Controle adaptativo com desacoplamento aplicado a um sistema de tanques acoplados MIMO

O controle de sistemas MIMO (Multiple Input Multiple Output) é muitas vezes realizado por várias malhas de controladores clássicos que operam com restrições e apresentam baixo desempenho. Técnicas de controle adaptativo são uma alternativa interessante para aumentar o rendimento desses sistemas, como por exemplo os controladores MRAC (Model Reference Adaptive Control), que quando bem projetados, permitem que a dinâmica da planta seja escolhida de maneira a seguir um modelo de referência. O presente trabalho apresenta uma estratégia de desacoplamento para um sistema MIMO de três tanques acoplados e o projeto de um controlador MRAC para o mesmo.

Controle adaptativo com desacoplamento aplicado a um sistema de tanques acoplados MIMO

O controle de sistemas MIMO (Multiple Input Multiple Output) é muitas vezes realizado por várias malhas de controladores clássicos que operam com restrições e apresentam baixo desempenho. Técnicas de controle adaptativo são uma alternativa interessante para aumentar o rendimento desses sistemas, como por exemplo os controladores MRAC (Model Reference Adaptive Control), que quando bem projetados, permitem que a dinâmica da planta seja escolhida de maneira a seguir um modelo de referência. O presente trabalho apresenta uma estratégia de desacoplamento para um sistema MIMO de três tanques acoplados e o projeto de um controlador MRAC para o mesmo.

Algorithms for super-resolution of images based on Sparse Representation and Manifolds

lmage super-resolution is defined as a class of techniques that enhance the spatial resolution of images. Super-resolution methods can be subdivided in single and multi image methods. This thesis focuses on developing algorithms based on mathematical theories for single image super­ resolution problems. lndeed, in arder to estimate an output image, we adopta mixed approach: i.e., we use both a dictionary of patches with sparsity constraints (typical of learning-based methods) and regularization terms (typical of reconstruction-based methods). Although the existing methods already per- form well, they do not take into account the geometry of the data to: regularize the solution, cluster data samples (samples are often clustered using algorithms with the Euclidean distance as a dissimilarity metric), learn dictionaries (they are often learned using PCA or K-SVD). Thus, state-of-the-art methods still suffer from shortcomings. In this work, we proposed three new methods to overcome these deficiencies. First, we developed SE-ASDS (a structure tensor based regularization term) in arder to improve the sharpness of edges. SE-ASDS achieves much better results than many state-of-the- art algorithms. Then, we proposed AGNN and GOC algorithms for determining a local subset of training samples from which a good local model can be computed for recon- structing a given input test sample, where we take into account the underlying geometry of the data. AGNN and GOC methods outperform spectral clustering, soft clustering, and geodesic distance based subset selection in most settings. Next, we proposed aSOB strategy which takes into account the geometry of the data and the dictionary size. The aSOB strategy outperforms both PCA and PGA methods. Finally, we combine all our methods in a unique algorithm, named G2SR. Our proposed G2SR algorithm shows better visual and quantitative results when compared to the results of state-of-the-art methods.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Projeto, implementação e análise de um conversor CC-CC de alto ganho e alto rendimento para aplicações fotovoltaicas

In recent years the photovoltaic generation has had greater insertion in the energy mix of the most developed countries, growing at annual rates of over 30%. The pressure for the reduction of pollutant emissions, diversification of the energy mix and the drop in prices are the main factors driving this growth. Grid tied systems plays an important role in alleviating the energy crisis and diversification of energy sources. Among the grid tied systems, building integrated photovoltaic systems suffers from partial shading of the photovoltaic modules and consequently the energy yield is reduced. In such cases, classical forms of modules connection do not produce good results and new techniques have been developed to increase the amount of energy produced by a set of modules. In the parallel connection technique of photovoltaic modules, a high voltage gain DC-DC converter is required, which is relatively complex to build with high efficiency. The current-fed isolated converters explored in this work have some desirable characteristics for this type of application, such as: low input current ripple and input voltage ripple, high voltage gain, galvanic isolation, feature high power capacity and it achieve soft switching in a wide operating range. This study presents contributions to the study of a high gain and high efficiency DC-DC converter for use in a parallel system of photovoltaic generation, being possible the use in a microinverter or with central inverter. The main contributions of this work are: analysis of the active clamping circuit operation proposing that the clamp capacitor connection must be done on the negative node of the power supply to reduce the input current ripple and thus reduce the filter requirements; use of a voltage doubler in the output rectifier to reduce the number of components and to extend the gain of the converter; detailed study of the converter components in order to raise the efficiency; obtaining the AC equivalent model and control system design. As a result, a DC-DC converter with high gain, high efficiency and without electrolytic capacitors in the power stage was developed. In the final part of this work the DC-DC converter operation connected to an inverter is presented. Besides, the DC bus controller is designed and are implemented two maximum power point tracking algorithms. Experimental results of full system operation connected to an emulator and subsequently to a real photovoltaic module are also given.

