1000 resultados para parametric identification


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Growth of complexity and functional importance of integrated navigation systems (INS) leads to high losses at the equipment refusals. The paper is devoted to the INS diagnosis system development, allowing identifying the cause of malfunction. The proposed solutions permit taking into account any changes in sensors dynamic and accuracy characteristics by means of the appropriate error models coefficients. Under actual conditions of INS operation, the determination of current values of the sensor models and estimation filter parameters rely on identification procedures. The results of full-scale experiments are given, which corroborate the expediency of INS error models parametric identification in bench test process.

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This work deals with the initial applications and formulation of an aniscitropic plastic-damage constitutive model proposed for non-linear analysis of reinforced concrete structures submitted to a loading with change of the sign. The original constitutive model is based on the fundamental hypothesis of energy equivalence between real and continuous medium following the concepts of the Continuum Damage Mechanics. The concrete is assumed as an initial elastic isotropic medium presenting anisotropy, permanent strains and bimodularity (distinct elastic responses whether traction or compression stress states prevail) induced by damage evolution. In order to take into account the bimodularity, two damage tensors governing the rigidity in tension or compression regimes are introduced. Then, some conditions are introduced in the original version of the model in order to simulate the damage unilateral effect. The three-dimensional version of the proposed model is analyzed in order to validate its formulation when compared to micromechanical theory. The one-dimensional version of the model is applied in the analyses of a reinforced concrete beam submitted to a loading with change of the sign. Despite the parametric identification problems, the initial applications show the good performance of the model.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Este artigo apresenta um estudo experimental de técnicas de identificação paramétrica aplicadas à modelagem dinâmica de um servidor web Apache. Foi desenvolvido um arranjo experimental para simular variações de carga no servidor. O arranjo é composto por dois computadores PC, sendo um deles utilizado para executar o servidor Apache e o outro utilizado como um gerador de carga, solicitando requisições de serviço ao servidor Apache. Foram estimados modelos paramétricos auto-regressivos (AR) para diferentes pontos de operação e de condição de carga. Cada ponto de operação foi definido em termos dos valores médios para o parâmetro de entrada MaxClients (parâmetro utilizado para definir o número máximo de processos ativos) e a saída percentual de consumo de CPU (Central Processing Unit) do servidor Apache. Para cada ponto de operação foram coletadas 600 amostras, com um intervalo de amostragem de 5 segundos. Metade do conjunto de amostras coletadas em cada ponto de operação foi utilizada para estimação do modelo, enquanto que a outra metade foi utilizada para validação. Um estudo da ordem mais adequada do modelo mostrou que, para um ponto de operação com valor reduzido de MaxClients, um modelo AR de 7a ordem pode ser satisfatório. Para valores mais elevados de MaxClients, os resultados mostraram que são necessários modelos de ordem mais elevada, devido às não-linearidades inerentes ao sistema.

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Neste trabalho são apresentados o desenvolvimento e a implementação de estratégias de controle digital para regulação automática de tensão e para o amortecimento de oscilações eletromecânicas em um sistema de potência em escala reduzida de 10kVA, localizado no Laboratório de Controle de Sistemas de Potência (LACSPOT), da Universidade Federal do Pará (UFPA). O projeto dos dois controladores é baseado na técnica de alocação polinomial de polos. Para o projeto do Regulador Automático de Tensão (RAT) foi adotado um modelo simplificado, de primeira ordem, da máquina síncrona, cujos parâmetros foram levantados experimentalmente. Para o controlador amortecedor, por sua vez, também chamado de Estabilizador de Sistemas de Potência (ESP), foi utilizado um modelo discreto, do tipo auto regressivo com entrada exógena (ARX). Este modelo foi estimado por meio de técnicas de identificação paramétrica, considerando para tal, o conjunto motor-gerador interligado a um sistema de maior porte (concessionária de energia elétrica). As leis de controle foram embarcadas em um microcontrolador de alto desempenho e, para a medição dos sinais utilizados nos controladores, foi desenvolvida uma instrumentação eletrônica baseada em amplificadores operacionais para o condicionamento dos sinais dos sensores. O sinal de controle é baseado na técnica de modulação por largura de pulso (PWM) e comanda o valor médio da tensão de um conversor CC-CC, o qual é utilizado como circuito de excitação que energiza o enrolamento de campo do gerador. Além disso, o acionamento elétrico das máquinas que compõem o grupo gerador de 10kVA foi projetado e automatizado somando segurança aos operadores e ao componentes deste sistema de geração. Os resultados experimentais demonstraram o bom desempenho obtido pela estratégia proposta.

