Submitted by Maria Cristina (library@lncc.br) on 2018-06-27T12:31:36Z No. of bitstreams: 1 Dissertacao_final_Fortia.pdf: 758629 bytes, checksum: 6b31d1df1ed8f464b298cce7e1ee4180 (MD5) / Approved for entry into archive by Maria Cristina (library@lncc.br) on 2018-06-27T12:31:54Z (GMT) No. of bitstreams: 1 Dissertacao_final_Fortia.pdf: 758629 bytes, checksum: 6b31d1df1ed8f464b298cce7e1ee4180 (MD5) / Made available in DSpace on 2018-06-27T12:32:06Z (GMT). No. of bitstreams: 1 Dissertacao_final_Fortia.pdf: 758629 bytes, checksum: 6b31d1df1ed8f464b298cce7e1ee4180 (MD5) Previous issue date: 2017-02-24 / Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ) / Stochastic differential equations with Markovian jump parameters constitute one of the most important class of hybrid dynamical systems, which has been extensively used for the modeling of dynamical systems which are subject to abrupt changes in their structure. The abrupt changes can be due, for instance, to abrupt environmental disturbances, component failure, volatility in economic systems, changes in subsystems interconnections, abrupt changes in the operation of a nonlinear plant, etc. This can be found, for instance, in aircraft control systems, robot systems, large flexible structure for space station, etc. We shall be particularly interested in the linear class which is dubbed in the literature as the class of Markov jump linear systems (MJLS). The jump mechanism is modeled by a Markov process, which is also known in the literature as the operation mode. The dissertation address the filtering problem of the operation mode for the class of MJLS. Previous result in the literature on this problem has been obtained by Wonham, which has shown the existence of an optimal nonlinear filter for this problem. The main hindrance with Wonham’s result, in the context of the control problem with partial observation of operation mode, is that it introduces a great deal of nonlinearity in the Hamilton-Jacobi- Belman equation, which makes it difficult to get an explicit closed solution for the control problem. Motivated by this, the main contribution of this dissertation is to devise an optimal linear filter for the mode operation, which we believe could be more favorable in the solution of the control problem with partial observations. In addition, relying on Murayama’s stochastic numerical method and the results of Yuan and Mao, we carry out simulation of Wonham’s filter, and the one devised in the dissertation, in order to compare their performances. / As equações diferenciais estocáticas com salto Markoviano constituem uma das clases de sistemas dinâmicos híbridos mais importantes, e tem sido muito usados para modelar sistemas sujeitos a mudanças abruptas na sua estructura. Essas mudanças podem ser devido a, por exemplo, perturbações ambientais, falhas em componentes, volatilidade em sistemas econômicos, mudanças em interconexões de subsistemas, mudanças abruptas em operações de plantas não lineares, etc. Estas falhas podem ser encontradas em sistemas de controle para aeronaves, sistemas robóticos, estructuras grandes e flexíveis em estações espaciais, etc. Nós estamos especialmente interessados na clase de sistemas lineares que é referenciada na literatura como sistemas lineares com salto Markoviano (SLSM). O mecanismo de salto é modelado por um processo de Markov, que é conhecido na literatura como modo de operação do sistema. Essa dissertação visa o problema de filtragem para o modo de operação do sistema linear com salto. Na literatura pode-se encontrar resultados já obtidos para esse problema como é o caso do filtro ótimo não linear deduzido por Wonham. Mas no contexto de controle ótimo com observações parciais do modo de operação, o filtro de Wonham introduz não linearidades na equação de Hamilton-Jacobi-Belman, fazendo com que seja muito complexo obter uma solução fechada para o problema de controle. A principal motivação desta dissertação é deduzir o filtro ótimo linear para o modo de operação, já que esta pode ser uma solução mais favorável para o problema de controle ótimo. Finalmente, usando o método numérico para equações diferenciais estocásticas de Euler-Murayama e o resultado de Yuan e Mao, realizamos a simulação do filtro de Wonham tal como o filtro deduzido neste trabalho, com o objetivo de comparar as respectivas performances.

