Esta tese trata das propriedades estruturais e do controle de sistemas lineares singulares sujeitos a saltos Markovianos (SLSSM). Três questões fundamentais são consideradas para esta classe de sistemas. A primeira estabelece condições necessárias para que o sistema seja estocasticamente regular em um período de tempo determinado. A segunda trata da estabilidade exponencial estocástica de SLSSM. Equações de Lyapunov acopladas generalizadas são deduzidas para caracterizar estabilidade deste tipo de sistema. Em virtude da complexidade das soluções numéricas dessas equações, cada equação de Lyapunov do conjunto acoplado está em função de duas variáveis desconhecidas, estamos propondo um algoritmo para resolver este problema. A terceira questão diz respeito à síntese de um regulador para este tipo de sistema singular definida em termos de equações algébricas generalizadas de Riccati acopladas. / This thesis deals with the structural features and with the control of singular linear systems with Markovian jump parameters (SLSMJP). Three fundamental questions are considered to this class of systems. The first provides necessary conditions to characterize stochastic regularity in a determined period of time. The second deals with exponential stability of SLSMJP. Coupled generalized Lyapunov Equations are deduced to check the stability of this class of systems. In virtue of the complexity of the numerical solutions of these equations, there exist two unknown variables for each equation of the set of coupled Lyapunov equations, we are proposing an algorithm to solve this problem. The third question is related with the synthesis of a regulator for this class of singular systems defined in terms of coupled algebraic generalized Riccati equations.

Esta tese trata das propriedades estruturais e do controle de sistemas lineares singulares sujeitos a saltos Markovianos (SLSSM). Três questões fundamentais são consideradas para esta classe de sistemas. A primeira estabelece condições necessárias para que o sistema seja estocasticamente regular em um período de tempo determinado. A segunda trata da estabilidade exponencial estocástica de SLSSM. Equações de Lyapunov acopladas generalizadas são deduzidas para caracterizar estabilidade deste tipo de sistema. Em virtude da complexidade das soluções numéricas dessas equações, cada equação de Lyapunov do conjunto acoplado está em função de duas variáveis desconhecidas, estamos propondo um algoritmo para resolver este problema. A terceira questão diz respeito à síntese de um regulador para este tipo de sistema singular definida em termos de equações algébricas generalizadas de Riccati acopladas. / This thesis deals with the structural features and with the control of singular linear systems with Markovian jump parameters (SLSMJP). Three fundamental questions are considered to this class of systems. The first provides necessary conditions to characterize stochastic regularity in a determined period of time. The second deals with exponential stability of SLSMJP. Coupled generalized Lyapunov Equations are deduced to check the stability of this class of systems. In virtue of the complexity of the numerical solutions of these equations, there exist two unknown variables for each equation of the set of coupled Lyapunov equations, we are proposing an algorithm to solve this problem. The third question is related with the synthesis of a regulator for this class of singular systems defined in terms of coupled algebraic generalized Riccati equations.

Esta dissertação desenvolve filtro de informação, algoritmos array para estimador do erro médio mínimo quadrático para sistemas lineares sujeitos a saltos Markovianos e algoritmos array rápidos para filtragem de sistemas singulares convencionais. Exemplos numéricos serão apresentados para mostrarem as vantagens dos algoritmos array deduzidos. Parte dos resultados obtidos nesta pesquisa serão publicados no seguinte artigo: Terra et al. (2007). Terra, M. H., Ishihara, J. Y. and Jesus, G. Q. (2007). Information filtering and array algorithms for discrete-time Markovian jump linear systems. Proceedings of the American Control Conference ACC07. / This dissertation develops information filter and array algorithms for linear minimum mean square error estimator (LMMSE) of discrete-time Markovian jump linear systems (MJLSs) and fast array algorithms for filtering of standard singular systems. Numerical examples to show the advantage of the array algorithms are presented. Some results obtained in this research are published in the following paper: Terra et al. (2007). Terra, M. H., Ishihara, J. Y. and Jesus, G. Q. (2007). Information filtering and array algorithms for discrete-time Markovian jump linear systems. Proceedings of the American Control Conference ACC07.

