Este trabalho trata de filtragem robusta para sistemas lineares sujeitos a saltos Markovianos discretos no tempo. Serão desenvolvidas estimativas preditoras e filtradas baseadas em algoritmos recursivos que são úteis para aplicações em tempo real. Serão desenvolvidas duas classes de filtros robustos, uma baseada em uma estratégia do tipo H \'INFINITO\' e a outra baseada no método dos mínimos quadrados regularizados robustos. Além disso, serão desenvolvidos filtros na forma de informação e seus respectivos algoritmos array para estimar esse tipo de sistema. Neste trabalho assume-se que os parâmetros de saltos do sistema Markoviano não são acessíveis. / This work deals with the problem of robust state estimation for discrete-time uncertain linear systems subject to Markovian jumps. Predicted and filtered estimates are developed based on recursive algorithms which are useful in on-line applications. We develop two classes of filters, the first one is based on a H \'INFINITO\' approach and the second one is based on a robust regularized leastsquare method. Moreover, we develop information filter and their respective array algorithms to estimate this kind of system. We assume that the jump parameters of the Markovian system are not acessible.

O presente trabalho apresenta um método de projeto de controlador com alocação de pólos em sistemas fuzzy utilizando funções de Lyapunov por partes e contínuas no espaço de estado. A idéia principal é utilizar controladores chaveados no espaço de estado para obter uma resposta transitória satisfatória do sistema, obtida pela localização dos pólos. A modelagem fuzzy Takagi-Sugeno é utilizada para representar um sistema não-linear em diversos pontos de linearização através de uma aproximação por vários modelos locais lineares invariantes no tempo. A análise de estabilidade e o projeto de sistemas de controle podem se formulados em termos de desigualdades matriciais lineares (em inglês, linear matrix inequalities (LMIs)), as quais são resolvidas por técnicas de programação convexa. Na análise de estabilidade ou na síntese de um controlador em sistemas fuzzy é necessário resolver um número determinado de LMIs de acordo com o número de modelos locais. Encontrar uma função de Lyapunov comum a todos os modelos locais pode ser inviável, especialmente quando se impõem critérios de desempenho, que aparecem como restrições no contexto de LMIs. A proposta de uma função de Lyapunov por partes objetiva diminuir o conservadorismo na busca de um controlador que leve os pólos de malha fechada à uma região desejada. Resultados de análise e síntese da teoria de sistemas lineares por partes contribuíram para a construção do resultado apresentado. Exemplos com simulação ilustram o método proposto. / This work presents a controller design method for fuzzy dynamic systems based on piecewise Lyapunov functions with constraints on the closed-loop pole location. The main idea is to use switched controllers to locate the poles of the system to obtain a satisfactory transient response. The pole placement strategy allows to specify the performance in terms of the desired time response of the feedback system. The Takagi-Sugeno fuzzy model can approximate the nonlinear system in several linearization points using linear time invariant systems. Thus, a global fuzzy model can be obtained from a fuzzy combination of these linear systems. Stability analysis and design of fuzzy control systems can be efficiently carried out in the context of linear matrix inequalities (LMIs). If the fuzzy system is described by many local models, the resulting set of LMIs may be infeasible. The search for a Lyapunov function in the fuzzy pole placement problem may be easier to be satisfied in a piecewise framework. Some results from piecewise linear systems theory have contributed to the development of the presented technique. Some examples are given to illustrate the proposed method.

Este trabalho trata de filtragem robusta para sistemas lineares sujeitos a saltos Markovianos discretos no tempo. Serão desenvolvidas estimativas preditoras e filtradas baseadas em algoritmos recursivos que são úteis para aplicações em tempo real. Serão desenvolvidas duas classes de filtros robustos, uma baseada em uma estratégia do tipo H \'INFINITO\' e a outra baseada no método dos mínimos quadrados regularizados robustos. Além disso, serão desenvolvidos filtros na forma de informação e seus respectivos algoritmos array para estimar esse tipo de sistema. Neste trabalho assume-se que os parâmetros de saltos do sistema Markoviano não são acessíveis. / This work deals with the problem of robust state estimation for discrete-time uncertain linear systems subject to Markovian jumps. Predicted and filtered estimates are developed based on recursive algorithms which are useful in on-line applications. We develop two classes of filters, the first one is based on a H \'INFINITO\' approach and the second one is based on a robust regularized leastsquare method. Moreover, we develop information filter and their respective array algorithms to estimate this kind of system. We assume that the jump parameters of the Markovian system are not acessible.