Dažnai realių stochastinių sistemų negalime aprašyti Markovo procesais, nes operacijų trukmės nėra pasiskirstę pagal eksponentinį dėsnį. Šiame darbe nagrinėjome sistemų aproksimavimo galimybes, taikant eksponentinių skirstinių mišinius ir sąsūkas. Skirstinių aproksimavimui taikėme Erlango mišinius ir Kokso skirstinį. Skirstinių aproksimavimą pritaikėme aptarnavimo sistemų M/G/1 ir G/M/1 tyrimui. Atlikti teoriniai skaičiavimai parodė, kad gaunamas aukštas aproksimavimo tikslumas. Aptarnavimo sistemų modeliavimui naudojome skaitmeninio Markovo procesų modeliavimo sistemą naudojant įvykių kalbą. Darbe sukurti metodai leidžia tiksliai apskaičiuoti sistemų charakteristikas, naudojant aproksimavimą eksponentiniais mišiniais ir sąsūkomis. Sukurta programinė įranga leidžia automatizuoti sistemų M/G/1 ir G/M/1 modeliavimą, naudojant aproksimavimą eksponentiniais mišiniais. Sistemos G/G/1 ( neištiriamos analiziniais metodais ) aproksimavimo rezultatai leidžia tikėtis, kad šiame darbe nagrinėjamas metodas gali būti naudojamas ir sudėtingų sistemų modeliavime. / Application of numerical methods with approximation allows to extend a class of systems represented by Markovian processes under investigation compared with analytical methods. In this paper we used approximation of positive distribution functions, using phase-type distributions: mixtures of Erlang distributions and Coxian distribution – both 2 and 3 moments-matching algorithms was used. Analysis of M/G/1 and G/M/1 queueing systems showed, that moment-based queueing approximation gives high accuracy. In purpose to compute characteristics of M/G/1 and G/M/1 systems described in an event-based language, algorithms and software was created. Comparison to simulation results shows, that event-based language enables to get more precise results. Analysis of G/G/1 systems showed, that moment-based approximation can be used to analyse difficult queueing systems.

Markovo proceso tikimybinio mato absoliutaus tolydumo nesudėtingos sąlygos leidžia gauti atitinkamų statistinių eksperimentų tikėtinumo santykio pavidalą, kurio asimptotinės savybės susijusios su dviejų paprastų hipotezių asimptotiniais atskyrimo uždaviniais, kai yra taikomas maksimalaus tikėtinumo arba minimakso kriterijus. Tų paprastų hipotezių asimptotinis atskyrimas yra charakterizuojamas 1-os ir 2-os rūšies klaidos tikimybėmis, kurių asimptotinis elgesys priklausomai nuo optimalaus statistinio kriterijaus parinkimo užsirašo dvejomis formulėmis. Maksimalaus kriterijaus atveju tokia formulė buvo gauta bendriausiu atveju, tik nebuvo pritaikyta Markovo procesui su dideliu būsenų skaičiumi. Šiame darbe kaip tik parodyti šie taikymai. Taikant maksimalaus tikėtinumo kriterijų (Neimono-Pirsono) atitinkamas rezultatas buvo gautas tik tuo atveju, kai stebėjimai yra nepriklausomi ir vienodai pasiskirstę. Analogiškas rezultatas gautas bendriausiu atveju – gautos sąlygos, kada galioja atitinkama asimptotinė formulė. Kartu, pavyzdžiuose yra parodyti šios asimptotinės formulės taikymai, kai stebimas Markovo procesas su dideliu būsenų skaičiumi. / Absolute continuity simple conditions of probabilistic measure of Markov process allows you to get relevand statistical experiments likelihood ratio form, which asymptotic properties is associated with the asymptotic separation of the two simple hypotheses tasks, when is applied maximum likelihood (Neiman-Pirson) or minimax criterion. That asymptotic separation of the two simple hypothesis is characterized by type I and type II errors of probability, which asymptotic behavior depending on the optimal statistical criterion selection note down by two formulas. In maximum likelihood criterion case, formula was obtained on a very general case, not only been applied of the Markov process with a large number of states. These applications are shown at this work. Using maximum likelihood criterion (Neiman-Pirson) corresponding result was obtained only in that case, when observations are independent and identically distributed. Analogous result were obtained on a very general case – from conditions, when is valid the asymptotic formula. In examples of this work are shown that asymptotic formula applications, when is observed Markov process with a large number of states.

<p>We consider stochastic hybrid systems that stem from evolution equations with right-hand sides that stochastically switch between a given set of right-hand sides. To begin our study, we consider a linear ordinary differential equation whose right-hand side stochastically switches between a collection of different matrices. Despite its apparent simplicity, we prove that this system can exhibit surprising behavior.</p><p>Next, we construct mathematical machinery for analyzing general stochastic hybrid systems. This machinery combines techniques from various fields of mathematics to prove convergence to a steady state distribution and to analyze its structure.</p><p>Finally, we apply the tools from our general framework to partial differential equations with randomly switching boundary conditions. There, we see that these tools yield explicit formulae for statistics of the process and make seemingly intractable problems amenable to analysis.</p> / Dissertation

