Orientador: Víctor Hugo Lachos Dávila / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica / Made available in DSpace on 2018-08-24T00:22:53Z (GMT). No. of bitstreams: 1 Costa_DeniseReis_D.pdf: 5095534 bytes, checksum: 5bb05e15edf36db32e78eff601b757db (MD5) Previous issue date: 2013 / Resumo: Modelos de variáveis latentes são amplamente utilizados por psicometristas, econometristas e pesquisadores da área de ciencias sociais para modelar variáveis que não podem ser medidas diretamente, conhecidas como construtos ou efeitos aleatórios (Skrondal e Rabe-Hesketh, 2004). Na literatura, é muito comum verificar a utilização da distribuição normal para a modelagem dessas variáveis, contudo tal suposição pode ser inadequada, especialmente na presença de valores discrepantes. Preocupados com a sensibilidade das inferências sob a presença de potenciais pontos discrepantes ou com dados provenientes de distribuições com caudas pesadas, nesta tese propomos métodos de inferência robusta, utilizando a distribuição t de Student multivariada, para dois tipos de modelos de variáveis latentes: o modelo linear generalizado misto para respostas binárias (GLMM) e o modelo de análise fatorial Tobit (TCFA) para respostas contínuas e censuradas. Para a estimação dos parâmetros dos modelos estudados, um algoritmo do tipo EM foi proposto e este apresenta expressões fechadas no passo E que utiliza os dois primeiros momentos de uma distribuição multivariada t truncada. Adicionalmente apresentamos uma abordagem via análise Bayesiana e propomos medidas de diagnóstico de influência para dados censurados sob o modelo TCFA quando a suposição de normalidade é assumida. Para avaliação dos métodos propostos, foram realizados alguns estudos simulados, além da aplicação a conjuntos de dados reais. / Abstract: Latent variable models are broadly used by psychometrists, econometrists and social science researchers to model variables that cannnot be directly measured, known as constructs or random effects (Skrondal and Rabe-Hesketh, 2004). In the literature, such variables are commonly modeled with a normal distribution, but such assumption may be inadequate, especially when there are outliers. Concerned with the sensitivity of the inferences under the presence of potential outliers or data derived from heavy-tailed distributions, this thesis proposes robust inference models, using the mutivariate t-Student distribution, for two types of latent variable models: the Generalized Linear Mixed Model for correlated binary data (GLMM) and the Tobit Confirmatory Factor Analysis (TCFA) for continuous and censored data. In order to estimate the parameters of the studied models, an EM-type algorithm was proposed. This algorithm presents closed expressions on the E-step which use the two first moments of a multivariate truncated t-distribution. Moreover, we present a Bayesian approach and propose measures of influence diagnostics for censored data under the TCFA model when normality is assumed. In order to evaluate the proposed methods, simulated studies were carried out, as well as the application on real datasets. / Doutorado / Estatistica / Doutor em Estatística

[pt] Esta tese teve como objetivo o estudo do problema de Desempenho H2 Robusto, com enfase para o caso de perturbações lineares não estruturadas nos fatores coprimos normalizados da função de transferência que representa uma determinada planta nominal. A primeira parte desta tese foi dedicada à determinação de um novo índice de Desempenho H2 Robusto pela utilização de limitantes superiores, levando em conta dois fatores: melhoria destes limitantes com relação aos limitantes propostos na literatura e viabilidade de sua implementação numérica. A parte seguinte da tese foi dedicada à determinação de elementos que influenciam no Desempenho H2 Robusto. Estes elementos serviram de base para a definição de problemas de controle multiobjetivos que, por sua vez, geraram uma classe de controladores sobre a qual foi otimizado o índice de Desempenho H2 Robusto proposto nesta tese. / [en] The objective of this thesis was the study of the Robust H2 Performance problem, with emphasis on the case of linear and unstructured perturbations on the normalized coprime factors of the transfer function that represents the nominal plant. The first was dedicated to the determination of a new Robust H2 Performance index, by the utilization of upper bounds, taking into accunt two factors: better upper bounds, with relation to upper bonds proposed in the literature, and numerical implementation viability. The second part was dedicated to the determination of elements that have influence in the Robust H2 Performance. These elements became a basis for the definition of multiobjetive control problems, that generate a class of controllers, over which the Robust H2 Performance index, proposed in the first part of this thesis, was optimizated.

