Orientador: Carlos Alberto Canesin / Banca: Falcondes Jose Mendes de Seixas / Banca: Denizar Cruz Martins / Resumo: Este trabalho propõe uma nova abordagem na metodologia de operação para o inversor Boost monofásico, como estrutura base para o aproveitamento de fontes alternativas e renováveis de energia elétrica. Considerando-se que equipamentos eletro/eletrônicos convencionais em CA (corrente alternada) necessitam, normalmente, de níveis e formato de tensão diferentes daqueles fornecidos por essas fontes de energia, o inversor proposto é uma estrutura integrada que tem a capacidade de operar como conversor elevador de tensão e inversor, apresentando um número reduzido de componentes e rendimento maior, quando comparado às formas tradicionais de se associar em cascata o conversor elevador com o inversor. O projeto convencional do inversor fonte de corrente (CSI) exige uma indutância elevada de entrada, além disso, o modelo a pequeno sinais do CSI é semelhante ao do conversor Boost no modo de condução contínua, apresentando um zero no semi-plano direito na função de transferência para o controle da tensão de saída, sendo que este zero causa o conhecido efeito de fase não-mínima. Desta forma, uma metodologia especial de projeto é apresentada resultando numa indutância Boost reduzida e numa técnica de controle utilizando um sistema multi-malhas, com alimentação direta, devidamente projetada de forma a possibilitar elevadas dinâmicas de transferência de energia. Adicionalmente, o inversor apresenta tensão de saída com reduzidas distorções harmônicas (DHT), número reduzido de componentes de potência e, consequentemente, elevada densidade de potência. Neste trabalho são apresentadas as análises qualitativa e quantitativa do inversor, a modelagem e técnica de controle proposta, metodologia de projeto, os principais resultados de simulação e experimentais com a finalidade de demonstrar a viabilidade de aplicação da proposta. / Abstract: This work presents a new methodology for the operation and control of a single-phase current-source Boost Inverter, it is used as base structure for alternative and renewable electric energy sources. The electro/electronics devices normally require eletrical source in AC (alternate current) in different voltage levels and shapes those provided by the alternative and renewable electrical sources. The proposed inverter is an integrated structure able to operate as step-up DC-DC converter and inverter, it presents a reduced number of components, high efficiency when compared with the traditional technique of step-up and inverter for cascade association. The conventional design of current source inverter (CSI) require a large boost inductance, therefore, the small-signal model is similar to continuous-current-mode (CCM) Boost converter, which has a right-half-plane (RHP) zero in its control-to-output transfer function, and this RHP zero causes the well-known non-minimum-phase effects. In this context, a special design with small boost inductance and a multi-loop control is proposed in order to assure stability and very fast dynamics. Furthermore, the inverter presents output voltage with very low total harmonic distortion (THD), reduced number of components and high power density. In addition, this work presents the Boost CSI operation, the proposed control technique, the main simulation and experimental results in order to demonstrate the feasibility of the proposal. / Mestre

Orientador: Francisco Villarreal Alvarado / Resumo: Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. ... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