[pt] Identificação paramétrica de sistemas mecânicos é uma das principais aplicações das técnicas de identificação de sistemas na Engenharia Mecânica, especificamente para a identificação de parâmetros modais de estruturas flexíveis. Um dos principais problemas na identificação é a presença de ruido nas medições. Este trabalho apresenta uma análise na presença de ruído de alguns dos métodos no domínio do tempo aplicáveis na identificação de parâmetros modais de sistemas mecânicos lineares invariantes no tempo com múltiplas entradas e múltiplas saídas (MIMO), usando como base o modelo em espaço de estados tipicamente usado em Dinâmica e Vibrações. Os algoritmos de subespaço envolvidos neste estudo destacam-se pela utilização da decomposição em valores singulares (SVD) dos dados, obtendo subespaços ortogonais dos modos associados ao sistema e dos modos associados ao ruído. Outros complicadores no processo de identificação que serão explorados neste trabalho são: flexibilidde e baixo amortecimento. Comparam-se as técnicas usando o modelo no espaço de estado da estrutura Mini- mast desenvolvida pela NASA Langley Research Center e simulações são feitas variando o nível de ruído nos dados, o amortecimento e a flexibilidade da estrutura. O problema de identificação de parâmetros estruturais (matrizes de massa, rigidez e amortecimento) também é estudado, as características e limitações dos algoritmos utilizados são analisados. Como exemplo de aplicação prática, um experimento foi realizado para identificar os parâmetros modais e estruturais de um rotor flexível e os resultados são discutidos. / [en] Parametric identification of mechanical systems is one of the main applications of the system identification techniques in Mechanical Engineering, specifically for the identification of modal parameters of flexible structures. One of the main problems in the identification is the presence of noise in the measurements. This work presents an analysis in the presence of noise of some of the time domain methods applicable in modal parameters identification of linear time-invariant mechanical systems with multiple inputs and multiple outputs (MIMO), using as base the state-space model typically used in Dynamics and Vibrations. The subspace algorithms involved in this study are distinguished for the use of the singular values decomposition (SVD) of the data, obtaining ortogonal subspaces of the modes associates to the system and of the modes associates to the noise. Other complicators in the identification process that will be explored in this work are: flexibility and low damping. The techniques are compared using the state-space model of the Mini-mast structure developed for NASA Langley Research Center and simulations are made varying the level of noise in the data, the damping and the flexibility of the structure. The problem of identification of structural parameters (mass, stiffness and damping matrices) also is studied, the characteristics and limitations of the used algorithm is analyzed. As example of practical application, an experiment was made to identify the modal parameters of a flexible rotor and the results are discussed.

<p>In computational science it is common to describe dynamic systems by mathematical models in forms of differential or integral equations. These models may contain parameters that have to be computed for the model to be complete. For the special type of ordinary differential equations studied in this thesis, the resulting parameter estimation problem is a separable nonlinear least squares problem with equality constraints. This problem can be solved by iteration, but due to complicated computations of derivatives and the existence of several local minima, so called short-cut methods may be an alternative. These methods are based on simplified versions of the original problem. An algorithm, called the modified Kaufman algorithm, is proposed and it takes the separability into account. Moreover, different kinds of discretizations and formulations of the optimization problem are discussed as well as the effect of ill-conditioning.</p><p>Computation of parameters often includes as a part solution of linear system of equations <i>Ax = b</i>. The corresponding pseudoinverse solution depends on the properties of the matrix <i>A</i> and vector <i>b</i>. The singular value decomposition of <i>A</i> can then be used to construct error propagation matrices and by use of these it is possible to investigate how changes in the input data affect the solution <i>x</i>. Theoretical error bounds based on condition numbers indicate the worst case but the use of experimental error analysis makes it possible to also have information about the effect of a more limited amount of perturbations and in that sense be more realistic. It is shown how the effect of perturbations can be analyzed by a semi-experimental analysis. The analysis combines the theory of the error propagation matrices with an experimental error analysis based on randomly generated perturbations that takes the structure of <i>A</i> into account</p>