An identification procedure of multi-input Wiener models for the distortion analysis of nonlinear circuits

In this contribution, a system identification procedure of a two-input Wiener model suitable for the analysis of the disturbance behavior of integrated nonlinear circuits is presented. The identified block model is comprised of two linear dynamic and one static nonlinear block, which are determined using an parameterized approach. In order to characterize the linear blocks, an correlation analysis using a white noise input in combination with a model reduction scheme is adopted. After having characterized the linear blocks, from the output spectrum under single tone excitation at each input a linear set of equations will be set up, whose solution gives the coefficients of the nonlinear block. By this data based black box approach, the distortion behavior of a nonlinear circuit under the influence of an interfering signal at an arbitrary input port can be determined. Such an interfering signal can be, for example, an electromagnetic interference signal which conductively couples into the port of consideration. © 2011 Author(s).

Modelo teórico para cuantificar la eficiencia térmica del calentador eléctrico en una secadora doméstica de ropa

En este trabajo de difusión se presenta la mejora de la generación y transferencia de calor en el calentador eléctrico de una secadora doméstica de ropa, con el desarrollo de un modelo teórico para estimar la eficiencia térmica, basado en el flujo másico y la potencia eléctrica del calentador como variables de entrada, y la eficiencia térmica del calentador como variable de salida, con el calentador analizado como un componente aislado. Se realizaron pruebas al calentador para determinar la función matemática de su eficiencia térmica. Del análisis de resultados se observó la tendencia exponencial típica de un sistema sobreamortiguado, base del modelo matemático cuyo coeficiente de predicción es 0.96.El modelo matemático se comprobó con flujo másico alto obteniendo un error relativo máximo de 0.66 %, y provee de información suficiente para elevar la eficiencia en 7.7%. El rango de potencia en el que fue probado el modelo matemático desarrollado para el calentador es de 1 KW hasta 5 KW, el cual es el rango recomendado para su uso.

Previsão do índice bovespa por meio de redes neurais artificiais: uma análise comparada aos métodos tradicionais de séries de tempo

Forecast is the basis for making strategic, tactical and operational business decisions. In financial economics, several techniques have been used to predict the behavior of assets over the past decades.Thus, there are several methods to assist in the task of time series forecasting, however, conventional modeling techniques such as statistical models and those based on theoretical mathematical models have produced unsatisfactory predictions, increasing the number of studies in more advanced methods of prediction. Among these, the Artificial Neural Networks (ANN) are a relatively new and promising method for predicting business that shows a technique that has caused much interest in the financial environment and has been used successfully in a wide variety of financial modeling systems applications, in many cases proving its superiority over the statistical models ARIMA-GARCH. In this context, this study aimed to examine whether the ANNs are a more appropriate method for predicting the behavior of Indices in Capital Markets than the traditional methods of time series analysis. For this purpose we developed an quantitative study, from financial economic indices, and developed two models of RNA-type feedfoward supervised learning, whose structures consisted of 20 data in the input layer, 90 neurons in one hidden layer and one given as the output layer (Ibovespa). These models used backpropagation, an input activation function based on the tangent sigmoid and a linear output function. Since the aim of analyzing the adherence of the Method of Artificial Neural Networks to carry out predictions of the Ibovespa, we chose to perform this analysis by comparing results between this and Time Series Predictive Model GARCH, developing a GARCH model (1.1).Once applied both methods (ANN and GARCH) we conducted the results' analysis by comparing the results of the forecast with the historical data and by studying the forecast errors by the MSE, RMSE, MAE, Standard Deviation, the Theil's U and forecasting encompassing tests. It was found that the models developed by means of ANNs had lower MSE, RMSE and MAE than the GARCH (1,1) model and Theil U test indicated that the three models have smaller errors than those of a naïve forecast. Although the ANN based on returns have lower precision indicator values than those of ANN based on prices, the forecast encompassing test rejected the hypothesis that this model is better than that, indicating that the ANN models have a similar level of accuracy . It was concluded that for the data series studied the ANN models show a more appropriate Ibovespa forecasting than the traditional models of time series, represented by the GARCH model

