Morcegos. São desenvolvidas metodologias híbridas baseadas no acoplamento dos métodos bioinspirados com o Método do Gradiente Descendente para o refinamento dos ganhos dos controladores de forma a melhorar a busca local do processo de otimização. Com o objetivo de manter a diversidade da população, estratégias baseadas em multipopulações também são propostas. As metodologias propostas foram validadas através da simulação de sistemas teste de pequeno e médio porte, que são normalmente utilizados na literatura especializada. Os resultados são considerados promissores e acredita-se que as metodologias propostas possam ser de grande valor nessa área de conhecimento. / Power system stabilizers have been used for decades in order to provide the necessary damping of power system oscillations through generators excitation control. In this thesis, methodologies for stabilizers design (gain and phase compensation tuning) are presented. All stabilizers are simultaneously designed (coordinated design) taking into account a set of pre-specified operating conditions in order to ensure robustness. Two control structures are considered: decentralized (based on the use of local signals) and hierarchical (that uses remote signals). The power system dynamic is modeled in state space and the tuning procedure is formulated as an optimization problem in order to maximize the damping coefficient associated to the dominant pole in closed-loop operation for all operating conditions. The proposed methodologies are based on optimization algorithms bio-inspired in swarm behavior: Particle Swarm Optimization and Bat Algorithm. Hybrid methodologies are developed through coupling bio-inspired methods to the Steepest Descent method in order to enhance the local search procedure during the optimization process (only the stabilizers gain are adjusted in the local search). Multipopulational approaches are also developed in order to prevent the population diversity lost.
The proposed methodologies are validated by using small and medium-sized benchmark power systems. The results are considered to be promising and the proposed methodologies are found of a great value in this research field.
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Naturanaloge Optimierungsverfahren zur Auslegung von FaserverbundstrukturenUlke-Winter, Lars 14 February 2017 (has links)
Die vollständige Ausnutzung des Leichtbaupotentials bei der Dimensionierung von mehrschichtigen endlosfaserverstärkten Strukturbauteilen erfordert die Bereitstellung von geeigneten Optimierungswerkzeugen, da bei der Auslegung eine große Anzahl von Entwurfsvariablen zu berücksichtigen sind. In dieser Arbeit werden Optimierungsalgorithmen und -strategien zur Lösung wissenschaftlicher Fragestellungen für industrielle Anwendungen bei der Konstruktion von entsprechenden Faserkunststoffverbunden entwickelt und bewertet. Um das breite Anwendungsspektrum aufzuzeigen, werden drei unterschiedliche repräsentative Problemstellungen bearbeitet. Dabei wird für Mehrschichtverbunde die Festigkeitsoptimierung hinsichtlich eines bruchtypbezogenen Versagenskriteriums vorgenommen, ein Dämpfungsmodell zur Materialcharakterisierung entworfen sowie eine bivalente Optimierungsstrategie zur Auslegung von gewickelten Hochdruckbehältern erstellt. Die Grundlage der entwickelten Methoden bilden dabei jeweils stochastische naturanaloge Optimierungsheuristiken, da die betrachteten Aufgabenstellungen nicht konvex sind und derartige Verfahren flexibel eingesetzt werden können. / The full utilization of the light weight potential in the dimensioning of multilayer fiber reinforced composites requires suitable optimization tools, since a large number of design variables has to be taken into account. In this work, optimization algorithms and strategies for the solution of scientific questions for industrial applications are developed and evaluated in the design of corresponding fiber-plastic composites. In order to show the wide range of applications, three different representative topics have been chosen. It will carry out a strength optimization for multilayer composites with regard to a type-related failure criterion, devolop a damping model for material characterization and established a bivalent optimization strategy for the design of wound high-pressure vessels. The developed methods are based on stochastic natural-analog optimization heuristics, since the considered tasks are not convex and such methods can be used in a very flexible manner.
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