Um problema-chave envolvendo processos químicos industriais é controlar, de forma confiável, eficiente e barata, a evolução dinâmica do sistema. Numa coluna de destilação, por exemplo, o objetivo do controle é manter a composição do destilado e do produto de fundo em torno de um valor desejado. As dificuldades operacionais e o alto custo dos analisadores industriais, existentes no mercado, usados na medição da composição têm motivado o projeto de sensores virtuais (soft sensors) para que, a partir de outras medições disponíveis, seja possível inferir de maneira online os valores das variáveis desejadas. Por outro lado, as redes neurais artificiais têm sido utilizadas em diversas aplicações práticas de engenharia, sendo possível usá-las para resolver problemas industriais complexos. Elas possuem diversas características que as fazem particularmente atrativas em aplicações envolvendo sistemas multivariáveis não lineares. Nesse trabalho, um estimador dinâmico virtual baseado em redes neurais é usado para inferir a composição de etanol destilado com base na temperatura e na pressão no interior da coluna, além das vazões de refluxo, do vapor no refervedor e da alimentação. Os resultados desse estudo poderão ser utilizados no desenvolvimento de futuros projetos envolvendo sensores virtuais aplicados ao controle e à otimização de processos industriais. / A key problem involving industrial chemical processes is to control the dynamic evolution of the system in a reliable, efficient and low cost way. In a distillation column, for example, the control objective is to keep the composition of both distillate and bottom product around a desired value. The operational difficulties and high cost of concentration analyzers, used for measuring the composition, have motivated the design of virtual sensors (soft sensors). They are used, in an online way, to infer the values of the desired variables from other available measurements. On the other hand, artificial neural networks have been used for solving many practical engineering applications involving complex industrial problems. They have several features, making them particularly attractive to applications involving nonlinear multivariable systems. In this work, a virtual estimator based on a dynamic neural network is used to infer the composition of distilled ethanol. Temperature and pressure within the column, and the flows of steam and reflux are used as inputs for the neural network. The results of this study can be used to develop future projects involving virtual sensors applied in control and optimization of industrial processes.

In this work we study rate of convergence of attractors for parabolic equations. We consider various types of problems where the diffusion coefficient has varied profiles: large diffusion, localized large diffusion and large diffusion except in the neighborhood of a point where it becomes small. In all cases we obtain a singular perturbation where a rate of convergence of attractors is obtained. / Neste trabalho estudamos taxa de convergência de atratores para equações parabólicas. Consideramos vários tipos de problemas onde o coeficiente de difusão apresenta perfís variados: difusão grande, difusão grande localizada e difusão grande exceto na vizinhança de um ponto onde ela torna-se pequena. Em todos os casos consideramos perturbações singulares e uma taxa de convergência para os atratores é obtida.

Um problema-chave envolvendo processos químicos industriais é controlar, de forma confiável, eficiente e barata, a evolução dinâmica do sistema. Numa coluna de destilação, por exemplo, o objetivo do controle é manter a composição do destilado e do produto de fundo em torno de um valor desejado. As dificuldades operacionais e o alto custo dos analisadores industriais, existentes no mercado, usados na medição da composição têm motivado o projeto de sensores virtuais (soft sensors) para que, a partir de outras medições disponíveis, seja possível inferir de maneira online os valores das variáveis desejadas. Por outro lado, as redes neurais artificiais têm sido utilizadas em diversas aplicações práticas de engenharia, sendo possível usá-las para resolver problemas industriais complexos. Elas possuem diversas características que as fazem particularmente atrativas em aplicações envolvendo sistemas multivariáveis não lineares. Nesse trabalho, um estimador dinâmico virtual baseado em redes neurais é usado para inferir a composição de etanol destilado com base na temperatura e na pressão no interior da coluna, além das vazões de refluxo, do vapor no refervedor e da alimentação. Os resultados desse estudo poderão ser utilizados no desenvolvimento de futuros projetos envolvendo sensores virtuais aplicados ao controle e à otimização de processos industriais. / A key problem involving industrial chemical processes is to control the dynamic evolution of the system in a reliable, efficient and low cost way. In a distillation column, for example, the control objective is to keep the composition of both distillate and bottom product around a desired value. The operational difficulties and high cost of concentration analyzers, used for measuring the composition, have motivated the design of virtual sensors (soft sensors). They are used, in an online way, to infer the values of the desired variables from other available measurements. On the other hand, artificial neural networks have been used for solving many practical engineering applications involving complex industrial problems. They have several features, making them particularly attractive to applications involving nonlinear multivariable systems. In this work, a virtual estimator based on a dynamic neural network is used to infer the composition of distilled ethanol. Temperature and pressure within the column, and the flows of steam and reflux are used as inputs for the neural network. The results of this study can be used to develop future projects involving virtual sensors applied in control and optimization of industrial processes.

