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Desenvolvimento de uma nova t?cnica para otimiza??o de circuitos planares inspirada no comportamento social das aranhasOliveira, Phelipe Sena 06 February 2017 (has links)
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Previous issue date: 2017-02-06 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico (CNPq) / As novas configura??es de dispositivos e circuitos de micro-ondas resulta em aumento de complexidade nos processos de desenvolvimento, particularmente nos casos de s?ntese. Antenas e superf?cies seletivas de frequ?ncia (Frequency Selective Surface - FSS) s?o estruturas muito importantes nos sistemas de comunica??es, que podem ser otimizadas pela atua??o dos algoritmos bioinspirados. Geralmente, para que os algoritmos bioinspirados auxiliem na otimiza??o dessas estruturas ? necess?ria a implementa??o de t?cnicas de an?lise num?rica como o M?todo dos Momentos ou Elementos Finitos. Diante da dificuldade de modelagem das t?cnicas descritas, ? comum a utiliza??o de uma fun??o de estima??o, como as Redes Neurais Artificiais, para substituir a an?lise num?rica. Embora encontre solu??es desejadas, as estima??es s?o realizadas ap?s um processo de treinamento efetuado atrav?s de uma base de dados. Cada estrutura de antena ou FSS exige uma base de dados espec?fica. Este trabalho prop?e uma t?cnica de otimiza??o baseado na utiliza??o de um algoritmo bioinspirado e um framework que realiza a integra??o do algoritmo ao software comercial ANSYS HFSS. O prop?sito ? realizar as simula??es das poss?veis solu??es durante a execu??o do algoritmo bioinspirado, e com isso, evitar o uso de uma base de dados, e assim, tornar a t?cnica eficiente e flex?vel com rela??o ?s altera??es nas estruturas de antenas ou FSS. Outro objetivo original deste trabalho ? a utiliza??o do algoritmo Social Spider Optimization ? SSO para a solu??o de problemas na ?rea de eletromagnetismo aplicado. Para comprovar a efic?cia da t?cnica proposta alguns projetos de antena e FSS s?o otimizados atrav?s de varia??es em seus par?metros estruturais. Os resultados obtidos na otimiza??o dos projetos dos circuitos s?o comparados com outras t?cnicas, tendo sido observado uma boa concord?ncia. / The new settings for devices and microwaves circuits result in an increase of complexity in the processes of development, specially in regards to the process of synthesis. Antennas and Frequency Selective Surfaces (FSS) are primordial in communication systems. Alternatively, these structures may be optimized through the usage of bio-inspired algorithms. Generally, in order for the bio-inspired algorithms to assist in the optimization of FSS structures, it is necessary to implement several numerical analysis techniques, such as the method of moments or finite elements. Because of the difficulty to model such methods, it has been turned common the usage of a point estimation function, such as artificial neural networks, to substitute the numerical analysis. Although these procedures end up encountering desirable solutions, the estimations are done after a training process conducted through a database. Additionally, every FSS antenna demands a specific database. This work proposes an optimization technique that relies on the usage of a bio-inspired algorithm and a framework (that provides the integration between the algorithm and the commercial software ANSS HFSS). The purpose of the work is to do simulations of possible solutions during the execution of the bio-inspired algorithm; therefore, avoiding the usage of the database; and so, make the technique flexible and efficient in relation to altering the antennas? structures or FSS. Furthermore, another objective of this work is the usage of the algorithm, namely Social Spider Optimization - SSO in the search for solutions in the field of applied electromagnetism. In order to prove the efficiency of the proposed techniques, some FSS? and antennas? projects are optimized through the variation of their structural parameters. In conclusion, the results that were obtained through the procedures previously shown, are compared to other techniques, resulting in a satisfying agreement rate.
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