In computational science it is common to describe dynamic systems by mathematical models in forms of differential or integral equations. These models may contain parameters that have to be computed for the model to be complete. For the special type of ordinary differential equations studied in this thesis, the resulting parameter estimation problem is a separable nonlinear least squares problem with equality constraints. This problem can be solved by iteration, but due to complicated computations of derivatives and the existence of several local minima, so called short-cut methods may be an alternative. These methods are based on simplified versions of the original problem. An algorithm, called the modified Kaufman algorithm, is proposed and it takes the separability into account. Moreover, different kinds of discretizations and formulations of the optimization problem are discussed as well as the effect of ill-conditioning. Computation of parameters often includes as a part solution of linear system of equations Ax = b. The corresponding pseudoinverse solution depends on the properties of the matrix A and vector b. The singular value decomposition of A can then be used to construct error propagation matrices and by use of these it is possible to investigate how changes in the input data affect the solution x. Theoretical error bounds based on condition numbers indicate the worst case but the use of experimental error analysis makes it possible to also have information about the effect of a more limited amount of perturbations and in that sense be more realistic. It is shown how the effect of perturbations can be analyzed by a semi-experimental analysis. The analysis combines the theory of the error propagation matrices with an experimental error analysis based on randomly generated perturbations that takes the structure of A into account

Many control algorithms for ABS systems have been proposed in the literature since the introduction of this equipment by Bosch in 1978. In general, one can divide these control algorithms into two different types: those based on a regulation logic with wheel acceleration thresholds that are used by most commercial ABS systems; and those based on wheel slip control that are preferred in the large majority of academic algorithms. Each approach has its pros and cons [Shida 2010]. Oversimplifying, one can say that the strength of the first ones is their robustness; while that of the latter ones their short braking distances (on dry grounds) and their absence of limit cycles. At the midpoint of this industry/academy dichotomy, based on the concept of extended braking stiffness (XBS), a quite different class of ABS control strategies has been proposed by several researchers (see, e.g., [Sugai 1999] and [Ono 2003]). This concept combines the advantages from both the industrial and academic approaches. Nevertheless, since the slope of the tyre characteristic is not directly measurable, it introduces the question of real-time XBS estimation. The first part of this thesis is devoted to the study of this estimation problem and to a generalization of the proposed technique to a larger class of systems. From the technological point of view, the design of ABS control systems is highly dependent on the ABS system characteristics and actuator performance. Current ABS control algorithms on passenger cars, for instance the Bosch ABS algorithm, are based on heuristics that are deeply associated to the hydraulic nature of the actuator. An interesting observation is that they seem to work properly only in the presence of a specific delay coming from the hydraulic actuation [Gerard 2012]. For brake systems that have different delays compared to those of hydraulic actuators, like electric in-wheel motors (with a smaller delay) or pneumatic trailer brakes (with a bigger delay), they might be no longer suitable [Miller 2013]. Therefore, adapting standard ABS algorithms to other advanced actuators becomes an imperative goal in the automobile industry. This goal can be reached by the compensation of the delays induced by actuators. The second part of this thesis is focused on this issue, and to the generalization of the proposed technique to a particular class of nonlinear systems. Throughout this thesis, we employ two different linearization techniques: the linearization of the error dynamics in the construction of model-based observers [Krener 1983] and the linearization based on restricted state feedback [Brockett 1979]. The former is one of the simplest ways to build an observer for dynamical systems with output and to analyze its convergence. The main idea is to transform the original nonlinear system via a coordinate change to a special form that admits an observer with a linear error dynamics and thus the observer gains can be easily computed to ensure the observer convergence. The latter is a classical method to control nonlinear systems by converting them into a controllable linear state equation via the cancellation of their nonlinearities. It is worth mentioning that existing results for observer design by error linearization in the literature are only applied to the case of regular time scalings ([Guay 2002] and [Respondek 2004]). The thesis shows how to extend them to the case of singular time scalings. Besides, the thesis combines the classical state feedback linearization with a new method for the input delay compensation to resolve the output tracking problem for restricted feedback linearizable systems with input delays.