Ces travaux de thèse portent essentiellement sur la modélisation, l’analyse et la commande des convertisseurs de type MMC intégrés dans un contexte MTDC. Le premier objectif de ce travail est d’aboutir à un modèle dynamique du convertisseur MMC, exprimé dans le repère $dq$, permettant d’une part, de reproduire avec précision les interactions AC-DC, et d’exprimer, d’autre part, la dynamique interne du convertisseur qui peut interagir également avec le reste du système. Le modèle développé peut être linéarisé facilement dans le but de l’exploiter pour l’étude de stabilité en se basant sur les techniques pour les systèmes linéaires à temps invariant. Ensuite, selon le modèle développé dans le repère dq, différentes stratégies de contrôle sont proposées en fonction de systèmes de contrôle-commande existantes dans la littérature mis en places pour le convertisseur MMC. Étant donné que l’ordre du système est un paramètre important pour l'étude des réseaux MTDC en présence de plusieurs stations de conversion de type MMC, l’approche de réduction de modèles à émerger comme une solution pour faciliter l’étude. En conséquence, différents modèles à ordre réduit sont développés, et qui sont validés par la suite, par rapport au modèle détaillé, exprimé dans le repère dq. Finalement, les modèles MMC développés ainsi que les systèmes de commande qui y ont associés sont exploités, pour l’analyse de stabilité en petits signaux des réseaux MMC-MTDC. Dans ce sens, la stratégie de commande associée à chaque MMC est largement évaluée dans le but d’investiguer les problèmes majeurs qui peuvent surgir au sein d’une configuration MTDC multi-constructeurs / This thesis deals with the modeling and control of MMCs in the context of MTDC. The first objective is to obtain an MMC model in dq frame which can reproduce accurately the AC- and DC- interactions, while representing at the same time the internal dynamics which may interact with the rest of the system. This model is suitable to be linearized and to study its stability, among other linear techniques. Then, based on the developed dq model, different control strategies are developed based on the state-of-the-art on MMC controllers. Since the order of the system may be a limiting factor for studying MTDC grids with many MMCs, different reduced-order models are presented and compared with the detailed dq model. Finally, the developed MMC models with different controllers are used for the MTDC studies. The impact of the chosen controllers of each MMC is evaluated, highlighting the potential issues that may occur in multivendor schemes.

Submitted by Juliane Andrade (juliane.a.andrade@gmail.com) on 2018-09-25T12:53:53Z No. of bitstreams: 1 DissertacaoFinalJulianeAndrade.pdf: 2648304 bytes, checksum: 0feea2eb88019ffdafb37180bd261f3b (MD5) / Approved for entry into archive by Joana Martorini (joana.martorini@fgv.br) on 2018-09-25T15:17:07Z (GMT) No. of bitstreams: 1 DissertacaoFinalJulianeAndrade.pdf: 2648304 bytes, checksum: 0feea2eb88019ffdafb37180bd261f3b (MD5) / Approved for entry into archive by Suzane Guimarães (suzane.guimaraes@fgv.br) on 2018-09-25T16:40:46Z (GMT) No. of bitstreams: 1 DissertacaoFinalJulianeAndrade.pdf: 2648304 bytes, checksum: 0feea2eb88019ffdafb37180bd261f3b (MD5) / Made available in DSpace on 2018-09-25T16:40:46Z (GMT). No. of bitstreams: 1 DissertacaoFinalJulianeAndrade.pdf: 2648304 bytes, checksum: 0feea2eb88019ffdafb37180bd261f3b (MD5) Previous issue date: 2018-08-16 / Esse trabalho apresenta análise combinada entre a macroeconomia e a estrutura a termo das taxas de juros, através de duas modelagens distintas. Primeiramente, utiliza-se o modelo Novo Keynesiano de pequeno porte, que é combinado com o modelo dinâmico de Nelson-Siegel. Em seguida estima-se o modelo dinâmico de Nelson-Siegel integrado com variáveis macroeconômicas. São empregados dados mensais referentes aos contratos futuros de DI, de Setembro de 2002 a Dezembro de 2017. A comparação das modelagens mostra que o modelo combinado apresenta resultados mais consistentes do que o modelo integrado. / This paper aims to present a combined analysis between macroeconomics and the term structure of interest rates, through two different models. Firstly, a small New Keynesian model is used, which is combined with the dynamic Nelson-Siegel model. Then the NelsonSiegel dynamic model integrated with macroeconomic variables is estimated. Monthly data on DI futures contracts are used from September 2002 to December 2017. Comparison of modeling shows that the combined model presents more consistent results than the integrated model.