[pt] Esta tese apresenta um estudo na área de controle robusto não paramétrico, mais precisamente relacionado ao Problema H2/Hinf. O Principal objetivo deste trabalho consiste no projeto de controladores por uma abordagem direta sobre o problema mencionado, baseada em método de Gallerkin. Dois métodos foram propostos, sendo denominados Expansão em Base Pré-Estabelecida (EBPE) e Expansão em Base Otimizada (EBO). Para a aplicação destes métodos, os controladores estabilizantes do sistema em estudo devem ser explicitados por intermédio da parametrização de Youla. Em seguida, uma nova parametrização é realizada a fim de colocar o problema resultante em um formato padrão, com a norma Hinf sob a forma do problema de Nehari. Um controlador calculado por EBO ou EBPE possui ordem previamente determinada, estabiliza internamente a planta, minimiza um funcional de desempenho e satisfaz a um nível pré- especificado de robustez em estabilidade. Em EBPE, uma base é escolhida para o espaço solução e o ajuste dos coeficientes de seus vetores é realizado minimizando o critério proposto. A vantagem deste método é resolver um problema de otimização convexo. Por outro lado, a escolha dos vetores que participarão da base truncada já estará definida, levando a uma solução com ordem superior àquela obtida por EBO e um mesmo nível de desempenho. No método EBO, as tarefas de escolha dos vetores que participarão da base e seus respectivos ajustes de coeficientes são realizados simultaneamente. Embora este problema seja não convexo, sua vantagem reside na possibilidade de encontrar soluções com ordens relativamente menores em comparação com aquelas por EBPE para um mesmo nível de desempenho. Adicionalmente, discute-se alguns resultados teóricos, onde a existência e a unicidade da solução do Problema H2/Hinf são demonstradas. Mostra-se também que a sequência de controladores calculados pelos métodos propostos, à medida que a ordem aumenta, converge para a solução ótima do problema original. / [en] This thesis presents a study on the subject of robust and non parametrical control, more precisely related to the Mixed H2/Hinf problem. The main purpose of this work consists in the controllers design by a direct approach over the mentioned problem, using Galerkin`s method. Two numerical methods were proposed, being known as Pre- Established Basis Expansion (EBPE) and Optimized Basis Expansion (EBO). For the application of these methods, the stabilizing controllers of the system under analisys must be explicated by Youla`s parametrization. After this, a new parametrization is performed in order to set the problem in a standard format, with the Hinf-norm in the Nehari problem. A controller computed by EBO or EBPE has a previously specified order, internally stabilizes the plant, minimizes a performance functional and satisfies a pre- established robustness stability margin. In the EBPE method, a basis is chosen from space solution and the adjustment of the vectors` coefficients is performed minimizing the proposed criterion. The advantage is solve a convex optimization problem. By the other side, the choice of vectors in the truncated basis will be defined, leading to a solution with a higher order than the one obtained by the EBO approach, for the same performance level In the EBO method, both the vectors` choice in the truncated basis and their respective coefficient adjustment are performed simultaneously. The Youla`s parameter is approximated by the class of real, rational, proper and stable transfer function and the project variables are the coefficients of the numerator and denominator polynomials. Although this problem is a non- convex one, its main advantage lies in the possibility of finding controllers of relatively lower orders than ones by EBPE at the same level of performance. In addition, some theoretical results are discussed, where the existence and uniqueness of Mixid H2/Hinf problem solution are proved. It is also shown that the sequence of controllers computed by the proposed methods, as order increase, converges to the solution of the original problem.

Voice control is a technology that most people encounter or use on a daily basis. The voice control technology can be used to interpret voice commands and execute tasks based on the command pronounced. According to previous studies problems arise with the precision when the voice control technologies are used in noisy environments. This study has been conducted as an experiment where the precision in two voice control frameworks for Android has been examined. The purpose with this study is to examine the precision in these two frameworks to assist a decision making for an organisation who has developed an application which will be used by midwives in low and middle income countries. Two prototypes was developed using the two voice control frameworks PocketSphinx and iSpeech. The precision of these frameworks was tested in three different surroundings. The surroundings the frameworks was tested in had the decibel levels 25, 60, and 80. The result shows that the number of correctly registered voice commands reduces considerably depending on which sound level the frameworks are being tested in. The framework who got the most voice commands correctly registered was PocketSphinx, but even this framework had a big margin of error. / Röststyrning är idag en teknologi som de flesta människor någon gång stöter på eller använder sig av dagligen. Röststyrningsteknologin kan användas för att tolka vissa kommandon som sedan utför en uppgift baserat på det kommando som uttalas. Enligt tidigare studier uppkommer det problem med precisionen hos de röststyrningsramverk som används i bullriga miljöer. Denna studie har utförts som ett experiment där precisionen hos två stycken röststyrningsramverk för Android har undersökts. Syftet med denna studie var att undersöka precisionen hos dessa ramverk för att bistå med underlag till en organisation som utvecklat en applikation som används av barnmorskor i låg- och medelinkomstländer. Två stycken prototyper utvecklades med hjälp av röststyrningsramverken PocketSphinx och iSpeech. Dessa ramverks precision testades i tre stycken olika miljöer. De miljöer som prototyperna testades i hade ljudnivåerna 25dB, 60dB samt 80dB. Resultatet påvisar att antalet korrekt registrerade kommandon minskar avsevärt beroende på vilken ljudnivå som ramverken testas i. Det ramverk som korrekt registrerade flest röstkommandon var PocketSphinx men även denna hade en stor felmarginal.