In this work we study rate of convergence of attractors for parabolic equations. We consider various types of problems where the diffusion coefficient has varied profiles: large diffusion, localized large diffusion and large diffusion except in the neighborhood of a point where it becomes small. In all cases we obtain a singular perturbation where a rate of convergence of attractors is obtained. / Neste trabalho estudamos taxa de convergência de atratores para equações parabólicas. Consideramos vários tipos de problemas onde o coeficiente de difusão apresenta perfís variados: difusão grande, difusão grande localizada e difusão grande exceto na vizinhança de um ponto onde ela torna-se pequena. Em todos os casos consideramos perturbações singulares e uma taxa de convergência para os atratores é obtida.

La dynamique des écoulements géophysiques planétaires est fortement influencée par des processus physiques souvent non résolus par les modèles numériques de circulation générale. Il est essentiel de comprendre les mécanismes physiques sous-jacents pour paramétrer l’effet des petites échelles sur les grandes. Dans cette thèse, nous étudions un problème emblématique d’interactions entre ondes et écoulements moyens : la dynamique des écoulements zonaux forces par des ondes internes de gravite. Une manifestation remarquable de ces interactions est l’oscillation quasi-biennale (QBO) des vents équatoriaux dans l’atmosphère terrestre. Dans un premier temps, nous décrivons une transition vers le chaos dans un modèle quasi-linéaire classique du QBO. Nous montrons que ces bifurcations persistent dans des simulations numériques directes. A l’aune de ces résultats, nous proposons une interprétation de l’observation d’une rupture inattendue de la périodicité du QBO en 2016. Le mécanisme de génération d’écoulements moyens par les ondes dans les fluides stratifies nécessite la prise en compte d’effets dissipatifs. Il s’agit d’un phénomène analogue au "streaming" acoustique. Dans un second temps nous exploitons cette analogie en étudiant la génération d’écoulements moyens par les ondes internes proche d’une paroi, a l’aide d’approches asymptotiques multi échelles. Finalement, nous proposons une approche inertielle pour décrire l’émergence spontanée d’écoulements vorticaux en présence d’ondes : nous appliquons les outils de mécanique statistique pour calculer la partition d’énergie entre petites et grandes échelles dans le modèle d’eau peu profonde. / The dynamics of planetary-scale geophysical flows is strongly influenced by physicalprocesses, mostly unresolved by general circulation numerical models. To parametrisethe coupling between small and large scales, it is essential to understand the underlying physical mechanisms. In this thesis, we study an emblematic problem of interactions between waves and mean flows: the dynamics of zonal flows forced by internal gravity waves. A striking manifestation of these interactions is the quasi-biennial oscillation (QBO) of equatorial winds in the Earth’s atmosphere. First, we describe a transition to chaos in a classical quasilinear model of the QBO and show that these bifurcations persist in direct numerical simulations. Based on these results, we suggest an interpretation for the observation of the unexpected periodicity disruption of the QBO in 2016. The mechanism by which mean flows are generated by waves in stratified fluids requires the consideration of dissipative effects. This phenomenon is analogous to acoustic "streaming". In a second time, we exploit this analogy to study the generation of mean flows by internal gravity waves close to a wall, using multi-scale asymptotic approaches. Finally, we propose an inertial approach to describe the spontaneous emergence of vortical flows in the presence of waves: we apply the tools of statistical mechanics to calculate the partition of energy between small and large scales in the shallow-water model.