Submitted by Alice Singer (lilicasinger@gmail.com) on 2013-02-27T16:25:59Z No. of bitstreams: 1 Dissertacao_Alice.pdf: 1210322 bytes, checksum: a587136246bce1145c8096d499e28342 (MD5) / Approved for entry into archive by Eliene Soares da Silva (eliene.silva@fgv.br) on 2013-02-27T16:28:28Z (GMT) No. of bitstreams: 1 Dissertacao_Alice.pdf: 1210322 bytes, checksum: a587136246bce1145c8096d499e28342 (MD5) / Made available in DSpace on 2013-02-27T16:33:15Z (GMT). No. of bitstreams: 1 Dissertacao_Alice.pdf: 1210322 bytes, checksum: a587136246bce1145c8096d499e28342 (MD5) Previous issue date: 2013-01-31 / Esse estudo foi motivado pela falta de bons fundos de investimento multimercado abertos para captação no Brasil e tem como objetivo analisar a viabilidade de utilizar a análise de estilo baseada em retorno para clonar retornos e comportamento de determinados fundos de investimento multimercado do mercado brasileiro. Modelos já testados no exterior e no Brasil foram pesquisados e optou-se por adaptar o modelo linear proposto por LIMA e VICENTE (2007). Verificou-se que o modelo de espaço de estados é mais adequado para clonar retornos de determinados fundos de investimento do que o modelo de regressão com parâmetros fixos. Resultados animadores foram obtidos para quatro dos cinco fundos analisados nesse estudo. / This work was motivated by the lack of hedge funds opened for new investments in Brazil and it aims to analyze the feasibility of using the style analyses to clone returns and behavior of certain Brazilian hedge funds. Models already tested abroad and in Brazil were investigated and it was decided to adapt the linear model proposed by LIMA and VICENTE (2007). It was found that the state space model is more suitable for cloning returns of certain hedge funds than fixed parameters regression models. Encouraging results were obtained for four of the five funds analyzed in this study.

Submitted by Camilo de Léllis Cavalcanti Júnior (camilojr@gmail.com) on 2013-09-20T14:38:32Z No. of bitstreams: 1 Dissertação - Estratégia de Trading Utilizando o Modelo Dinâmico de Nelson-Siegel Final.pdf: 1310470 bytes, checksum: f90849f3305d9519f30ddd197d650214 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-09-20T14:43:47Z (GMT) No. of bitstreams: 1 Dissertação - Estratégia de Trading Utilizando o Modelo Dinâmico de Nelson-Siegel Final.pdf: 1310470 bytes, checksum: f90849f3305d9519f30ddd197d650214 (MD5) / Made available in DSpace on 2013-09-20T14:49:57Z (GMT). No. of bitstreams: 1 Dissertação - Estratégia de Trading Utilizando o Modelo Dinâmico de Nelson-Siegel Final.pdf: 1310470 bytes, checksum: f90849f3305d9519f30ddd197d650214 (MD5) Previous issue date: 2013-08-21 / Esta pesquisa busca testar a eficácia de uma estratégia de arbitragem de taxas de juros no Brasil baseada na utilização do modelo de Nelson-Siegel dinâmico aplicada à curva de contratos futuros de taxa de juros de 1 dia da BM&FBovespa para o período compreendido entre 02 de janeiro de 2008 e 03 de dezembro de 2012. O trabalho adapta para o mercado brasileiro o modelo original proposto por Nelson e Siegel (1987), e algumas de suas extensões e interpretações, chegando a um dos modelos propostos por Diebold, Rudebusch e Aruoba (2006), no qual estimam os parâmetros do modelo de Nelson-Siegel em uma única etapa, colocando-o em formato de espaço de estados e utilizando o Filtro de Kalman para realizar a previsão dos fatores, assumindo que o comportamento dos mesmos é um VAR de ordem 1. Desta maneira, o modelo possui a vantagem de que todos os parâmetros são estimados simultaneamente, e os autores mostraram que este modelo possui bom poder preditivo. Os resultados da estratégia adotada foram animadores quando considerados para negociação apenas os 7 primeiros vencimentos abertos para negociação na BM&FBovespa, que possuem maturidade máxima próxima a 1 ano. / This research tries to test the effectiveness of an interest rate arbitrage strategy in Brazil based on a Dynamic Nelson-Siegel model applied to the term structure of future contracts of 1 day of interest rates traded at BM&FBovespa for the time between January, 2nd of 2008, and December, 3rd, 2012. The work adapts to the Brazilian market the mode originally proposed by Nelson and Siegel (1987), and some of its extensions and interpretations, reaching one of the models proposed by Diebold, Rudebusch and Aruoba (2006), in which they estimate the parameters of Nelson-Siegel Model in one only step, putting it in a state-space form and using the Kalman Filter to make the factors’ forecast, assuming that their behavior is an order 1 VAR. The model has the advantage that all the parameters are estimated simultaneously, and the authors showed that it has a good forecast power. The results of the adopted strategy were encouraging when considered for negotiation only the 7 first available maturities at BM&FBovespa, which have maturity of around 1 year.