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Neste trabalho, são apresentados a metodologia de projeto e resultados de testes experimentais de um estabilizador de sistema de potência (ESP), implementado em um sistema de geração em escala reduzida de 10 kVA, localizado no Laboratório de Controle e Sistema de Potência (LACSPOT) da Universidade Federal do Pará (UFPA). O projeto do ESP é baseado em uma estratégia de controle robusto com ênfase em incertezas paramétricas estruturadas, as quais são tratadas com ferramentas da teoria de análise intervalar. Estas incertezas são decorrentes de mudanças do ponto de operação do sistema, que provocam variações nos parâmetros de um modelo matemático linearizado referente ao comportamento dinâmico do sistema elétrico de potência no referido ponto de operação. Para o projeto do ESP robusto intervalar, são realizados uma serie de ensaios experimentais com o propósito de estimar os parâmetros de modelos linearizados da planta, representando satisfatoriamente a dinâmica dos modos poucos amortecidos do sistema de geração interligado. O método de identificação é baseado em técnica de identificação paramétrica, baseado em mínimos quadrados. A partir de um conjunto de dados de entrada e saída, para cada ponto de operação, um modelo linear, do tipo auto-regressivo com entrada exógenos (ARX), estimado para fim de uso do projeto do ESP. Por fim, uma série de testes experimentais é realizada no sistema de geração interligado a rede elétrica local, com o propósito de verificar a efetividade da técnica de controle robusto intervalar proposta para a sintonia do ESP. A partir da análise da função custo do sinal de erro de desvio de potência elétrica na saída do gerador síncrono e a função custo do sinal de controle do ESP comprova-se experimentalmente o bom desempenho obtido pela técnica de controle proposta em comparação com uma técnica de controle clássica.

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Pulse wave velocity (PWV) is a surrogate of arterial stiffness and represents a non-invasive marker of cardiovascular risk. The non-invasive measurement of PWV requires tracking the arrival time of pressure pulses recorded in vivo, commonly referred to as pulse arrival time (PAT). In the state of the art, PAT is estimated by identifying a characteristic point of the pressure pulse waveform. This paper demonstrates that for ambulatory scenarios, where signal-to-noise ratios are below 10 dB, the performance in terms of repeatability of PAT measurements through characteristic points identification degrades drastically. Hence, we introduce a novel family of PAT estimators based on the parametric modeling of the anacrotic phase of a pressure pulse. In particular, we propose a parametric PAT estimator (TANH) that depicts high correlation with the Complior(R) characteristic point D1 (CC = 0.99), increases noise robustness and reduces by a five-fold factor the number of heartbeats required to obtain reliable PAT measurements.

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Hypertension and congenital aortic valve malformations are frequent causes of ascending aortic aneurysms. The molecular mechanisms of aneurysm formation under these circumstances are not well understood. Reference genes for gene activity studies in aortic tissue that are not influenced by aortic valve morphology and its hemodynamic consequences, aortic dilatation, hypertension, or antihypertensive medication are not available so far. This study determines genes in ascending aortic tissue that are independent of these parameters. Tissue specimens from dilated and undilated ascending aortas were obtained from 60 patients (age â¤70 years) with different morphologies of the aortic valve (tricuspid undilated nâŠ=âŠ24, dilated nâŠ=âŠ11; bicuspid undilated nâŠ=âŠ6, dilated nâŠ=âŠ15; unicuspid dilated nâŠ=âŠ4). Of the studied individuals, 36 had hypertension, and 31 received ACE inhibitors or AT1 receptor antagonists. The specimens were obtained intraoperatively from the wall of the ascending aorta. We analyzed the expression levels of 32 candidate reference genes by quantitative RT-PCR (RT-qPCR). Differential expression levels were assessed by parametric statistics. The expression analysis of these 32 genes by RT-qPCR showed that EIF2B1, ELF1, and PPIA remained constant in their expression levels in the different specimen groups, thus being insensitive to aortic valve morphology, aortic dilatation, hypertension, and medication with ACE inhibitors or AT1 receptor antagonists. Unlike many other commonly used reference genes, the genes EIF2B1, ELF1, and PPIA are neither confounded by aortic comorbidities nor by antihypertensive medication and therefore are most suitable for gene expression analysis of ascending aortic tissue.