We present a model of coupled transcriptional-translational ultradian oscillators (TTOs) as a possible mechanism for the circadian rhythm observed at the cellular level. It includes nonstationary Poisson interactions between the transcriptional proteins and their affined gene sites. The associated reaction-rate equations are nonlinear ordinary differential equations of stochastic switching type. We compute the deterministic limit of this system, or the limit as the number of gene-proteins interactions per unit of time becomes large. In this limit, the random variables of the model are simply replaced by their limiting expected value. We derive the Kolmogorov equations — a set of partial differential equations —, and we obtain the associated moment equations for a simple instance of the model. In the stationary case, the Kolmogorov equations are linear and the moment equations are a closed set of equations. In the nonstationary case, the Kolmogorov equations are nonlinear and the moment equations are an open-ended set of equations. In both cases, the deterministic limit of the moment equations is in agreement with the deterministic state equations.

We present a model of coupled transcriptional-translational ultradian oscillators (TTOs) as a possible mechanism for the circadian rhythm observed at the cellular level. It includes nonstationary Poisson interactions between the transcriptional proteins and their affined gene sites. The associated reaction-rate equations are nonlinear ordinary differential equations of stochastic switching type. We compute the deterministic limit of this system, or the limit as the number of gene-proteins interactions per unit of time becomes large. In this limit, the random variables of the model are simply replaced by their limiting expected value. We derive the Kolmogorov equations — a set of partial differential equations —, and we obtain the associated moment equations for a simple instance of the model. In the stationary case, the Kolmogorov equations are linear and the moment equations are a closed set of equations. In the nonstationary case, the Kolmogorov equations are nonlinear and the moment equations are an open-ended set of equations. In both cases, the deterministic limit of the moment equations is in agreement with the deterministic state equations.

This research investigates existing relationships between the three apparently unrelated subjects: Markov process, Semigroups and Partial difierential equations. Markov processes define semigroups through their transition functions. Conversely particular semigroups determine transition functions and can be regarded as Markov processes. We have exploited these relationships to study some Markov chains. The infnitesimal generator of a Feller semigroup on the closure of a bounded domain of Rn; (n ^ 2), is an integro-diferential operator in the interior of the domain and verifes a boundary condition. The existence of a Feller semigroup defined by a diferential operator and a boundary condition is due to the existence of solution of a bounded value problem. From this result other existence suficient conditions on the existence of Feller semigroups have been obtained and we have applied some of them to construct Feller semigroups on the unity disk of R2. / Decision Sciences / M. Sc. (Operations Research)

