The primary goal of this thesis is to study finite element based a priori and a posteriori error estimates of optimal control problems of various kinds governed by linear elliptic PDEs (partial differential equations) of second and fourth orders. This thesis studies interior and boundary control (Neumann and Dirichlet) problems. The initial chapter is introductory in nature. Some preliminary and fundamental results of finite element methods and optimal control problems which play key roles for the subsequent analysis are reviewed in this chapter. This is followed by a brief literature survey of the finite element based numerical analysis of PDE constrained optimal control problems. We conclude the chapter with a discussion on the outline of the thesis. An abstract framework for the error analysis of discontinuous Galerkin methods for control constrained optimal control problems is developed in the second chapter. The analysis establishes the best approximation result from a priori analysis point of view and delivers a reliable and efficient a posteriori error estimator. The results are applicable to a variety of problems just under the minimal regularity possessed by the well-posedness of the problem. Subsequently, the applications of p p - interior penalty methods for a boundary control problem as well as a distributed control problem governed by the bi-harmonic equation subject to simply supported boundary conditions are discussed through the abstract analysis. In the third chapter, an alternative energy space based approach is proposed for the Dirichlet boundary control problem and then a finite element based numerical method is designed and analyzed for its numerical approximation. A priori error estimates of optimal order in the energy norm and the m norm are derived. Moreover, a reliable and efficient a posteriori error estimator is derived with the help an auxiliary problem. An energy space based Dirichlet boundary control problem governed by bi-harmonic equation is investigated and subsequently a l y - interior penalty method is proposed and analyzed for it in the fourth chapter. An optimal order a priori error estimate is derived under the minimal regularity conditions. The abstract error estimate guarantees optimal order of convergence whenever the solution has minimum regularity. Further an optimal order l l norm error estimate is derived. The fifth chapter studies a super convergence result for the optimal control of an interior control problem with Dirichlet cost functional and governed by second order linear elliptic PDE. An optimal order a priori error estimate is derived and subsequently a super convergence result for the optimal control is derived. A residual based reliable and efficient error estimators are derived in a posteriori error control for the optimal control. Numerical experiments illustrate the theoretical results at the end of every chapter. We conclude the thesis stating the possible extensions which can be made of the results presented in the thesis with some more problems of future interest in this direction.

We study asymptotic properties of evolution partial differential equations posed in unbounded spatial domain in the context of locally uniform spaces. This context allows the use of non-integrable data and carries an inherent non-compactness and non-separability. We establish the existence of a lo- cally compact attractor for non-local parabolic equation and weakly damped semilinear wave equation and provide an upper bound on the Kolmogorov's ε-entropy of these attractors and the attractor of strongly damped wave equation in the subcritical case using the method of trajectories. Finally we also investigate infinite dimensional exponential attractors of nonlinear reaction-diffusion equation in its natural energy setting. 1