Controle preditivo neural aplicado à processos petroquímicos

A pesquisa tem como objetivo desenvolver uma estrutura de controle preditivo neural, com o intuito de controlar um processo de pH, caracterizado por ser um sistema SISO (Single Input - Single Output). O controle de pH é um processo de grande importância na indústria petroquímica, onde se deseja manter constante o nível de acidez de um produto ou neutralizar o afluente de uma planta de tratamento de fluidos. O processo de controle de pH exige robustez do sistema de controle, pois este processo pode ter ganho estático e dinâmica nãolineares. O controlador preditivo neural envolve duas outras teorias para o seu desenvolvimento, a primeira referente ao controle preditivo e a outra a redes neurais artificiais (RNA s). Este controlador pode ser dividido em dois blocos, um responsável pela identificação e outro pelo o cálculo do sinal de controle. Para realizar a identificação neural é utilizada uma RNA com arquitetura feedforward multicamadas com aprendizagem baseada na metodologia da Propagação Retroativa do Erro (Error Back Propagation). A partir de dados de entrada e saída da planta é iniciado o treinamento offline da rede. Dessa forma, os pesos sinápticos são ajustados e a rede está apta para representar o sistema com a máxima precisão possível. O modelo neural gerado é usado para predizer as saídas futuras do sistema, com isso o otimizador calcula uma série de ações de controle, através da minimização de uma função objetivo quadrática, fazendo com que a saída do processo siga um sinal de referência desejado. Foram desenvolvidos dois aplicativos, ambos na plataforma Builder C++, o primeiro realiza a identificação, via redes neurais e o segundo é responsável pelo controle do processo. As ferramentas aqui implementadas e aplicadas são genéricas, ambas permitem a aplicação da estrutura de controle a qualquer novo processo

Estudo comparativo do desempenho de controladores robustos aplicados a um sistema de tanques acoplados.

Currently the uncertain system has attracted much academic community from the standpoint of scientific research and also practical applications. A series of mathematical approaches emerge in order to troubleshoot the uncertainties of real physical systems. In this context, the work presented here focuses on the application of control theory in a nonlinear dynamical system with parametric variations in order and robustness. We used as the practical application of this work, a system of tanks Quanser associates, in a configuration, whose mathematical model is represented by a second order system with input and output (SISO). The control system is performed by PID controllers, designed by various techniques, aiming to achieve robust performance and stability when subjected to parameter variations. Other controllers are designed with the intention of comparing the performance and robust stability of such systems. The results are obtained and compared from simulations in Matlab-simulink.

Percurso profissional. Destaque para a análise da produção de resíduos urbanos no Alentejo Central - portugal e utilização do modelo DEA na definição da meta da recolha seletiva