Improving the efficiency of spectrum access and utilization under the umbrella of cognitive radio (CR) is one of the most crucial research areas for nearly two decades. The results have been algorithms called cognitive radio engines which use machine learning (ML) to learn and adapt the communication's link based on the operating scenarios. While a number of algorithms for cognitive engine design have been identified, it is widely understood that significant room remains to grow the capabilities of the cognitive engines, and substantially better spectrum utilization and higher throughput can be achieved if cognitive engines are improved. This requires working through some difficult challenges and takes an innovative look at the problem. A tenet of the existing cognitive engine designs is that they are usually designed around one primary ML algorithm or framework. In this dissertation, we discover that it is entirely possible for an algorithm to perform better in one operating scenario (combination of channel conditions, available energy, and operational objectives such as max throughput, and max energy efficiency) while performing less effectively in other operating scenarios. This arises due to the unique behavior of an individual ML algorithm regardless of its operating conditions. Therefore, there is no individual algorithm or parameter sets that have superiority in performance over all other algorithms or parameter sets in all operating scenarios. Using the same algorithm at all times may present a performance that is acceptable, yet may not be the best possible performance under all operating scenarios we are faced with over time. Ideally, the system should be able to adapt its behavior by switching between various ML algorithms or adjusting the operating ML algorithm for the prevailing operating conditions and goal. In this dissertation, we introduce a novel architecture for cognitive radio engines, with the goal of better cognitive engines for improved link adaptation in order to enhance spectrum utilization. This architecture is capable of meta-reasoning and metacognition and the algorithms developed based on this architecture are called metacognitive engines (meta-CE). Meta-reasoning and metacognitive abilities provide for self-assessment, self-awareness, and inherent use and adaptation of multiple methods for link adaptation and utilization. In this work, we provide four different implementation instances of the proposed meta-CE architecture. First, a meta-CE which is equipped with a classification algorithm to find the most appropriate individual cognitive engine algorithm for each operating scenario. The meta-CE switches between the individual cognitive engine algorithms to decrease the training period of the learning algorithms and not only find the most optimal communication configuration in the fastest possible time but also provide the acceptable performance during its training period. Second, we provide different knowledge indicators for estimating the experience level of cognitive engine algorithms. We introduce a meta-CE equipped with these knowledge indicators extracted from metacognitive knowledge component. This meta-CE adjusts the exploration factors of learning algorithms to gain higher performance and decrease training time. The third implementation of meta-CE is based on the robust training algorithm (RoTA) which switches and adjusts the individual cognitive engine algorithms to guarantee a minimum performance level during the training phase. This meta-CE is also equipped with forgetting factor to deal with non-stationary channel scenarios. The last implementation of meta-CE enables the individual cognitive engine algorithms to handle delayed feedback scenarios. We analyze the impact of delayed feedback on cognitive radio engines' performances in two cases of constant and varying delay. Then we propose two meta-CEs to address the delayed feedback problem in cognitive engine algorithms. Our experimental results show that the meta-CE approach, when utilized for a CRS engine performed about 20 percent better (total throughput) than the second best performing algorithm, because of its ability to learn about its own learning and adaptation. In effect, the meta-CE is able to deliver about 70% more data than the CE with the fixed exploration rate in the 1000 decision steps. Moreover, the knowledge indicator (KI) autocorrelation plots show that the proposed KIs can predict the performance of the CEs as early as 100 time steps in advance. In non-stationary environments, the proposed RoTA based meta-CE guarantees the minimum required performance of a CRS while it’s searching for the optimal communication configurations. The RoTA based meta-CE delivers at least about 45% more data than the other algorithms in non-stationary scenarios when the channel conditions are often fluctuating. Furthermore, in delayed feedback scenarios, our results show that the proposed meta-CE algorithms are able to mitigate the adverse impact of delay in low latency scenarios and relieve the effects in high latency situations. The proposed algorithms show a minimum of 15% improvement in their performance compared to the other available delayed feedback strategies in literature. We also empirically tested the algorithms introduced in this dissertation and verified the results therein by designing an over the air (OTA) radio setup. For our experiments, we used GNU Radio and LiquidDSP as free software development toolkits that provide signal processing blocks to implement software-defined radios and signal-processing systems such as modulation, pulse-shaping, frame detection, equalization, and others. We also used two USRP N200 with WBX daughterboards, one as a transmitter and the other as a receiver. In these experiments, we monitored the packet success rate (PSR), throughput, and total data transferred as our key performance indicators (KPI). Then, we tested different proposed meta-CE algorithms in this dissertation to verify the productivity of the proposed algorithms in an OTA real-time radio setup. We showed that the experiments’ outputs support our simulations results as well.