In light of the complex and highly uncertain nature of dynamical systems requiring controls, it is not surprising that reliable system models for many high performance engineering and life science applications are unavailable. In the face of such high levels of system uncertainty, robust controllers may unnecessarily sacrifice system performance whereas adaptive controllers are clearly appropriate since they can tolerate far greater system uncertainty levels to improve system performance. In this dissertation, we develop a Lyapunov-based direct adaptive and neural adaptive control framework that addresses parametric uncertainty, unstructured uncertainty, disturbance rejection, amplitude and rate saturation constraints, and digital implementation issues. Specifically, we consider the following research topics: direct adaptive control for nonlinear uncertain systems with exogenous disturbances; robust adaptive control for nonlinear uncertain systems; adaptive control for nonlinear uncertain systems with actuator amplitude and rate saturation constraints; adaptive reduced-order dynamic compensation for nonlinear uncertain systems; direct adaptive control for nonlinear matrix second-order dynamical systems with state-dependent uncertainty; adaptive control for nonnegative and compartmental dynamical systems with applications to general anesthesia; direct adaptive control of nonnegative and compartmental dynamical systems with time delay; adaptive control for nonlinear nonnegative and compartmental dynamical systems with applications to clinical pharmacology; neural network adaptive control for nonlinear nonnegative dynamical systems; passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems; neural network adaptive dynamic output feedback control for nonlinear nonnegative systems using tapped delay memory units; Lyapunov-based adaptive control framework for discrete-time nonlinear systems with exogenous disturbances; direct discrete-time adaptive control with guaranteed parameter error convergence; and hybrid adaptive control for nonlinear uncertain impulsive dynamical systems.

Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2015-01-30T10:49:22Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação_Eduardo Koiti Hirota - 2014.pdf: 894506 bytes, checksum: 39a1f1c9a2e91954ecfdd1ef0513c5c0 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2015-01-30T13:05:19Z (GMT) No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação_Eduardo Koiti Hirota - 2014.pdf: 894506 bytes, checksum: 39a1f1c9a2e91954ecfdd1ef0513c5c0 (MD5) / Made available in DSpace on 2015-01-30T13:05:19Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Dissertação_Eduardo Koiti Hirota - 2014.pdf: 894506 bytes, checksum: 39a1f1c9a2e91954ecfdd1ef0513c5c0 (MD5) Previous issue date: 2014-10-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Phenomenon that occur in the nature are essentially nonlinear and the dynamical systems theory aims to obtain a mathematical model that best represents the real physical systems, then nothing more coherent than the description or analysis of these natural phenomenon using models and techniques. In this dissertation, the technique of direct expansion for the development of two differential equations order to solve a nonlinear equation and the approximate determination of the roots of order algebraic equation higher or equal to two, was used. For this purpose, it was initially shown the development of a differential equation of motion subjected to a nonlinear damping, which is represented by the equation of Duffing – Van der Pol. Generally, it’s not easy to obtain an approximated analytical solution for this type equation, but this study was done with the purpouse of illustrating the technique used in the work, solving type solving a problem in which these techniques are routinely used to obtain a solution. Studied for application in basic education, it presents a way to obtain the approximate roots of equations of second and third degrees, using the technique of direct expansion for the sake of comparison. Since there are formulas for resolving this, It was proved that is possible to determine the roots of high-order equations by using the same technique. / Os fenômenos que ocorrem na natureza são essencialmente não lineares e a teoria de sistemas dinâmicos tem como objetivo obter um modelo matemático que represente melhor os sistemas físicos reais, então nada mais coerentes que a descrição ou análise desses fenômenos naturais usando modelos e técnicas não lineares. Nesta dissertação, foi utilizada a técnica da expansão direta para o desenvolvimento de equações diferenciais de ordem dois para resolução de uma equação não linear e na determinação aproximada de raízes de equações algébricas de ordem maior ou igual a dois. Com esse intuito, mostrou-se, inicialmente, o desenvolvimento de uma equação diferencial do movimento sujeito a um amortecimento não linear, que é representado pela equação de Duffing – Van der Pol. Geralmente, não é fácil obter uma solução analítica aproximada para esse tipo de equação, porém, este estudo é feito com a finalidade de ilustrar a técnica empregada no trabalho, resolvendo um tipo de problema no qual essas técnicas são corriqueiramente utilizadas para obter uma solução. Visando a aplicabilidade no ensino básico, apresenta-se uma forma de se obter as raízes aproximadas de equações do segundo e terceiro graus usando a técnica da expansão direta para efeito de comparação uma vez que existem fórmulas resolutivas para isso, provouse que é possível determinar as raízes de equações de ordem maior por meio da mesma técnica.