Neste trabalho de Projeto efetua-se o desenvolvimento do tema da produção de Resíduos Urbanos (RU) no Alentejo Central, utilizando-se o modelo DEA (Data Envelopment Analysis) para a análise das metas da recolha seletiva estabelecidas para 2020. Genericamente, quanto maior é o grau de desenvolvimento económico de um território, maior é a taxa de urbanização e maior é também a quantidade de resíduos urbanos produzidos por habitante. O rendimento e a urbanização são variáveis altamente correlacionadas, quando aumenta o rendimento disponível e os padrões de vida, aumenta também o consumo de bens e serviços de modo correspondente, o que leva ao aumento da quantidade de resíduos gerados. Assim, tendo em conta os impactos locais que os RU abandonados trazem, e com o objetivo de quebrar o elo entre crescimento económico e os impactos ambientais associados à produção de resíduos, são implementadas, nos países com elevados níveis de desenvolvimento, políticas baseadas em modelos integrados de gestão de RU que permitem a recuperação, reciclagem e valorização dos materiais, reservando-se a eliminação (deposição em aterro) para frações não valorizáveis, o que gera empregos e riqueza. Em Portugal vigora o Plano Estratégico para os Resíduos Urbanos (PERSU 2020) que define objetivos e metas nacionais, nomeadamente a meta da recolha seletiva, estabelecendo para 2020 um quantitativo nacional mínimo a recuperar de 47 kg por habitante por ano. Deste modo, importa caracterizar, para o período de 2002 a 2012, como evoluiu a produção de RU em comparação com a evolução do PIB em Portugal. A análise foca-se então na produção de RU na região do Alentejo em particular no Alentejo Central que evidencia um elevado nível per capita em comparação com o resto do país, situando-se mesmo acima das regiões do grande Porto e Lisboa. São apresentadas possíveis razões para o registo destes elevados níveis de produção de RU não se conseguindo, no entanto, avançar com evidências. Como o modelo DEA é utilizado no PERSU 2020 para fundamentar a projeção das metas da recolha seletiva por sistema de gestão de resíduos urbanos, fez-se a sua reprodução, o que permitiu uma análise mais detalhada dos dados e o ensaio de novos resultados considerando, para além do nível de produção de RU, o numero de equipamentos de deposição de recolha seletiva como input do modelo; Abstract: Title of the report: Professional career. Emphasis on the analysis of urban waste production in Alentejo Central - Portugal and the use of the DEA in defining the separate collection target This professional report presents the theme of the Urban Waste (UW) production in Central Alentejo, using the DEA (Data Envelopment Analysis) to analyse the target set for selective collection in 2020. Generally, the higher the degree of economic development of a region, the greater the rate of urbanization and the greater also the amount of municipal waste produced per capita. The variables income and urbanization are highly correlated, if you have an increase in the disposable income and living standards, the consumption of goods and services will increase accordingly, which leads to the increase of the amount of produced waste. Thus, taking into account the local impact that the abandoned UW brings, and in order to break the link between economic growth and the environmental impacts associated with the production of waste, countries with high levels of development implement policies based on integrated UW management models that allow the recovery, recycling and valorisation of materials, restricting the disposal (landfill) to non-recoverable fractions, which creates jobs and wealth. Portugal established a national strategic plan for Urban Waste (PERSU 2020) which defines the goals and national targets, including the selective collection target stating for 2020 a minimum recover of 47 kg per capita per year. Then it is relevant to characterize and compare the evolution of UW production and GDP in Portugal for the period 2002 to 2012. The analysis then focuses on the production of UW in Alentejo, particularly in Central Alentejo region, which shows a high per capita level compared to the rest of the country, placed just above the Greater Porto and Lisbon region. Then we explore several possible reasons for this high level of UW production in this region, but none is successful in producing strong evidence. As the DEA is used in PERSU 2020 to support the projection of the selective collection targets for the municipal waste management systems, in this report we develop the model, which allowed access to the data and a more detailed analyse. Then we introduce and test a new input, the number of separate collection deposition equipment, which gives new results that are compared with the original ones.