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One of the targets of the climate and energy package of the European Union is to increase the energy efficiency in order to achieve a 20 percent reduction in primary energy use compared with the projected level by 2020. The energy efficiency can be improved for example by increasing the rotational speed of large electrical drives, because this enables the elimination of gearboxes leading to a compact design with lower losses. The rotational speeds of traditional bearings, such as roller bearings, are limited by mechanical friction. Active magnetic bearings (AMBs), on the other hand, allow very high rotational speeds. Consequently, their use in large medium- and high-speed machines has rapidly increased. An active magnetic bearing rotor system is an inherently unstable, nonlinear multiple-input, multiple-output system. Model-based controller design of AMBs requires an accurate system model. Finite element modeling (FEM) together with the experimental modal analysis provides a very accurate model for the rotor, and a linearized model of the magneticactuators has proven to work well in normal conditions. However, the overall system may suffer from unmodeled dynamics, such as dynamics of foundation or shrink fits. This dynamics can be modeled by system identification. System identification can also be used for on-line diagnostics. In this study, broadband excitation signals are adopted to the identification of an active magnetic bearing rotor system. The broadband excitation enables faster frequency response function measurements when compared with the widely used stepped sine and swept sine excitations. Different broadband excitations are reviewed, and the random phase multisine excitation is chosen for further study. The measurement times using the multisine excitation and the stepped sine excitation are compared. An excitation signal design with an analysis of the harmonics produced by the nonlinear system is presented. The suitability of different frequency response function estimators for an AMB rotor system are also compared. Additionally, analytical modeling of an AMB rotor system, obtaining a parametric model from the nonparametric frequency response functions, and model updating are discussed in brief, as they are key elements in the modeling for a control design. Theoretical methods are tested with a laboratory test rig. The results conclude that an appropriately designed random phase multisine excitation is suitable for the identification of AMB rotor systems.

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Dans cette thèse, je me suis interessé à lâidentification partielle des effets de traitements dans différents modèles de choix discrets avec traitements endogènes. Les modèles dâeffets de traitement ont pour but de mesurer lâimpact de certaines interventions sur certaines variables dâintérêt. Le type de traitement et la variable dâintérêt peuvent être défini de manière générale afin de pouvoir être appliqué à plusieurs différents contextes. Il y a plusieurs exemples de traitement en économie du travail, de la santé, de lâéducation, ou en organisation industrielle telle que les programmes de formation à lâemploi, les techniques médicales, lâinvestissement en recherche et développement, ou lâappartenance à un syndicat. La décision dâêtre traité ou pas nâest généralement pas aléatoire mais est basée sur des choix et des préférences individuelles. Dans un tel contexte, mesurer lâeffet du traitement devient problématique car il faut tenir compte du biais de sélection. Plusieurs versions paramétriques de ces modèles ont été largement étudiées dans la littérature, cependant dans les modèles à variation discrète, la paramétrisation est une source importante dâidentification. Dans un tel contexte, il est donc difficile de savoir si les résultats empiriques obtenus sont guidés par les données ou par la paramétrisation imposée au modèle. Etant donné, que les formes paramétriques proposées pour ces types de modèles nâont généralement pas de fondement économique, je propose dans cette thèse de regarder la version nonparamétrique de ces modèles. Ceci permettra donc de proposer des politiques économiques plus robustes. La principale difficulté dans lâidentification nonparamétrique de fonctions structurelles, est le fait que la structure suggérée ne permet pas dâidentifier un unique processus générateur des données et ceci peut être du soit à la présence dâéquilibres multiples ou soit à des contraintes sur les observables. Dans de telles situations, les méthodes dâidentifications traditionnelles deviennent inapplicable dâoù le récent développement de la littérature sur lâidentification dans les modèles incomplets. Cette littérature porte une attention particuliere à lâidentification de lâensemble des fonctions structurelles dâintérêt qui sont compatibles avec la vraie distribution des données, cet ensemble est appelé : lâensemble identifié. Par conséquent, dans le premier chapitre de la thèse, je caractérise lâensemble identifié pour les effets de traitements dans le modèle triangulaire binaire. Dans le second chapitre, je considère le modèle de Roy discret. Je caractérise lâensemble identifié pour les effets de traitements dans un modèle de choix de secteur lorsque la variable dâintérêt est discrète. Les hypothèses de sélection du secteur comprennent le choix de sélection simple, étendu et généralisé de Roy. Dans le dernier chapitre, je considère un modèle à variable dépendante binaire avec plusieurs dimensions dâhétérogéneité, tels que les jeux dâentrées ou de participation. je caractérise lâensemble identifié pour les fonctions de profits des firmes dans un jeux avec deux firmes et à information complète. Dans tout les chapitres, lâensemble identifié des fonctions dâintérêt sont écrites sous formes de bornes et assez simple pour être estimées à partir des méthodes dâinférence existantes.