Ce mémoire présente une approche basée sur des méthodes garanties pour résoudre des problèmes d’optimisation de systèmes dynamiques multi-physiques. Ces systèmes trouvent des applications directes dans des domaines variés tels que la conception en ingéniérie, la modélisation de réactions chimiques, la simulation de systèmes biologiques ou la prédiction de la performance sportive.La résolution de ces problèmes d’optimisation s’effectue en deux phases. La première consiste à mettre le problème en équations sous forme d’un modèle mathématique constitué d’un ensemble de variables, d’un ensemble de contraintes algébriques et fonctionelles ainsi que de fonctions de coût. Celles-ci sont utilisées lors de la seconde phase qui consiste à d’extraire du modèle les solutions optimales selon plusieurs critères (volume, poids, etc).Les contraintes algébriques permettent de manipuler des grandeurs statiques (quantité, taille, densité, etc). Elles sont non linéaires, non convexes et parfois discontinues.Les contraintes fonctionnelles permettent de manipuler des grandeurs dynamiques. Ces contraintes peuvent être relativement simples comme la monotonie ou la périodicité, mais aussi bien plus complexe par la prise en compte de contraintes différentielles simples ou définies par morceaux. Les équations différentielles sont utilisées pour modéliser des comportements physico-chimiques (magnétiques, thermiques, etc) et d’autres caractéristiques qui varient lors de l’évolution du système.Il existe plusieurs niveaux d’approximation pour chacune de ces deux phases. Ces approximations donnent des résultats pertinents, mais elles ne permettent pas de garantir l’optimalité ni la réalisabilité des solutions.Après avoir présenté un ensemble de méthodes garanties permettant de résoudre de manière garantie des équations différentielles ordinaires, nous formalisons un modèle particulier de systèmes hybrides sous la forme d’équations différentielles ordinaires par morceaux. A l’aide de plusieurs preuves et théorèmes nous étendons la première méthode de résolution pour résoudre de manière garantie ces équations différentielles par morceaux. Dans un second temps, nous intégrons ces deux méthodes au sein d’un module de programmation par contracteurs, que nous avons implémenté. Ce module basé sur des méthodes garantie permet de résoudre des problèmes de satisfaction de contraintes algébriques et fonctionnelles. Ce module est finalement utilisé dans un algorithme d’optimisation globale déterministe modulaire permettant de résoudre les problèmes considérés. / In this thesis a set of tools based on guaranteed methods are presented in order to solve multi-physics dynamic problems. These systems can be applied in various domains such that engineering design process, model of chemical reactions, simulation of biological systems or even to predict athletic performances.The resolution of these optimization problems is made of two stages. The first one consists in defining a mathematical model by setting up the equations for the problem. The model is made of a set of variables, a set of algebraic and functional constraints and cost functions. The latter are used in the second stage in order to extract the optimal solutions from the model depending on several criteria (volume, weight, etc).Algebraic constraints are used to describe the static properties of the system (quantity, size, density, etc). They are non-linear, non-convex and sometimes discontinuous. Functional constraints are used to manipulate dynamic quantities. These constraints can be quite simple such as monotony or periodicity or they can be more complex such as simple or piecewise differential constraints. Differential equations are used to describe physico-chemical properties (magnetic, thermal, etc) and other features evolving with the component use. Several levels of approximation exist for each of these two stages. These approximations give some relevant results but they do not guarantee the feasibility nor the optimality of the solutions.After presenting a set of guaranteed methods in order to perform the guaranteed integration of ordinary differential equations, a peculiar type of hybrid system that can be modeled with piecewise ordinary differential equation is considered. A new method that computes guaranteed integration of these piecewise ordinary differential equations is developed through an extension of the initial algorithm based on several proofs and theorems. In a second step these algorithms are gathered within a contractor programming module that have been implemented. It is used to solve algebraic and functional constraint satisfaction problems with guaranteed methods. Finally, the considered optimization problems are solved with a modular deterministic global optimization algorithm that uses the previous modules.

>Magister Scientiae - MSc / We present various methods of pricing Asian options. The methods include Monte Carlo simulations designed using control and antithetic variates, numerical solution of partial differential equation and using lower bounds.The price of the Asian option is known to be a certain risk-neutral expectation. Using the Feynman-Kac theorem, we deduce that the problem of determining the expectation implies solving a linear parabolic partial differential equation. This partial differential equation does not admit explicit solutions due to the fact that the distribution of a sum of lognormal variables is not explicit. We then solve the partial differential equation numerically using finite difference and Monte Carlo methods.Our Monte Carlo approach is based on the pseudo random numbers and not deterministic sequence of numbers on which Quasi-Monte Carlo methods are designed. To make the Monte Carlo method more effective, two variance reduction techniques are discussed.Under the finite difference method, we consider explicit and the Crank-Nicholson’s schemes. We demonstrate that the explicit method gives rise to extraneous solutions because the stability conditions are difficult to satisfy. On the other hand, the Crank-Nicholson method is unconditionally stable and provides correct solutions. Finally, we apply the pricing methods to a similar problem of determining the price of a European-style arithmetic basket option under the Black-Scholes framework. We find the optimal lower bound, calculate it numerically and compare this with those obtained by the Monte Carlo and Moment Matching methods.Our presentation here includes some of the most recent advances on Asian options, and we contribute in particular by adding detail to the proofs and explanations. We also contribute some novel numerical methods. Most significantly, we include an original contribution on the use of very sharp lower bounds towards pricing European basket options.

On étudie une équation différentielle stochastique animée par un processus ponctuel de Poisson, qui modélise un changement continu de lénvironnement d'une population et la fixation stochastique de mutations bénéfiques pour compenser ce changement. La probabilité de fixation d'une mutation augmente dès que le retard phénotypique $X_t$ entre la population et l'optimum augmente. On suppose que les mutations favorables se fixent instantanément induisant un saut adaptatif. En premier lieu, on a étudié le comportement à long terme de la solution de cette équation sachant qu'on ne considère qu'un seul trait phénotypique de la population et on a trouvé les conditions sous lesquelles $X_t$ est récurrent (possibilité de survie) ou transient (extinction inévitable). Ensuite, on a généralisé nos résultats en considérant un vecteur de traits phénotypiques de la population, essentiellement dans $mathbb R^2$. A la fin, on introduit une limite des petits sauts pour caractériser et comprendre le cas récurrent. / We study a stochastic differential equation driven by a Poisson point process, which models continuous changes in a population's environment, as well as the stochastic fixation of beneficial mutations that might compensate for this change. The fixation probability of a given mutation increases as the phenotypic lag $X_t$ between the population and the optimum grows larger, and successful mutations are assumed to fix instantaneously (leading to an adaptive jump). First, we study the large time behavior of the solution of this SDE taking into consideration one phenotypic trait of the population and we find the conditions under which $X_t$ is recurrent (possibility of survival) or transient (doomed to exctinction).Then we generalize our results to the case of a phenotypic traits vector, essentially in $R^2$. Finally, we introduce a small jumps limit to characterize and understand the recurrent case.