Le contexte général des travaux de recherche de cette thèse concerne les problématiques liées à l’optimisation glob-ale liée à la conception des futurs satellites d’observation terrestre et de missions scientifiques, nécessitantune très haute stabilité en pointage (capacité du satellite à garder son point de visée). Plus particulièrement,les travaux concernent le contrôle actif des modes micro-vibratoires.Dans une mission satellitaire d’observation terrestre, la qualité des images dépend bien évidemmentdes instruments de mesure optique (diamètre du miroir, aberrations optiques et qualité du polissage)mais également des performances de la stabilité de la ligne de visée du satellite qui peut s’avérer dégradéepour cause de micro-vibrations. La présence de ces micro-vibrations est liée aux divers éléments tournantdu satellite tels que les mécanismes de rotation des panneaux solaires ou de contrôle d’orientation dusatellite (on parle de contrôle d’attitude réalisé au moyen de roues inertielles).Le contrôle des micro-vibrations représentent ainsi un défit technologique, conduisant l’ESA et les ac-teurs industriels du monde spatial, a considéré cette problématique comme hautement prioritaire pour ledéveloppement des satellites d’observation terrestre nouvelle génération.Il existe à l’heure actuelle deux principes fondamentaux de contrôle des micro-vibrations :• le contrôle dit passif: la stratégie consiste à introduire des dispositions constructives et des matériauxparticuliers permettant de minimiser la transmission des vibrations à l’environnement.• le contrôle dit actif : le concept de contrôle actif des vibrations est tout autre : l’idée est cette fois-ci,de bloquer la micro-vibration en exerçant une vibration antagoniste créée artificiellement avec despropriétés en opposition, à tout instant, relativement à la vibration indésirable, pour rendre nulleleur somme.L’industrie spatiale aborde cette problématique en plaçant des isolateurs en élastomère au voisinage dechaque source de micro-vibrations. Cette solution, qui a fait ses preuves puisqu’elle équipe actuelle-ment nombre de satellites en orbite, permet de rejeter nombre de micro-vibrations. Malheureusement,la demande de plus en plus importante de grande stabilité de la ligne de visée pour les futures missionsd’observation terrestres telles que les missions GAIA rend l’approche passive insuffisante.L’ESA et Airbus Defence and Space, ont donc collaborer conjointement avec l’équipe ARIA au travers decette thèse, dans des travaux de recherche dans le domaine du contrôle actif pour palier ces problèmes.L’objectif visé est de coupler les approches passives et actives afin de rejeter à la fois les micro-vibrations enhautes fréquences (approche passive existant) et en basses fréquences (approche active objet des travauxde la thèse) / Next generation satellite missions will have to meet extremely challenging pointing stability requirements. Even low levels of vibration can introduce enough jitter in the optical elements to cause a significant reduction in image quality. The success of these projects is therefore constrained by the ability of on-board vibration isolation and optical control techniques to keep stable the structural elements of the spacecraft in the presence of external and internal disturbances.In this context, the research work presented in this thesis combines the expertise of the European Space Agency (ESA), the industry (Airbus Defence and Space) and the IMS laboratory (laboratoire de l’Intégration du Matériau au Système) with the aim of developing new generation of robust microvibration isolation systems for future space observation missions. More precisely, the thesis presents the development of an Integrated Modeling, Control and Analysis framework in which to conduct advanced studies related to reaction wheel microvibration mitigation.The thesis builds upon the previous research conducted by Airbus Defence and Space and ESA on the use of mixed active/passive microvibration mitigation techniques and provides a complete methodology for the uncertainty modeling, robust control system design and worst-case analysis of such systems for a typical satellite observation mission. It is shown how disturbances produced by mechanical spinning devices such as reaction wheels can be significantly attenuated in order to improve the pointing stability of the spacecraft even in the presence of model uncertainty and other nonlinear phenomenon.Finally, the work introduces a new disturbance model for the multi harmonic perturbation spectrum produced by spinning reaction wheels that is suitable for both controller synthesis and worst-case analysis using modern robust control tools. This model is exploited to provide new ways of simulating the image distortions induced by such disturbances.