MODELAJE DE LA EROSIÓN DE SUELOS EN COSTA RICA MEDIANTE EL MODELO WEPP

El objetivo de esta investigación consiste básicamente en probar la aplicabilidad para las condiciones físico-geográficas características de Costa Rica, del modelo para la predicción de suelos Watcr Erosion Prediction Project (WEPP), el cual es desarrollado por el Servicio de Conservación de Suelos de los Estados Unidos.Los pronósticos efectuados por el WEPP, son comparados con mediciones reales de erosión y escorrentía efectuadas por medio de parcelas tipo USLE (café, pastos y tabaco-maíz-frijol) ubicadas en la localidad de Cerbatana de Puriscal (1990-1995), junto con mediciones de las condiciones climáticas y análisis de las características de los suelos.Los resultados indican que ci modelo tiene un aceptable pronóstico en los datos de la erosión y de la escorrentía, sobre todo si se le compara con pronósticos hechos con la Ecuación Universal de Pérdida de Suelos. Los parámetros de entrada (input) que requiere el WEPP son muy abundantes en cantidad y muy sensibles en su efecto sobre los pronósticos, por lo tanto el uso y la interpretación de los resultados deben efectuarse con un enfoque muy crítico.Abstract: the objective of this invcstigation basically consists of testing the suitabiiity of the model Water Erosion Prediction Project (WEPP) to predict soil erosion given the physical geographical charactcristics of Costa Rica. The model was developed by the Soil Conservation Service of the United States.Thc effectted predictions of the WEPP are compared with real soil erosion and surface runoff measurements taken at a typical USLE site (coffee, pasture and tobacco-corn-bean), located in the surroundings of Cerbatana of Puriscal (1990-1995). This data was taken in conjuntion with measurements of ciimactic conditions and analysis of soil characteristics.The results indicate that the model has an acceptable ability to predict soil erosion and surface runoff data, particularly if one compares thern with predictions made with the Universal Soil Loss Equation. Thc input variables that are rcquired by WEPP are quite abundant in quantity and are very sensitive in their effect of the predictions made. For that reason, the uses and interpretation of the results should be put into use with a very critical eye.

Modelo dinâmico de simulação e otimização da força normal de reação do solo para um mecanismo de corte basal

The physical model was based on the method of Newton-Euler. The model was developed by using the scientific computer program Mathematica®. Several simulations where tried varying the progress speeds (0.69; 1.12; 1.48; 1.82 and 2.12 m s-1); soil profiles (sinoidal, ascending and descending ramp) and height of the profile (0.025 and 0.05 m) to obtain the normal force of soil reaction. After the initial simulations, the mechanism was optimized using the scientific computer program Matlab® having as criterion (function-objective) the minimization of the normal force of reaction of the profile (FN). The project variables were the lengths of the bars (L1y, L2, l3 and L4), height of the operation (L7), the initial length of the spring (Lmo) and the elastic constant of the spring (k t). The lack of robustness of the mechanism in relation to the variable height of the operation was outlined by using a spring with low rigidity and large length. The results demonstrated that the mechanism optimized showed better flotation performance in relation to the initial mechanism.

Modelo de programação quadrática para análise da movimentação logística e comercialização da soja brasileira

The purpose of this work was to analyze the logistical distribution of Brazilian soybean by applying a quadratic programming to a spatial equilibrium model. The soybean transportation system is an important part of the soybean complex in Brazil, since the major part of the costs of this commodity derives from the transportation costs. Therefore, the optimization of this part of the process is essential to a better competitiveness of the Brazilian soybean in the international market. The Brazilian soybean complex have been increasing its agricultural share in the total of the exportation value in the last ten years, but due to other countries' investments the Brazilian exportations cannot be only focused on increasing its production but it still have to be more efficient. This way, a model was reached which can project new frames by switching the transportation costs and conduce the policy makers to new investments in the sector.

Estrutura de um curso de taxonomia de campo: o modelo aplicado em Ubatuba, São Paulo

The field activities are essential for the education of a good taxonomist. The most common problems found in field activities are: a) large number of students, b) heterogeneous educational background and unlevelled knowledge of the participants, c) repetitions and tendency of collecting the more evidents life-forms. The causes and consequences of such problems are discussed herein. The proposed solution is a methodology, based on many years of experience in field courses for undergraduate and graduate courses. Topics about the ideal number of participants, area of coverage, period of activity, division of work and the necessary material and equipment are discussed. According to the number of species collected at the same place, this methodology may result in a list of local species with precise information about the life-forms, habitat, common names, frequency, uses, phenology and further information in this kind of work. The results of the aplication of this metodology in a field course held in the region of Ubatuba-SP are presented.