Dans nos travaux, nous avons considéré un processus de Lévy X avec une composante brownienne non nulle et dont la partie à sauts est un processus de Poisson composé. Nous avons supposé que la valeur d'une entreprise est modélisée par un processus stochastique de la forme V = Vo exp X et que cette entreprise est mise à défaut dès lors que sa valeur passe sous un certain seuil b déterminé de façon exogène et qui donc, est une donnée du problème. L'instant de défaut T est alors de la forme Tx pour x= ln(Vo) ln((b) où x> 0, Tx = inf{t 2:0: X, 2:x}. Dans un premier temps, nous supposons que des agents observant la valeur V des ac­tifs de la firme souhaitent connaître le comportement de l'instant de défaut. Dans ce modèle, au chapitre 2, nous avons étudié d'une part la régularité de la densité de la loi de l'instant de défaut. D'autre part, nous avons étudié la loi conjointe de l'instant de défaut, de l'overshoot et de l'undershoot. Au chapitre 3, nous avons obtenu une équation à valeurs mesures dont le quadriplet formé par la variable aléatoire X,, le su­ premum du processus X à l'instant t, le supremum du processus X au dernier instant de saut avant l'instant t et le dernier instant de saut à l'instant t est solution au seris faible, puis une équation dont ce quadriplet est une solution forte. Dans un second temps, au chapitre 4, nous avons supposé que des investisseurs souhaitant détenir une part de cette entreprise ne disposent pas de l'information complète. Ils n'observent pas la valeur des actifs de la firme V, mais sa valeur bruitée. Leur information est modélisée par la filtration Ç = (Ç,, t 2: 0) engendrée par cette observation. Dans ce modèle, nous avons montré que la loi conditionnelle de l'instant de défaut sachant la tribu Ç, admet une densité par rapport à la mesure de Lebesgue et obtenu une équation de Volttera dont cette densité est solution. Cette connaissance permet aux investisseurs de prévoir au vu de leur information, quand est-ce que l'instant de défaut va intervenir après l'instant t. Nous avons complété ce travail par des simulations numériques. / In this Ph.D thesis, we consider a jump-diffusion process which the diffusion part is a drifted Brownian motion and the jump part is a compound Poisson process. We assume that a firm value is modelling by a stochastic process V = V0 exp-X. This firm goes to default whenever its value is below a specified tlrreshold b which is exo­ genously determined. For x = ln(Vo) - ln(b) > 0, the default time is of the form Tx = inf{t 2:0: X, 2: x}. First, we suppose that agents observe perfectly the firm value. In this mode, we sho­ wed in chapter 2 that the density of the default time is continuons, then study the joint law of the default time, overshoot an undershoot. We obtained in chapter 3 a valued measure differentia equation which the solution is the quadruplet formed by the random variable X,, the running supremum x; of X at time t, the supremum of X at the last jump time before t and the last jump time before t. Secondly, we assume that investors wishing detain a part of the firm can not observe the firm value. They observe a noisy value of the firm and their information is madel­ ling by the filtration g = (9,,t 2: 0) generated by their observation. In this mode, we have shown that the conditional density of Tx with respect to Ç has a density which is solution of one stochastic integral-differentia equation The knowledge of this density allows investors to predict the default time after time t. This second part is the chapter 4.

Orientador: Vanderlei Minori Horita / Banca: Isabel Lugão Rios / Banca: Claudio Aguinaldo Buzzi / Resumo: Neste trabalho vamos estudar equações diferenciais ordinárias e analisar seu comportamento ao longo de suas trajetórias, com o principal objetivo de encontar, caso possível, uma função de Lyapunov apropriada para o sistema, isto é, dar condição suficiente e necessária para a existência dessa função. / Abstract: In this work we study ordinary differential equations and analyse the behavior along of trajectories. The main goal is to find Lyapunov functions for the system when possibel: i e, we want to find necessary and sufficient conditions for the existence of those. / Mestre