Au cours de ces dernières années, les matrices de covariance ont montré leur intérêt dans de nombreuses applications en traitement du signal et de l'image.Les travaux présentés dans cette thèse se concentrent sur l'utilisation de ces matrices comme descripteurs pour la classification. Dans ce contexte, des algorithmes robustes de classification sont proposés en développant les aspects suivants.Tout d'abord, des estimateurs robustes de la matrice de covariance sont utilisés afin de réduire l'impact des observations aberrantes. Puis, les distributions Riemannienne Gaussienne et de Laplace, ainsi que leur extension au cas des modèles de mélange, sont considérés pour la modélisation des matrices de covariance.Les algorithmes de type k-moyennes et d'espérance-maximisation sont étendus au cas Riemannien pour l'estimation de paramètres de ces lois : poids, centroïdes et paramètres de dispersion. De plus, un nouvel estimateur du centroïde est proposé en s'appuyant sur la théorie des M-estimateurs : l'estimateur de Huber. En outre,des descripteurs appelés vecteurs Riemannien de Fisher sont introduits afin de modéliser les images non-stationnaires. Enfin, un test d'hypothèse basé sur la distance géodésique est introduit pour réguler la probabilité de fausse alarme du classifieur.Toutes ces contributions sont validées en classification d'images de texture, de signaux du cerveau, et d'images polarimétriques radar simulées et réelles. / In the recent years, covariance matrices have demonstrated their interestin a wide variety of applications in signal and image processing. The workpresented in this thesis focuses on the use of covariance matrices as signatures forrobust classification. In this context, a robust classification workflow is proposed,resulting in the following contributions.First, robust covariance matrix estimators are used to reduce the impact of outlierobservations, during the estimation process. Second, the Riemannian Gaussianand Laplace distributions as well as their mixture model are considered to representthe observed covariance matrices. The k-means and expectation maximization algorithmsare then extended to the Riemannian case to estimate their parameters, thatare the mixture's weight, the central covariance matrix and the dispersion. Next,a new centroid estimator, called the Huber's centroid, is introduced based on thetheory of M-estimators. Further on, a new local descriptor named the RiemannianFisher vector is introduced to model non-stationary images. Moreover, a statisticalhypothesis test is introduced based on the geodesic distance to regulate the classification false alarm rate. In the end, the proposed methods are evaluated in thecontext of texture image classification, brain decoding, simulated and real PolSARimage classification.

Un système est dit robuste s'il est possible de garantir son bon comportement dynamique malgré les dispersions de ses caractéristiques lors de sa fabrication, les variations de l'environnement ou encore son vieillissement. Au-delà du fait que la dispersion des caractéristiques est inéluctable, une plus grande dispersion permet notamment de diminuer fortement les coûts de production. La prise en compte explicite de la robustesse par les ingénieurs est donc un enjeu crucial lors de la conception d'un système. Des propriétés robustes peuvent être garanties lors de la synthèse d'un correcteur en boucle fermée. Il est en revanche beaucoup plus difficile de garantir ces propriétés en boucle ouverte, ce qui concerne par exemple des cas comme la synthèse d'estimateur.Prendre en compte la robustesse lors de la synthèse est une problématique importante de la communauté du contrôle robuste. Un certain nombre d'outils ont été développés pour analyser la robustesse d'un système vis-à-vis d'un ensemble d'incertitudes(μ analyse par exemple). Bien que le problème soit intrinsèquement complexe au sens algorithmique, des relaxations ont permis de formuler des conditions suffisantes pour tester la stabilité d'un système vis-à-vis d'un ensemble d'incertitudes. L'émergence de l'Optimisation sous contrainte Inégalité Matricielle Linéaire (LMI) a permis de tester ces conditions suffisantes au moyen d'un algorithme efficace, c'est-à-dire convergeant vers une solution en un temps raisonnable grâce au développement des méthodes des points intérieurs.En se basant sur ces résultats d'analyse, le problème de synthèse de correcteurs en boucle fermée ne peut pas être formulé sous la forme d'un problème d'optimisation pour lequel un algorithme efficace existe. En revanche, pour certains cas comme la synthèse de filtres robustes, le problème de synthèse peut être formulé sous la forme d'un problème d'optimisation sous contrainte LMI pour lequel un algorithme efficace existe. Ceci laisse entrevoir un certain potentiel de l'approche robuste pour la synthèse d'estimateurs.Exploitant