Este trabalho aborda o problema de controle ótimo por modos deslizantes via função penalidade para sistemas de tempo discreto. Para resolver este problema será desenvolvido uma estrutura matricial alternativa baseada no problema de mínimos quadrados ponderados e funções penalidade. A partir desta nova formulação é possível obter a lei de controle ótimo por modos deslizantes, as equações de Riccati e a matriz do ganho de realimentação através desta estrutura matricial alternativa. A motivação para propormos essa nova abordagem é mostrar que é possível obter uma solução alternativa para o problema clássico de controle ótimo por modos deslizantes. / This work introduces a penalty function approach to deal with the optimal sliding mode control problem for discrete-time systems. To solve this problem an alternative array structure based on the problem of weighted least squares penalty function will be developed. Using this alternative matrix structure, the optimal sliding mode control law of, the matrix Riccati equations and feedback gain were obtained. The motivation of this new approach is to show that it is possible to obtain an alternative solution to the classic problem of optimal sliding mode control.

Ce mémoire est dédié à l’étude de la synthèse de l’estimation d’état en temps fini par une approche algébrique (les techniques développées au sein de l’équipe ALIEN) pour les systèmes linéaires à paramètres invariant dans le temps (LTI) sujets à des perturbations extérieures inconnues, les systèmes linéaires à paramètres variant dans le temps (LTV) et les systèmes linéaires à commutation en temps continu (SLC). Pour les systèmes LTI et LTV, une expression formelle de l’état en fonction des intégrales itérées des sorties et de l’entrée a été donnée. Pour les systèmes linéaires à commutation, en combinant les résultats de l’estimation d’état pour les systèmes LTI et de la détection de l’instant de commutation en temps réel présentée dans le chapitre 4, nous donnons la démarche principale de l’estimation en temps réel du mode courant et l’état continu du système. Pour ce faire, on applique certains outils mathématiques : la transformation de Laplace, les outils issus du calcul opérationnel et la théorie des distributions / This PhD thesis is dedicated to the synthesis of the state estimation in a finite time by an algebraic approach (the techniques developed within the ALIEN group) for the linear time-invariant systems (LTI) subject to the external unknown disturbances, the linear time-varying systems (LTV) and the switched linear systems (SLC) in continuous time. For the LTI and LTV systems, a formal expression of state as a function of iterated integrals of the output and the input is obtained. For switched linear systems, combining the results of state estimation for LTI systems and switch instant detection presented in Chapter 4, we give the main approach of current mode estimation and the continuous state estimation in real time. To do this, one applies some mathematical tools: Laplace transforms, the operational calculus and the theory of distribution

Orientador: Parham Salehyan / Banca: Eduardo de Sequeira Esteves / Banca: Jéfferson Luiz Rocha Bastos / Resumo: O objetivo principal deste trabalho é estudar o Teorema de Riemann-Roch, um dos resultados fundamentais na teoria de curvas algébricas, e apresentar algumas de suas aplicações. Este teorema é uma importante ferramenta para a classificação das curvas algébricas, pois relaciona propriedades algébricas e topológicas. Daremos uma descrição das curvas algébricas de gênero g, 1≤ g ≤ 5, e faremos um breve estudo dos pontos de inflexão de um sistema linear sobre uma curva algébrica / Abstract: The main purpose of this work is to discuss The Riemann-Roch Theorem, wich is one of the most important results of the theory algebraic curves, and to present some applications. This theorem is an important tool of the classification of algebraic curves, sinces relates algebraic and topological properties. We will describle the algebraic curves of genus g, 1≤ g ≤ 5, and also study inflection points of a linear system on an algebraic curve / Mestre