Orientadores: José Pissolato Filho, Sérgio Kurokawa / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-22T00:02:34Z (GMT). No. of bitstreams: 1 Costa_EduardoCoelhoMarquesda_D.pdf: 1639814 bytes, checksum: 41a5776b46ed850ac50a5bc6db923da7 (MD5) Previous issue date: 2013 / Resumo: Uma metodologia alternativa e aprimorada para modelagem de linhas de transmissão multifásicas é apresentada ao longo do desenvolvimento proposto. O desacoplamento modal das fases e cabos pára-raios dá-se por meio de uma metodologia otimizada no uso das matrizes de transformação modal ao longo das sucessivas transformações entre os domínios dos modos e das fases, eliminando os erros decorrentes da modelagem e representação da linha fazendo uso de análise modal. A representação equivalente de cada modo de propagação é desenvolvida por elementos discretos convencionais com base na teoria fundamental de circuitos elétricos, o que torna a modelagem em questão simplificada, porém não menos precisa. Para modelagem do efeito da frequência nos parâmetros longitudinais da linha, é utilizado vector fitting para sintetizar os parâmetros de forma equivalente e por elementos discretos para cada modo de propagação do sistema multifásico. O sistema de equações diferenciais é representado no espaço de estados e facilmente solucionado por métodos numéricos de integração. No entanto, propõe-se a resolução do sistema de equações de estado por meio de um método de solução analítico, significativamente mais eficaz computacionalmente e mais robusto que o método de integração trapezoidal, amplamente aplicado na simulação de transitórios eletromagnéticos. Ademais, o método analítico possibilita o desenvolvimento de uma metodologia híbrida, adequada tanto na simulação de fenômenos transitórios quanto na simulação fenômenos em regime permanente. O modelo proposto é totalmente desenvolvido no domínio do tempo, sem a utilização de transformadas inversas e convoluções, tornando simples a integração de outros dispositivos e elementos não lineares ao longo da linha. Por fim, um processo utilizando FIR digital filtering integrado à modelagem por matrizes de estado, elimina todas as oscilações espúrias decorrentes da discretização da linha por elementos discretos e erros de truncamento. Em suma, o modelo computacional proposto apresenta uma metodologia aprimorada que se estender desde a modelagem dos parâmetros elétricos da linha à simulação propriamente dita dos transitórios eletromagnéticos, na ordem de poucos milissegundos, e fenômenos transitórios mais lentos, próximos do sinal fundamental em regime permanente / Abstract: An alternative and accurate methodology to model multiphase transmission lines is presented in the proposed development. The modal decoupling of the phases and shield wires is given by an optimized methodology in the use of the modal transformation matrix through the successive transformations between modal and phase domains, correcting the errors associated with the modeling and representation of the line by using analysis modal. Each propagation mode is represented by conventional lumped elements widely approached in the electrical circuit theory, which simplify the equivalent modeling, although a no less accurate procedure. To insert the frequency dependence of the longitudinal parameters in the line model, the vector fitting is applied to synthesize the parameters by an equivalent lumped circuit for each propagation mode of the multiphase system. The system of differential equations, resulting from the differential equations associated with the modal parameters, is represented in the state space and easily solved by numeric integration methods. Although, an analytical solution method is proposed to solve the system of state equations. This solution method is more efficient in computational terms and more robust than the well-known trapezoidal rule, widely used for simulation of electromagnetic transients. Furthermore, the proposed analytical method enables the development of a hybrid methodology, properly adapted to simulate transients as well as steady-state phenomena. The proposed model is completely developed in the time domain, without the use of inverse transforms and convolutions, which means that the proposed modeling is totally compatible with any other power electrical devices and nonlinear elements modeled in the time domain. Finally, a process using FIR digital filtering integrated to the modeling by state matrices eliminates all the spurious oscillations occurred from the line parameters discretization and truncation errors. In short, the proposed computational model presents an improved methodology carried out since the line electrical parameters modeling up to the simulation of electromagnetic transients of a few microseconds up to slow transient phenomena, close of the steady-state fundamental signal / Doutorado / Energia Eletrica / Doutor em Engenharia Elétrica