Made available in DSpace on 2014-08-20T14:36:59Z (GMT). No. of bitstreams: 1 Dissertacao_Leandro_Sanzi_Aquino.pdf: 2633860 bytes, checksum: eeb09c0678ebe75556f513e8a4e089b7 (MD5) Previous issue date: 2010-02-25 / Soil land leveling is a technique used in low land areas and has the objective to improve agricultural use to facilitate the management of water both for irrigation and drainage operations, for the establishment of agricultural practices and crop harvest. However, it causes changes in the physical environment where the plant grows, and many studies have sought to identify the effect of this practice in the structure of soil spatial variability and in the relationship between the hydric-physical and chemical soil attributes. Thus, the objective of this study was to identify and characterize the structure of spatial variability of soil hydric-physical and chemical attributes of a low land soil, before and after land leveling, and to study the relationship between these soil attributes through an autoregressive state space model. In an experimental area of 0.81 ha belongs to Embrapa Clima Temperado situated in Capão do Leão county, state of Rio Grande do Sul, Brazil, was established a regular grid of 100 points spaced 10 m apart in both directions. At each point, soil disturbed and undisturbed samples were collected at the depth of 0-0.20 m to determine, before and after land leveling, the following soil attributes: clay, silt and sand contents, soil macroporosity, soil microporosity and soil total porosity, soil bulk density and soil water content at field capacity and permanent wilting point, soil organic carbon and cation exchange capacity. All data sets were organized into a spreadsheet in the form of a spatial transect consisting of 100 points and they were ordered following the gradient slope area resulting from the soil land leveling. Autocorrelograms and crosscorrelograms were built to evaluate the structure of spatial correlation of all soil attributes having served as a subsidy for the selection of variables in each autoregressive state-space model. The results show that the soil land leveling changed the structure of soil spatial dependence of all variables and between them as well. The soil cation exchange capacity and soil microporosity variables were the variables that made up the largest number of state space models, before and after soil land leveling. The contribution of the each variable at position i-1 to estimate its value at position increased to the sand content, silt content, soil bulk density, soil microporosity, soil macroporosity, soil water content at permanent wilting point, soil organic carbon and cation exchange capacity variables and decreased to soil water content at field capacity variable after land leveling. Soil land leveling improved the state space model performance for soil organic carbon content, sand content, soil bulk density, soil total porosity and soil water content at field capacity and permanent wilting point variables. The worst state space model performances, after soil land leveling, were found taking silt content, soil microporosity and cation exchange capacity variables as response variables. The best state space model performance, before land leveling, was obtained taking the soil total porosity as response variable. / A sistematização do solo é uma técnica utilizada em regiões planas, com características de várzea, e tem por objetivo aperfeiçoar o uso agrícola facilitando o manejo da água tanto de irrigação como de drenagem, as operações de implantação da lavoura, de tratos culturais e de colheita. No entanto, a sistematização do solo provoca alterações no ambiente físico onde a planta se desenvolve, sendo que muitos estudos têm buscado identificar o efeito dessa prática na estrutura de variabilidade espacial e no relacionamento entre os atributos físico-hídricos e químicos do solo. Dessa forma, o objetivo deste trabalho foi identificar e caracterizar a estrutura de variabilidade espacial dos atributos físico-hídricos e químicos de um solo de várzea, antes e depois da sistematização, assim como estudar o relacionamento entre esses atributos por meio de um modelo autoregressivo de espaço de estados. Em uma área experimental de 0,81 ha pertencente a Embrapa Clima Temperado, Capão do Leão-RS, foi estabelecida uma malha regular de 100 pontos, espaçados de 10 m entre si em ambas as direções. Em cada ponto foram coletadas amostras de solo deformadas e com estrutura preservada na profundidade de 0-0,20 m para a determinação, antes e depois da sistematização, dos teores de argila, silte e areia, macroporosidade, microporosidade e porosidade total, densidade