In this monograph we continue with the inspection initiated in [1] on the fundamental tools introduced in the approach proposed in [2,3] for the study of metastability. We give the definition of the Poisson random measures and prove the main properties that we will subsequently use to construct Markov processes with finite state space. Such construction will allow us to provide a probabilistic proof of the fact that the law of a Markov process solves the martingal problem. / En esta monografía continuamos con el desarrollo iniciado en [1] sobre las herramientas fundamentales usadas en el abordaje propuesto en [2,3] para el estudio de la metaestabilidad. Definimos las medidas aleatorias de Poisson y probamos las principales propiedades que seran usadas para construir procesos de Markov con espacio de estados finito. Esta forma de abordar la propiedad Markoviana nos permitirá dar una demostración probabilística de que la ley de un proceso de Markov resuelve un problema martingala.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / The Brazilian agricultural sector has made in the period of stabilization after the Real Plan (1996-2009) a satisfactory economic dynamics, in which the level of agricultural products began an upward trend and virtually uninterrupted growth. This performance suggests that state economies are undergoing a process of catching up, which in the long run there would be a tendency for poorer economies achieve the same level of economic growth (in terms of per capita agricultural GDP) of the richest economies, setting a process of convergence to steady state. Accordingly, this paper seeks to analyze the convergence of per capita agricultural income between the states of Brazil, making sure that the dynamics of the agricultural sector had contributed to the reduction of inequalities existing interstate. To this end, it was used the first-order Markov process. The results indicate the occurrence of movements backward economies to levels of income per capita agricultural lower, indicating that the economies under review showed a trend of impoverishment, despite the global economic growth presented by the sector over the period. Among the factors that led these economies to tread a path of impoverishment, one can cite the emphasis of public policy to export crops, not covered by all the federating units of the country, which would result in the strengthening of the state economies have developed, expense of which are under development; beyond the migration of manpower for the agricultural production centers in more developed agricultural, causing the "Red Queen Effect," in which the growth of agricultural GDP does not translate into growth of income per capita in the field. However, the focus of this study is to identify the occurrence of convergence / divergence, no inferences about the causes that led to the initiation of such a movement, since these factors make room for new studies that seek to investigate them, in order to provide tools for the formulation of agricultural policies aimed at minimizing or even reversal of the causes that lead to poverty in the countryside. / O setor agropecuÃrio brasileiro tem apresentado no perÃodo de pÃs estabilizaÃÃo do Plano Real (1996-2009) uma dinÃmica econÃmica satisfatÃria, em que o nÃvel de produto agropecuÃrio iniciou uma trajetÃria ascendente e praticamente ininterrupta de crescimento. Tal performance sugere que as economias estaduais estejam passando por um processo de catching up, em que no longo prazo existiria uma tendÃncia das economias mais pobres alcanÃarem o mesmo nÃvel de crescimento econÃmico (em termos de PIB per capita agropecuÃrio) das economias mais ricas, configurando um processo de convergÃncia no steady state. Eom efeito, este, trabalho busca analisar a convergÃncia da renda agropecuÃria per capita entre os estados do Brasil, verificando se a dinÃmica do setor agrÃcola teria contribuÃdo para a reduÃÃo das desigualdades interestaduais preexistentes. Para tal, fez-se uso do processo markoviano de primeira ordem. Os resultados apontaram a ocorrÃncia de movimentos de retrocesso das economias para nÃveis de renda per capita agropecuÃria inferiores, indicando que as economias em anÃlise apresentaram uma tendÃncia de empobrecimento, apesar do crescimento econÃmico global do setor ao longo do perÃodo. Dentre os fatores que levariam tais economias a trilharem uma trajetÃria de empobrecimento, pode-se citar a Ãnfase das polÃticas pÃblicas Ãs culturas de exportaÃÃo, nÃo contempladas por todas as unidades federativas do PaÃs, o que resultaria no fortalecimento das economias estaduais jà desenvolvidas, em detrimento das que se encontram em desenvolvimento; alÃm dos movimentos migratÃrios da mÃo-de-obra agropecuÃria para os centros produtores agrÃcolas mais desenvolvidos, causando o âEfeito Rainha Vermelhaâ, em que o crescimento do PIB agropecuÃrio nÃo se traduziria em crescimento das rendas per capita no campo. Contudo, o foco deste estudo consiste na identificaÃÃo da ocorrÃncia do processo de convergÃncia/divergÃncia, sem inferir sobre as causas que levariam ao desencadeamento de tal movimento, jà que tais fatores abrem espaÃo para novos estudos que busquem investigÃ-los, a fim de poder fornecer instrumentos de formulaÃÃo de polÃticas pÃblicas agropecuÃrias direcionadas à minimizaÃÃo ou mesmo reversÃo das causas que levam à pobreza no campo.

Esta tese trata do problema de controle ótimo estocástico de sistemas com saltos Markovianos e ruído multiplicativo a tempo discreto, com horizontes de tempo finito e infinito. A função custo é composta de termos quadráticos e lineares nas variáveis de estado e de controle, com matrizes peso indefinidas. Como resultado principal do problema com horizonte finito, é apresentada uma condição necessária e suficiente para que o problema de controle seja bem posto, a partir da qual uma solução ótima é derivada. A condição e a lei de controle são escritas em termos de um conjunto acoplado de equações de Riccati interconectadas a um conjunto acoplado de equações lineares recursivas. Para o caso de horizonte infinito, são apresentadas as soluções ótimas para os problemas de custo médio a longo prazo e com desconto, derivadas a partir de uma solução estabilizante de um conjunto de equações algébricas de Riccati acopladas generalizadas (GCARE). A existência da solução estabilizante é uma condição suficiente para que tais problemas sejam do tipo bem posto. Além disso, são apresentadas condições para a existência das soluções maximal e estabilizante do sistema GCARE. Como aplicações dos resultados obtidos, são apresentadas as soluções de um problema de otimização de carteiras de investimento com benchmark e de um problema de gestão de ativos e passivos de fundos de pensão do tipo benefício definido, ambos os casos com mudanças de regime nas variáreis de mercado. / This thesis considers the finite-horizon and infinite-horizon stochastic optimal control problem for discrete-time Markov jump with multiplicative noise linear systems. The performance criterion is assumed to be formed by a linear combination of a quadratic part and a linear part in the state and control variables. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. For the finite-horizon problem the main results consist of deriving a necessary and sufficient condition under which the problem is well posed and a optimal control law is derived. This condition and the optimal control law are written in terms of a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. For the infinite-horizon problem a set of generalized coupled algebraic Riccati equations (GCARE) is studied. In this case, a sufficient condition under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution for the GCARE are presented. Moreover, a solution for the discounted and long run average cost problems is presented. The results obtained are applied to solver a portfolio optimization problem with benchmark and a pension fund problem with regime switching.