Orientadores: Luiz Koodi Hotta, Fernando Antônio da Silva Moura / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica / Made available in DSpace on 2018-08-20T15:43:54Z (GMT). No. of bitstreams: 1 LunaHernandez_Angela_M.pdf: 2230052 bytes, checksum: 7cee5005f5f1bd9bbdd565de481db0ad (MD5) Previous issue date: 2012 / Resumo: A dissertação apresenta o processo de estimação em pesquisas repetidas sob o enfoque de séries temporais, empregando Modelos de Espaço de Estados e o filtro dos mínimos quadrados generalizados ou filtro GLS. Este filtro permite o tratamento de modelos com erros de observação autocorrelacionados de forma mais simples do que utilizando o filtro de Kalman e, além disso, possibilita a modelagem conjunta de várias subpopulações ou domínios sob restrições de benchmark obtidas a partir da mesma pesquisa. Isto não só permite manter a coerência entre as estimativas obtidas pelo método, e estimativas agregadas baseadas no planejamento da amostra, como ajuda na proteção contra possíveis erros de especificação dos modelos. Considerando o caso de amostras com rotação, também é abordado o processo de estimação da estrutura de autocorrelação dos erros amostrais empregando o método dos pseudo-erros. Via simulação, é replicado todo o procedimento de estimação, comparando resultados obtidos empregando os filtros GLS e de Kalman. Adicionalmente, é ilustrada a aplicação do filtro sob restrições de benchmark empregando a série de taxa de desemprego da Pesquisa Mensal de Emprego do IBGE, no período de março de 2002 a fevereiro de 2012 / Abstract: This work presents the estimation process in repeated surveys using State Space Models and the generalized linear squares filter, GLS filter, under the time series approach. This filter deals with autocorrelated errors in the observation equation, in a simpler way than the well-known Kalman filter. Additionally, it allows for modeling jointly several domains under benchmark constraints obtained from the same survey. The benchmarking not only achieves coherence between the model-based estimates and the corresponding design-based aggregated estimates, but also provides protection against possible model failures. For the scenario of samples with a rotation scheme, the estimation of the autocorrelation structure of observational errors, using the pseudo-errors method, is also addressed. Simulation are used to compare the GLS and Kalman filter estimators. Moreover, the application of GLS filter under benchmark restrictions is illustrated, using the unemployment rate time serie from the Brazilian monthly labor force survey, from March 2002 to February 2012 / Mestrado / Estatistica / Mestre em Estatística

[pt] O presente trabalho tem como objetivo principal investigar por meio de simulação Monte Carlo algumas propriedades estatísticas dos modelos GARMA (Generalized Autoregressive Moving Average) para séries temporais de dados de contagem. Os modelos GARMA são uma extensão dos Modelos Lineares Generalizados de McCullagh e Nelder para situações de dados dependentes, caracterizando-se pela adição de um termo extra ao preditor linear, o qual passa a incorporar termos autoregressivos (AR) e de médias móveis (MA). As propriedades estatísticas investigadas foram às condições de estacionariedade dos modelos GARMA e os critérios de identificação da ordem (p,q) dos polinômios AR e MA que definem o modelo. Os resultados encontrados indicam que os critérios AIC BIC e Hannan-Quin utilizados foram razoavelmente eficazes na identificação da ordem dos modelos e que as condições de estacionariedade estabelecidas empiricamente em termo de restrições no espaço paramétrico são bastante complexas exigindo um estudo mais detalhado. Como objetivo secundário testamos os modelo GARMA em séries reais, ajustando os modelos GARMA- Poissson e GARMA-Binomial Negativa ao número de caso de poliomielite nos EUA e ao número de infartos do miocárdio no município do Rio de Janeiro. Os resultados indicam que os modelos foram capazes de explicar, de forma econômica, a variação destas séries. / [en] The main objective of this dissertation is to investigate, using Monte Carlo simulations, some statistical properties of GARMA (Generalized Autoregressive Moving Average ) models for time series of count data. GARMA models are extensions of the Generalized Linear Models to dependent data, in which autoregressive (AR) and/or moving average (MA) terms are incorporated into the linear predictor. The statistical properties targeted in our investigation were the model stationarity conditions and the identification criteria for selection of model orders, the lag structure (p,q) associated with the AR and MA terms. Our results suggest that AIC, BIC and Hann-Quinn criteria worked relatively well in identifying the model order, and that the conditions for stationarity established empirically in terms of parameter space restrictions were not totally conclusive, requiring further investigation. As a secondary objective we tested the model against real data, by fitting both a GARMA-Poisson and a GARMA-Negative Binomial to the series of number of cases of poliomyelitis on the US and the number of heart-attacks in Rio de Janeiro city. The results we found indicate that these models were able to explain, in a parsimonious way, the variation of both series.