ce fait, cette thèse propose une approche complète du problème de synthèse d'estimateurs robustes par l'intermédiaire des outils d'analyse de la commande robuste en conservant le caractère efficace de la synthèse lié aux outils classiques. Cette approche passe par une ré-interprétation de l'estimation nominale (sans incertitude) par l'optimisation sous contrainte LMI, puis par une extension systématique des outils de synthèse et d'analyse développés pour l'estimation nominale à l'estimation robuste.Cette thèse présente des outils de synthèse d'estimateurs, mais également des outils d'analyse qui permettront de tester les performances robustes atteintes par les estimateurs.Les résultats présentés dans ce document sont exprimés sous la forme de théorèmes présentant des contraintes LMI. Ces théorèmes peuvent se mettre de façon systématique sous la forme d'un problème d'optimisation pour lequel un algorithme efficace existe.Pour finir, les problèmes de synthèse d'estimateurs robustes appartiennent à une classe plus générale de problèmes de synthèse robuste : les problèmes de synthèse robuste en boucle ouverte. Ces problèmes de synthèse ont un potentiel très intéressant. Des résultats de base sont formulés pour la synthèse en boucle ouverte, permettant de proposer des méthodes de synthèse robustes dans des cas pour lesquels la mise en place d'une boucle de rétroaction est impossible. Une extension aux systèmes LPV avec une application à la commande de position sans capteur de position est également proposée. / A system is said to be robust if it is possible to guarantee his dynamic behaviour despite dispersion of his features due to production, environmental changes or aging. beyond the fact that a dispersion is ineluctable, a greater one allows to reduce production costs. Thus, considering robustness is a crucial stake during the conception of a system.Robustness can be achieved using feedback, but is more difficult in Open-Loop, which concerns estimator synthesis for instance.Robustness is a major concern of the Robust Control Community. Many tools have been developed to analyse robustness of a system towards a set of uncertainties (μ analysis for instance). And even if the problem is known to be difficult (speaking of complexity), sufficient conditions allow to formulate results to test the robust stability of a system. Thanks to the development of interior point methods, the emergence of optimization under Linear Matrix Inequalities Constraints allows to test these results using an efficient algorithm.Based on these analysis results, the robust controller synthesis problem cannot be recast as a convex optimization problem involving LMI. But for some cases such as filter synthesis, the synthesis problem can recast as a convex optimization problem. This fact let sense that robust control tools have some potential for estimators synthesis.Exploiting this fact, this thesis ofiers a complete approach of robust estimator synthesis, using robust control tools, while keeping what made the nominal approaches successful : eficient computation tools. this approach goes through reinterpretation of nominal estimation using LMI optimization, then propose a systematic extension of these tools to robust estimation.This thesis presents not only synthesis tools, but also analysis tools, allowing to test the robust performance reached by estimators All the results are proposed as convex optimization problems involving LMI.As a conclusion, robust estimator synthesis problems belong to a wider class of problems : robust open-loop synthesis problems, which have a great potential in many applications. Basic results are formulated for open-loop synthesis, providing results for cases where feedback cannot be used. An extension to LPV systems with an application to sensorless control is given.

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01 Abstract: This thesis is concerned with the robust methods in portfolio theory. Different risk measures used in portfolio management are introduced and the corresponding robust portfolio optimization problems are formulated. The analytical solutions of the robust portfolio optimization problem with the lower partial moments (LPM), value-at-risk (VaR) or conditional value-at-risk (CVaR), as a risk measure, are presented. The application of the worst-case conditional value-at-risk (WCVaR) to robust portfolio management is proposed. This thesis considers WCVaR in the situation where only partial information on the underlying probability distribution is available. The minimization of WCVaR under mixture distribution uncertainty, box uncertainty, and ellipsoidal uncertainty are investigated. Several numerical examples based on real market data are presented to illustrate the proposed approaches and advantage of the robust formulation over the corresponding nominal approach.