do solo, conteúdo de água retido na capacidade de campo e ponto de murcha permanente, carbono orgânico e capacidade de troca de cátions. Os dados foram organizados em uma planilha de cálculo na forma de uma transeção espacial composta de 100 pontos e foram ordenados seguindo o gradiente de declividade da área resultante do processo de sistematização do solo. Para avaliar a estrutura de correlação espacial foram construídos autocorrelogramas e crosscorrelogramas que serviram de subsídio para a seleção de variáveis em cada um dos modelos autoregressivos de espaço de estados. Os resultados mostram que a sistematização do solo alterou a estrutura de dependência espacial tanto da variável como entre as variáveis deste estudo. A capacidade de troca de cátions e a microporosidade do solo foram as variáveis que compuseram o maior número de modelos de espaço de estados, antes e depois da sistematização. A contribuição da variável na posição i-1 na estimativa na posição i, por meio do modelo autoregressivo de espaço de estados, aumentou com a sistematização para as variáveis teor de areia, teor de silte, densidade do solo, microporosidade, macroporosidade, conteúdo de água no solo retido no ponto de murcha permanente, carbono orgânico e da capacidade de troca de cátions; e diminuiu para a variável conteúdo de água no solo retido na capacidade de campo.A sistematização do solo melhorou a estimativa, por meio dos modelos de espaço de estados, das variáveis carbono orgânico, teor de areia, densidade do solo, macroporosidade e do conteúdo de água no solo retido na capacidade de campo e no ponto de murcha permanente, sendo o modelo da variável porosidade total, antes da sistematização, que apresentou o melhor desempenho. Já os piores desempenhos dos modelos, depois da sistematização do solo, foram encontrados quando utilizadas as variáveis teor de silte, microporosidade e capacidade de troca de cátions como resposta.

Les études menées permettent de prendre en main un système depuis l’identification jusqu’à la commande robuste des systèmes non entiers. Les principes de la platitude permettent de parvenir à la planification de trajectoire à condition de connaître le modèle du système, d’où l’intérêt de l’identification des paramètres du système. Les principaux travaux de cette thèse concernent l’identification de système par modèles non entiers, la génération et la poursuite robuste de trajectoire par l’application des principes de la platitude aux systèmes non entiers.Le chapitre 1 rappelle les définitions et propriétés de l’opérateur non entier ainsi que les diverses méthodes de représentation d’un système non entier. Le théorème de stabilité est également remémoré. Les algèbres sur les polynômes non entiers et sur les matrices polynômiales non entières sont introduites pour l’extension de la platitude aux systèmes non entiers.Le chapitre 2 porte sur l’identification par modèle non entier. Après un état de l’art sur les méthodes d’identification par modèle non entier, deux contextes sont étudiés : en présence de bruit blanc et en présence de bruit coloré. Dans chaque cas, deux estimateurs optimaux (sur la variance et le biais) sont propos´es : l’un, en supposant une structure du modèle connue et d’ordres de dérivation fixés, et l’autre en combinant des techniques de programmation non linéaire qui optimise à la fois les coefficients et les ordres de dérivation.Le chapitre 3 établit l’extension des principes de la platitude aux systèmes non entiers.La platitude des systèmes non entiers linéaires en proposant différentes approches telles que les fonctions de transfert et la pseudo-représentation d’état par matrices polynômiales est étudiée.La robustesse du suivi de trajectoire est abordée par la commande CRONE. Des exemples de simulations illustrent les développements théoriques de la platitude au travers de la diffusion thermique sur un barreau métallique.Enfin, le chapitre 4 est consacré à la validation des contributions en identification, en planification de trajectoire et en poursuite robuste sur un système non entier réel : un barreau métallique est soumis à un flux de chaleur. / The general theme of the work enables to handle a system, from identification to robust control. Flatness principles tackle path planning unless knowing the system model, hence the system parameter identification necessity. The principal contribution of this thesis deal with system identification by non integer models and with robust path tracking by the use of flatness principles for fractional models.Chapter 1 recalls the definitions and properties of a fractional operator and also the various representation methods of a fractional