Le modèle RiskMetrics développé par la Banque JP Morgan suite à l'amendement des accords de Bâle de 1988 a été érigé comme mesure de risque financier pour faire face aux importantes perturbations ayant affecté les marchés bancaires internationaux. Communément appelé Value at Risk, il a été admis par l'ensemble des organes et institutions financiers comme une mesure de risque cohérente. Malgré sa popularité, elle est le sujet de beaucoup de controverses. En effet, les paramètres d'estimation du système RiskMetrics sont supposés fixes au cours du temps ce qui est contraire aux caractéristiques des marchés financiers. Deux raisons valables permettent de justifier cette instabilité temporelle : * la présence d'agents hétérogènes fait qu'on n'analyse plus la VaR en se focalisant sur une seule dimension temporelle mais plutôt sur des fréquences de trading (nous recourons pour cela à la méthode Wavelet). * la structure des séries financières qui d'habitude est affectée par les phénomènes de crash, bulle etc. Ceux-ci peuvent être considérés comme des variables cachées qu'on doit prendre en compte dans l'évaluation du risque. Pour cela, nous recourons à la modélisation espace d'états et au filtre de Kalman. Nous savons d'emblée que les performances de la VaR s'évaluent en recourant au test de backtesting. Celui-ci repose sur la technique de régression roulante qui montre une faille évidente : Nous ne pouvons pas connaitre le processus gouvernant la variation des paramètres, il n'y a pas endogénéisation de la dynamique de ceux-ci. Pour apporter une solution à ce problème, nous proposons une application du filtre de Kalman sur les modèles VaR et WVaR. Ce filtre, par ses fonctions corrige de manière récursive les paramètres dans le temps. En ces termes nous définissons une mesure de risque dit SVaR qui en réalité est la VaR obtenue par une actualisation des paramètres d'estimation. Elle permet une estimation précise de la volatilité qui règne sur le marché financier. Elle donne ainsi la voie à toute institution financière de disposer de suffisamment de fonds propres pour affronter le risque de marché. / The RiskMetrics model developed by the bank JP Morgan following the amendment of Basel accords 1988 was erected as a measure of financial risk to deal with important disturbances affecting international banking markets. Commonly known as Value at Risk, it was accepted by all bodies and financial institutions to be a coherent risk measure. Despite its popularity, it is the subject of many controversies. Indeed, the estimation parameters of RiskMetrics are assumed to be fixed over time, which is contrary to the characteristics of financial markets. Two valid reasons are used to justify temporal instability : *Due to the presence of heterogenous agents the VaR is not analysed by focusing on a single temporal dimension but rather on trading frequencies (we use Wavelet method for it). *The structure of financial time series wich is usually affected by the crash bubble phenomenons and so on. These can be considered as hidden variables that we must take into account in the risk assessment. For this, we use state space modeling and kalman filter. We immediately know that performances of the VaR are evaluated using backtesting test. This is based on the technique of rolling regression wich shows an obvious break : We can not know the processes governing the variation of parameters; there is no endogeneisation dynamics thereof. To provide a solution to this problem, we propose an application of the kalman filter on VaR and WVaR models. This filter recursively corrects by its functions the parameters of time. In these terms we define a risk measure called SVaR wich in realitity is the VaR obtained by updating estimation parameters. It provides an accurate estimate of the volatility existing in the financial market. It thus gives way to any financial institution to have enough capital to face market risk.

In industrial fuel gas preparation, there are several compositional properties that must be controlled within specified limits. This allows client plants to use the fuel gas mixture safely without having to adjust and control the composition themselves. The variables to be controlled are the Higher Heating Value (HHV), Wobbe Index (WI), Flame Speed Index (FSI), and Pressure (P). These variables are controlled by adjusting the volumetric flow rates of several inlet gas streams of which some are makeup streams (always available) and some are wild streams that vary in composition and availability (by-products of plants). The inlet streams need to be adjusted in the correct ratios to keep all the controlled variables (CVs) within limits while minimising the cost of the gas blend. Furthermore, the controller needs to compensate for fluctuations in inlet stream compositions and total fuel gas demand (the total discharge from the header). This dissertation describes the modelling and model validation of an industrial fuel gas header as well as a simulation study of three different Model Predictive Control (MPC) strategies for controlling the system while minimising the overall operating cost. / Dissertation (MEng)--University of Pretoria, 2011. / Electrical, Electronic and Computer Engineering / unrestricted