Le fonctionnement d'un neurone, unité fondamentale du système nerveux, intéresse de nombreuses disciplines scientifiques. Il existe ainsi des modèles mathématiques qui décrivent leur comportement par des systèmes d'EDO ou d'EDP. Plusieurs de ces modèles peuvent ensuite être couplés afin de pouvoir étudier le comportement de réseaux, systèmes complexes au sein desquels émergent des propriétés. Ce travail présente, dans un premier temps, les principaux mécanismes régissant ce fonctionnement pour en comprendre la modélisation. Plusieurs modèles sont alors présentés, jusqu'à celui de FitzHugh-Nagumo (FHN), qui présente une dynamique très intéressante.C'est sur l'étude théorique mais également numérique de la dynamique asymptotique et transitoire du modèle de FHN en EDO, que se concentre la seconde partie de cette thèse. A partir de cette étude, des réseaux d'interactions d'EDO sont construits en couplant les systèmes dynamiques précédemment étudiés. L'étude du phénomène de synchronisation identique au sein de ces réseaux montre l'existence de propriétés émergentes pouvant être caractérisées par exemple par des lois de puissance. Dans une troisième partie, on se concentre sur l'étude du système de FHN dans sa version EDP. Comme la partie précédente, des réseaux d'interactions d'EDP sont étudiés. On entreprend dans cette partie une étude théorique et numérique. Dans la partie théorique, on montre l'existence de l'attracteur global dans l'espace L2(Ω)nd et on donne des conditions suffisantes de synchronisation. Dans la partie numérique, on illustre le phénomène de synchronisation ainsi que l'émergence de lois générales telles que les lois puissances ou encore la formation de patterns, et on étudie l'effet de l'ajout de la dimension spatiale sur la synchronisation. / The neuron, a fundamental unit in the nervous system, is a point of interest in many scientific disciplines. Thus, there are some mathematical models that describe their behavior by ODE or PDE systems. Many of these models can then be coupled in order to study the behavior of networks, complex systems in which the properties emerge. Firstly, this work presents the main mechanisms governing the neuron behaviour in order to understand the different models. Several models are then presented, including the FitzHugh-Nagumo one, which has a interesting dynamic. The theoretical and numerical study of the asymptotic and transitory dynamics of the aforementioned model is then proposed in the second part of this thesis. From this study, the interaction networks of ODE are built by coupling previously dynamic systems. The study of identical synchronization phenomenon in these networks shows the existence of emergent properties that can be characterized by power laws. In the third part, we focus on the study of the PDE system of FHN. As the previous part, the interaction networks of PDE are studied. We have in this section a theoretical and numerical study. In the theoretical part, we show the existence of the global attractor on the space L2(Ω)nd and give the sufficient conditions for identical synchronization. In the numerical part, we illustrate the synchronization phenomenon, also the general laws of emergence such as the power laws or the patterns formation. The diffusion effect on the synchronization is studied.