system. The stability theorem is also brought to mind. Fractional polynomial and fractional polynomial matrice algebras are introduced for the extension of flatness principles for fractional systems.Chapter 2 is about non integer model identification. After a state of the art on system identification by non integer model. Two contexts are considered : in presence of white noise and of colored noise. In each situation, two optimal (in variance and bias sense) estimators are put forward : one, when considering a known model structure with fixed differentiating orders, and another one by combining nonlinear programming technics for the optimization of coefficients and differentiating orders.Chapter 3 establishes the extension of flatness principles to fractional systems. Flatness of linear fractional systems are studied while considering different approaches such as transfer functions or pseudo-state-space representations with polynomial matrices. Path tracking robustness is ensured with CRONE control. Simulation examples display theoretical developments on flatness through thermal diffusion on a metallic rod. Finally, Chapter 4 is devoted to validate the contributions to system identification, to trajectory planning and to robust path tracking on a real fractional system : a metallic rod submitted to a heat flux.

Recent breakthrough studies by Gali and Gertler (1999), Sbordone (2002) and Roberts (2001) argue that the New Keynesian Phillips curve (based on Calvo pricing model) is empirically valid concept and they conclude that the real marginal costs are preferred driving force to output gap in inflation dynamics for open economies. Neiss and Nelson (2002) and Gali, Gertler and Salido (2001), in turn, contradict that to date, there has been only little empirical evidence to support this statement. Neiss and Nelson (2002) add that "once output gap is defined consistently with economic theory, the gap-based New Keynesian Phillips curve has a fit with data which is at least as good as the real marginal costs-based one". For this purpose, my study investigates relationship between output gap and inflation described in the hybrid New Keynesian Phillips curve. Study estimates key coefficients of the hybrid gap-based New Keynesian Phillips curve, with both forward- and backward-looking inflation components, in the Czech Republic for periods 2000Q1 - 2012Q4 using Kalman filtration. My findings suggest that (i) output gap has a significant impact on Czech inflation dynamics (ii) share of forward-looking agents predominates to backward-looking agents in the Czech Republic and (iii) Czech inflation seems to be significantly driven by change in import prices.

Le volume des données disponibles permettant de décrire l’environnement, en particulier l’atmosphère et les océans, s’est accru à un rythme exponentiel. Ces données regroupent des observations et des sorties de modèles numériques. Les observations (satellite, in situ, etc.) sont généralement précises mais sujettes à des erreurs de mesure et disponibles avec un échantillonnage spatio-temporel irrégulier qui rend leur exploitation directe difficile. L’amélioration de la compréhension des processus physiques associée à la plus grande capacité des ordinateurs ont permis des avancées importantes dans la qualité des modèles numériques. Les solutions obtenues ne sont cependant pas encore de qualité suffisante pour certaines applications et ces méthodes demeurent lourdes à mettre en œuvre. Filtrage et lissage (les méthodes d’assimilation de données séquentielles en pratique) sont développés pour abonder ces problèmes. Ils sont généralement formalisées sous la forme d’un modèle espace-état, dans lequel on distingue le modèle dynamique qui décrit l’évolution du processus physique (état), et le modèle d’observation qui décrit le lien entre le processus physique et les observations disponibles. Dans cette thèse, nous abordons trois problèmes liés à l’inférence statistique pour les modèles espace-états: reconstruction de l’état, estimation des paramètres et remplacement du modèle dynamique par un émulateur construit à partir de données. Pour le premier problème, nous introduirons tout d’abord un algorithme de lissage original qui combine les algorithmes Conditional Particle Filter (CPF) et Backward Simulation (BS). Cet algorithme CPF-BS permet une exploration efficace de l’état de la variable physique, en raffinant séquentiellement l’exploration autour des trajectoires qui respectent le mieux les contraintes du modèle dynamique et des observations. Nous montrerons sur plusieurs modèles jouets que, à temps de calcul égal, l’algorithme CPF-BS donne de meilleurs résultats que les