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Laser engineering is an area in which developments in the existing design concepts and technology appear at an alarming rate. Nowâa-days, emphasis has shifted from innovation to cost reduction and system improvement. To a major extent, these studies are aimed at attaining larger power densities, higher system efficiency and identification of new lasing media and new lasing wavelengths. Todate researchers have put to use all the ditferent Forms of matter as lasing material. Laser action was observed For the first time in a gaseous system - the He-Ne system. This was Followed by a variety of solidstate and gas laser systems. Uarious organic dyes dissolved in suitable solvents were found to lase when pumped optically. Broad band emission characteristics of these dye molecules made wavelength tuning possible using optical devices. Laser action was also observed in certain p-n junctions of semiconductor materials and some of these systems are also tunable. The recent addition to this list was the observation of laser action from certain laser produced plasmas. The purpose of this investigation was to examine the design and Fabrication techniques of pulsed Nitrogen lasers and high power Nd: Glass laserso Attempt was also made to put the systems developed into certain related experiments

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We analyze the effect of a parametric reform of the fully-funded pension regime in Colombia on the intensive margin of the labor supply. We take advantage of a threshold defined by law in order to identify the causal effect using a regression discontinuity design. We find that a pension system that increases retirement age and the minimum weeks during which workers must contribute to claim pension benefits causes an increase of around 2 hours on the number of weekly worked hours; this corresponds to 4% of the average number of weekly worked hours or around 14% of a standard deviation of weekly worked hours. The effect is robust to different specifications, polynomial orders and sample sizes.

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The modelling of a nonlinear stochastic dynamical processes from data involves solving the problems of data gathering, preprocessing, model architecture selection, learning or adaptation, parametric evaluation and model validation. For a given model architecture such as associative memory networks, a common problem in non-linear modelling is the problem of "the curse of dimensionality". A series of complementary data based constructive identification schemes, mainly based on but not limited to an operating point dependent fuzzy models, are introduced in this paper with the aim to overcome the curse of dimensionality. These include (i) a mixture of experts algorithm based on a forward constrained regression algorithm; (ii) an inherent parsimonious delaunay input space partition based piecewise local lineal modelling concept; (iii) a neurofuzzy model constructive approach based on forward orthogonal least squares and optimal experimental design and finally (iv) the neurofuzzy model construction algorithm based on basis functions that are Bézier Bernstein polynomial functions and the additive decomposition. Illustrative examples demonstrate their applicability, showing that the final major hurdle in data based modelling has almost been removed.

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Parametric term structure models have been successfully applied to innumerous problems in fixed income markets, including pricing, hedging, managing risk, as well as studying monetary policy implications. On their turn, dynamic term structure models, equipped with stronger economic structure, have been mainly adopted to price derivatives and explain empirical stylized facts. In this paper, we combine flavors of those two classes of models to test if no-arbitrage affects forecasting. We construct cross section (allowing arbitrages) and arbitrage-free versions of a parametric polynomial model to analyze how well they predict out-of-sample interest rates. Based on U.S. Treasury yield data, we find that no-arbitrage restrictions significantly improve forecasts. Arbitrage-free versions achieve overall smaller biases and Root Mean Square Errors for most maturities and forecasting horizons. Furthermore, a decomposition of forecasts into forward-rates and holding return premia indicates that the superior performance of no-arbitrage versions is due to a better identification of bond risk premium.