Avanços recentes nos conhecimentos sobre a infecção viral e AIDS tem levado pacientes soropositivos a uma melhor qualidade de vida. A determinação de quais populações celulares ou qual mecanismo imunológico seja mais relevante para instalação da epidemia conduz a novos patamares de possibilidades de novas drogas antiretrovirais e tratamento mais eficientes. O uso de modelagem matemática, para a epidemiologia, correlaciona indivíduos (neste caso células) e doença (o vírus) através de equações diferenciais, onde se quer observar as condições necessárias para a instalação ou não da doença. Neste trabalho, observou-se através das simulações, que o componente mais importante, depois do linfócito TCD4+, é a célula macrófago (por ser um reservatório de proliferação viral), que a infecção ocorre várias vezes ao longo do tempo (devido o processo de apresentação de antígenos) e que os linfócitos CTL são ineficientes em erradicar a infecção pelo vírus HIV-1, que pode ser um simples fenômeno de co-adaptação. / Recent advances in knowledge about the viral infection and AIDS seropositive patients has led to a better life quality. The determination of what people or cellular immune mechanism which is more relevant for the epidemic installation leads to new levels of possibilities to new antiretroviral drugs discovers and more efficient treatment. Mathematical modeling use on epidemiology, correlates individuals (this case cells) and illness (the virus) through differential equations, where want to observe the conditions necessary to the installation or not the disease. In this study, it was observed through simulations, that the most important component, after lymphocyte CD4 T cells, macrophages is the cell (as a reservoir of viral proliferation) that the infection occurs repeatedly over time (because of the antigen presenting process) and CTL lymphocytes are inefficient in eradicating the infection by HIV-1, which may be a simple phenomenon of co-adaptation.

Este trabalho apresenta um estudo qualitativo das equações diferenciais nãolineares que descrevem o sincronismo de fase nos PLLs de 3ª ordem que compõem redes OWMS de topologia mista, Estrela Simples e Cadeia Simples. O objetivo é determinar, através da Teoria de Bifurcações, os valores ou relações entre os parâmetros constitutivos da rede que permitam a existência e a estabilidade do estado síncrono, quando são aplicadas, no oscilador mestre, duas funções de excitação muito comuns na prática: o degrau e a rampa de fase. Na determinação da estabilidade dos pontos de equilíbrio, sob o ponto de vista de Lyapunov, a existência de pontos de equilíbrio não-hiperbólicos não permite uma aproximação linear e, nesses casos, é aplicado o Teorema da Variedade Central. Essa técnica de simplificação de sistemas dinâmicos permite fazer uma aproximação homeomórfica em torno desses pontos, preservando a orientação no espaço de fases e possibilitando determinar localmente suas estabilidades. / This work presents a qualitative study of the non-linear differential equations that describe the synchronous state in 3rd order PLLs that compose One-way masterslave time distribution networks with Single Star and Single Chain topologies. Using bifurcation theory, the dynamical behavior of third-order phase-locked loops employed to extract the syncronous state in each node is analyzed depending on constitutive node parameters when two usual inputs, the step and the ramp phase pertubations, are supposed to appear in the master node. When parameter combinations result in non hyperbolic synchronous states, from Lyapunov point of view, the linear approximation does not provide any information about the local behavior of the system. In this case, the center manifold theorem permits the construction of an equivalent vector field representing the asymptotic behavior of the original system in the neighborhood of these points. Thus, the local stability can be determined.

Reatores tubulares de polimerização podem apresentar um perfil de velocidade bastante distorcido. Partindo desta observação, um modelo estocástico baseado no modelo de dispersão axial foi proposto para a representação matemática da fluidodinâmica de um reator tubular para produção de poliestireno. A equação diferencial foi obtida inserindo a aleatoriedade no parâmetro de dispersão, resultando na adição de um termo estocástico ao modelo capaz de simular as oscilações observadas experimentalmente. A equação diferencial estocástica foi discretizada e resolvida pelo método Euler-Maruyama de forma satisfatória. Uma função estimadora foi desenvolvida para a obtenção do parâmetro do termo estocástico e o parâmetro do termo determinístico foi calculado pelo método dos mínimos quadrados. Uma análise de convergência foi conduzida para determinar o número de elementos da discretização e o modelo foi validado através da comparação de trajetórias e de intervalos de confiança computacionais com dados experimentais. O resultado obtido foi satisfatório, o que auxilia na compreensão do comportamento fluidodinâmico complexo do reator estudado. / The velocity profile of polymerization tubular reactors may be very distorted. Based on this observation, a stochastic model based on the axial dispersion model was proposed for the mathematical representation of the fluid dynamics of a tubular reactor for polystyrene production. The differential equation was built by inserting randomness in the dipersion coefficient, which added a stochastic term to the model. This term was capable of simulating the experimentally observed fluctuations. The stochastic differential equation was discretized and solved by the Euler-Maruyama method adequately. An estimator function has been developed to calculate the parameter of the stochastic term, while the parameter of the deterministic term was estimated by a least squares method. A convergence analysis was carried out in order to determine the number of elements needed for the time discretization. The model was validated through comparisons of sample paths and computational confidence intervals with experimental data. The result was considered satisfactory, allowing a better understanding of the complex fluid dynamic behaviour of the analised reactor. Key-words: modelling, simulation, stochastic differential equation, polymerization tubular reactor, time residence distribution.