Finding limit cycles and their stability is one of the central problems of nonlinear thermoacoustics. However, a limit cycle is not the only type of self-excited oscillation in a nonlinear system. Nonlinear systems can have quasi-periodic and chaotic oscillations. This thesis examines the different types of oscillation in a numerical model of a ducted premixed flame, the bifurcations that lead to these oscillations and the influence of external forcing on these oscillations. Criteria for the existence and stability of limit cycles in single mode thermoacoustic systems are derived analytically. These criteria, along with the flame describing function, are used to find the types of bifurcation and minimum triggering amplitudes. The choice of model for the velocity perturbation field around the flame is shown to have a strong influence on the types of bifurcation in the system. Therefore, a reduced order model of the velocity perturbation field in a forced laminar premixed flame is obtained from Direct Numerical Simulation. It is shown that the model currently used in the literature precludes subcritical bifurcations and multi-stability. The self-excited thermoacoustic system is simulated in the time domain with many modes in the acoustics and analysed using methods from nonlinear dynamical systems theory. The transitions to the periodic, quasiperiodic and chaotic oscillations are via sub/supercritical Hopf, Neimark-Sacker and period-doubling bifurcations. Routes to chaos are established in this system. It is shown that the single mode system, which gives the same results as a describing function approach, fails to capture the period-$2$, period-$k$, quasi-periodic and chaotic oscillations or the bifurcations and multi-stability seen in the multi-modal case, and underpredicts the amplitude. Instantaneous flame images reveal that the wrinkles on the flame surface and pinch off of flame pockets are regular for periodic oscillations, while they are irregular and have multiple time and length scales for quasi-periodic and chaotic oscillations. Cusp formation, their destruction by flame propagation normal to itself, and pinch-off and rapid burning of pockets of reactants are shown to be responsible for generating a heat release rate that is a highly nonlinear function of the velocity perturbations. It is also shown that for a given acoustic model of the duct, many discretization modes are required to capture the rich dynamics and nonlinear feedback between heat release and acoustics seen in experiments. The influence of external harmonic forcing on self-excited periodic, quasi-periodic and chaotic oscillations are examined. The transition to lock-in, the forcing amplitude required for lock-in and the system response at lock-in are characterized. At certain frequencies, even low-amplitude forcing is sufficient to suppress period-$1$ oscillations to amplitudes that are 90$\%$ lower than that of the unforced state. Therefore, open-loop forcing can be an effective strategy for the suppression of thermoacoustic oscillations. This thesis shows that a ducted premixed flame behaves similarly to low-dimensional chaotic systems and that methods from nonlinear dynamical systems theory are superior to the describing function approach in the frequency domain and time domain analysis currently used in nonlinear thermoacoustics.

Ces travaux s'articulent autour du calcul des solutions périodiques dans les systèmes dynamiques non linéaires, au moyen de méthodes numériques de continuation. La recherche de solutions périodiques se traduit par un problème avec conditions aux limites périodiques, pour lequel nous avons implémenté deux méthodes d'approximation : - Une méthode spectrale dans le domaine fréquentiel, l'équilibrage harmonique d'ordre élevé, qui repose sur une formulation quadratique des équations. Nous proposons en outre une extension de cette méthode aux cas de non-linéarités non rationnelles. - Une méthode pseudo-spectrale dans le domaine temporel, la collocation à l'aide fonctions polynômiales par morceaux. Ces méthodes transforment le problème continu en un système d'équations algébriques non linéaires, dont les solutions sont calculées par continuation à l'aide de la méthode asymptotique numérique. L'ensemble de ces outils, complétés d'une analyse linéaire de stabilité, sont intégrés au code de calcul MANLAB. Applications : Un modèle physique non-régulier de clarinette est étudié en détail : à partir de la branche de solutions statiques et ses bifurcations, on calcule les différentes branches de solutions périodiques, ainsi que leur stabilité et leurs bifurcations. Ce modèle est ensuite adapté au cas du saxophone, pour lequel on intègre une caractérisation acoustique expérimentale, afin de mieux tenir compte de la géométrie complexe de l'instrument. Enfin, nous étudions un modèle physique simplifié de violon, avec une non-régularité liée frottement de Coulomb. / Periodic solutions of nonlinear dynamical systems are the focus of this work. We compute periodic solutions through a BVP formulation, solved with two numerical methods: - a spectral method, in the frequency domain: the hogh-order Harmonic Balance Method, using a quadratic formulation of the original equations. We also propose an extension to nonrational nonlinearities. - a pseudo-spectral method, in the time domain : the arthogonal collocation at Gauss point, with piece-wise polynomial interpolation. Both methods lead to a system of nonlinear algebraic equations, and its solutions are computed by a continuation algorithm : the Asymptotic Numerical Method. These methods are embeded in the numerical package MANLAB, together with a linear stability analysis. Application We then apply these methods to physical models of several instruments : a clarinet, a saxophone, and a violin. The clarinet model contains a non-smooth contact between the reed and the mouthpiece. The study focuses on the evolution of frequency, loudness, and spectrum along the branch of periodic solutions when varying the mouth pressure. The saxophone model is very similar, but an experimental characterization of the bore is used in that case. Finally, the violin model with a non-smooth Coulomb contact law and a simplified resonator is studied, showing the variety of models that can be treated using this method.