The accurate evaluation of interlaminar stresses is of great significance in the analysis and design of laminated and piezoelectric laminated structures because complex behaviours of these stresses near free edges initiate edge delamination that raises concerns about the structural integrity and reliability. This thesis presented 3D hybrid analyses on the interlaminar stresses to investigate the electromechanical coupling and free edge effects of piezoelectric laminated plates with an emphasis on the realistic distributions of the 3D stress and electric fields near free edges. In this research, the state space equations for simply-supported and free-edge piezoelectric laminates under transverse loads and infinite long free-edge piezoelectric laminates under uniaxial extension were obtained in the framework of 3D piezoelasticity by considering all the independent elastic and piezoelectric constants. The equations satisfy the traction-free and open-circuit boundary conditions at free edges and the continuity conditions across all interfaces. On the basis of the transfer matrix and recursive solution approaches, 3D exact solutions were sought by a novel non-uniform layer refinement technique to evaluate the accuracy of the finite element method (FEM), and realistic gradients of interlaminar stresses and electric fields were captured. The FEM results were in good agreement with those from the present solutions except for the regions near free edges. For simply-supported and free-edge laminates, stress variations with material properties, geometries and stacking sequences were obtained. The interlaminar stress τxz was dominant at corners and τyz also tended to contribute to delamination. In the infinite long free-edge laminates, σz, τyz, Ey and Ez exhibited significant gradients near free edges. Furthermore, the considerable influence of the electromechanical coupling effect on interlaminar stresses revealed that piezoelectric laminates were more susceptible to edge delamination and the application of closed-circuited surface conditions might prevent such edge delamination. The present analytical solution demonstrated an improvement in precision over other 2D analytical and numerical solutions and could serve as a benchmark for the determination of interlaminar stresses and electric fields near the free edges of the piezoelectric laminates.

Inverters play key roles in connecting sustainable energy (SE) sources to the local loads and the ac grid. Although there has been a rapid expansion in the use of renewable sources in recent years, fundamental research, on the design of inverters that are specialized for use in these systems, is still needed. Recent advances in power electronics have led to proposing new topologies and switching patterns for single-stage power conversion, which are appropriate for SE sources and energy storage devices. The current source inverter (CSI) topology, along with a newly proposed switching pattern, is capable of converting the low dc voltage to the line ac in only one stage. Simple implementation and high reliability, together with the potential advantages of higher efficiency and lower cost, turns the so-called, single-stage boost inverter (SSBI), into a viable competitor to the existing SE-based power conversion technologies. The dynamic model is one of the most essential requirements for performance analysis and control design of any engineering system. Thus, in order to have satisfactory operation, it is necessary to derive a dynamic model for the SSBI system. However, because of the switching behavior and nonlinear elements involved, analysis of the SSBI is a complicated task. This research applies the state-space averaging technique to the SSBI to develop the state-space-averaged model of the SSBI under stand-alone and grid-connected modes of operation. Then, a small-signal model is derived by means of the perturbation and linearization method. An experimental hardware set-up, including a laboratory-scaled prototype SSBI, is built and the validity of the obtained models is verified through simulation and experiments. Finally, an eigenvalue sensitivity analysis is performed to investigate the stability and dynamic behavior of the SSBI system over a typical range of operation.

No description available.

This thesis deals with the optimization of state space controller of DC motor on FPGA in LabVIEW environment on NI cRIO platform. In the first part, the state space model of the given DC motor is presented in Matlab/Simulink and then the position feedback controller with steady-state error elimination and with state observer with error compen-sation using LQR method is designed. The thesis continues with transforming the con-troller to LabVIEW environment where the code is edited for FPGA use. Next, the fo-cus on FPGA hardware resources consumption optimization leads to careful work with fixed-point data type. After successful code compilation on target hardware, the real given DC motor is connected and the series of tests are performed. The output of the thesis is working state space controller running on FPGA and the graphical user inter-face on real-time host cRIO, which enables the user to control the plant and save the data on the disk.

This master thesis is focused on the sensitivity analysis of selected kinds of state reconstructors. They are realized in a general form, via direct and parallel programing. Quantity that determines the quality of sensitivity is output signal difference of the reconstructor with the general form of the system. Testing will be based on different initial state conditions and on the parameters change of the feedback A matrix due to the rested reconstructors.