autres CPF et l’algorithme EnKS stochastique qui est couramment utilisé dans les applications opérationnelles. Nous aborderons ensuite le problème de l’estimation des paramètres inconnus dans les modèles espace-état. L’algorithme le plus usuel en statistique pour estimer les paramètres d’un modèle espace-état est l’algorithme EM qui permet de calculer itérativement une approximation numérique des estimateurs du maximum de vraisemblance. Nous montrerons que les algorithmes EM et CPF-BS peuvent être combinés efficacement pour estimer les paramètres d’un modèle jouet. Pour certaines applications, le modèle dynamique est inconnu ou très coûteux à résoudre numériquement mais des observations ou des simulations sont disponibles. Il est alors possible de reconstruire l’état conditionnellement aux observations en utilisant des algorithmes de filtrage/lissage dans lesquels le modèle dynamique est remplacé par un émulateur statistique construit à partir des observations. Nous montrerons que les algorithmes EM et CPF-BS peuvent être adaptés dans ce cadre et permettent d’estimer de manière non-paramétrique le modèle dynamique de l’état à partir d'observations bruitées. Pour certaines applications, le modèle dynamique est inconnu ou très coûteux à résoudre numériquement mais des observations ou des simulations sont disponibles. Il est alors possible de reconstruire l’état conditionnellement aux observations en utilisant des algorithmes de filtrage/lissage dans lesquels le modèle dynamique est remplacé par un émulateur statistique construit à partir des observations. Nous montrerons que les algorithmes EM et CPF-BS peuvent être adaptés dans ce cadre et permettent d’estimer de manière non-paramétrique le modèle dynamique de l’état à partir d'observations bruitées. Enfin, les algorithmes proposés sont appliqués pour imputer les données de vent (produit par Météo France). / The amount of both observational and model-simulated data within the environmental, climate and ocean sciences has grown at an accelerating rate. Observational (e.g. satellite, in-situ...) data are generally accurate but still subject to observational errors and available with a complicated spatio-temporal sampling. Increasing computer power and understandings of physical processes have permitted to advance in models accuracy and resolution but purely model driven solutions may still not be accurate enough. Filtering and smoothing (or sequential data assimilation methods) have developed to tackle the issues. Their contexts are usually formalized under the form of a space-state model including the dynamical model which describes the evolution of the physical process (state), and the observation model which describes the link between the physical process and the available observations. In this thesis, we tackle three problems related to statistical inference for nonlinear state-space models: state reconstruction, parameter estimation and replacement of the dynamic model by an emulator constructed from data. For the first problem, we will introduce an original smoothing algorithm which combines the Conditional Particle Filter (CPF) and Backward Simulation (BS) algorithms. This CPF-BS algorithm allows for efficient exploration of the state of the physical variable, sequentially refining exploration around trajectories which best meet the constraints of the dynamic model and observations. We will show on several toy models that, at the same computation time, the CPF-BS algorithm gives better results than the other CPF algorithms and the stochastic EnKS algorithm which is commonly used in real applications. We will then discuss the problem of estimating unknown parameters in state-space models. The most common statistical algorithm for estimating the parameters of a space-state model is based on EM algorithm, which makes it possible to iteratively compute a numerical approximation of the maximum likelihood estimators. We will show that the EM and CPF-BS algorithms can be combined to effectively estimate the parameters in toy models. In some applications, the dynamical model is unknown or very expensive to solve numerically but observations or simulations are available. It is thence possible to reconstruct the state conditionally to the observations by using filtering/smoothing algorithms in which the dynamical model is replaced by a statistical emulator constructed from the observations. We will show that the EM and CPF-BS algorithms can be adapted in this framework and allow to provide non-parametric estimation of the dynamic model of the state from noisy observations. Finally the proposed algorithms are applied to impute wind data (produced by Méteo France).