Dans ce travail de thèse on s’intéresse à l’estimation de l’attitude d’un corps rigideen mouvement dans l’espace 3D en utilisant les quaternions comme représentation. Cetteproblématique a été largement étudiée dans la littérature sous divers domaines d’application.L’objectif de la thèse est de proposer de nouvelles méthodes de fusion de données en combinantdes mesures inertielles et magnétiques. Dans un premier temps, nous nous sommesintéressés à l’estimation de l’attitude en cas de mouvement accéléré où l’accélération linéairedu corps n’est plus négligeable devant la gravité. Deux approches ont été proposées dans cecadre. La première utilise un filtre de Kalman adaptatif pour la compensation des accélérationslinéaires. Précisément, des lois de détection ont été développées pour distinguer d’unefaçon automatique les différentes phases de mouvement (statiques et dynamiques). Ainsi, lamatrice de covariance associée à l’accélération linéaire est estimée afin d’ajuster le gain dufiltre. La deuxième approche consiste à intégrer un filtre singulier élaboré sur la base d’unnouveau modèle, dans lequel le modèle du processus est défini en se basant sur les mesuresissues de l’accéléromètre tandis que le modèle d’observation est défini par les mesures issuesdu gyromètres et du magnétomètres. Cette formulation permet de prendre en compte l’effetdes accélérations linéaires d’une manière efficace. Dans un deuxième temps, on s’est focalisésur l’estimation de l’attitude avec utilisation intermittente de gyromètres, considérés commecapteurs énergivores. Nous avons étudié dans ce cas la façon la plus adéquate afin de réduirel’acquisition des mesures de vitesse angulaire tout en gardant une qualité acceptable de l’estimationde l’attitude. Toutes les approches développées ont été validées par des simulationsnumériques ainsi que des expérimentations utilisant des données réelles. / In this PhD. thesis we deal with attitude estimation of accelerated rigid body moving in the 3D space using quaternion parameterization. This problem has been widely studied in the literature in various application areas. The main objective of the thesis is to propose new methods for data fusion to combine inertial gyros) and magnetic measurements. The first challenge concerns the attitude estimation during dynamic cases, in which external acceleration of the body is not negligible compared to the Gravity. Two main approaches are proposed in this context. Firstly, a quatenion-based adaptive Kalman filter (q-AKF) was designed in order to compensate for such external acceleration. Precisely, a smart detector is designed to decide whether the body is in static or dynamic case. Then, the covariance matrix of the external acceleration is estimated to tune the filter gain. Second, we developed descriptor filter based on a new formulation of the dynamic model where the process model is fed by accelerometer measurements while observation model is fed by gyros and magnetometer measurements. Such modeling gives rise to a descriptor system. The resulting model allows taking the external acceleration of the body into account in a very efficient way. The second challenge is related to the energy consumption issue of gyroscope, considered as the most power consuming sensor. We study the way to reduce the gyro measurements acquisition by switching on/off the sensor while maintaining an acceptable attitude estimation. The effciency of the proposed methods is evaluated by means of numerical simulations and experimental tests.

Esta dissertação apresenta um estudo dos filtros de Kalman para sistemas singulares em tempo discreto. Novos algoritmos são formulados para as estimativas filtradas, preditoras e suavizadas com as correspondentes equações de Riccati para sistemas singulares variantes no tempo. Nesta dissertação considera-se também uma aproximação do problema de filtragem de Kalman como um problema determinístico de ajuste ótimo de trajetória. A formulação proposta permite considerar um atraso no sinal de medida, sendo permitida a correlação entre os estados e os ruídos da medida. Apresentam-se também as provas da estabilidade e da convergência destes filtros. / This dissertation presents a study of Kalman filters for singular systems in discrete time. New algorithms are developed for the Kalman filtered, predicted and smoothed estimate recursions with the corresponding Riccati equations for time-variant singular systems. This dissertation addresses the Kalman filtering problem as a deterministic optimal trajectory fitting problem. The problem is formulated taking into account one delay in the measured signals and correlations between state and measurement noises. In the final, this work presents the stability and convergence proofs of these filters.

Orientadores: Sandra Augusta Santos, Roberto Andreani / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-14T11:40:11Z (GMT). No. of bitstreams: 1 Shirabayashi_WesleyVagnerInes_D.pdf: 877226 bytes, checksum: a814cd9947431a0aee17517c4cc953f4 (MD5) Previous issue date: 2009 / Resumo: Neste trabalho reformulamos o problema de complementaridade não linear generalizado (GNCP) em cones poliedrais como um sistema não linear com restrição de não negatividade em algumas variáveis, e trabalhamos na resolução de tal reformulação por meio de estratégias de pontos interiores. Em particular, definimos dois algoritmos e provamos a convergência local de tais algoritmos sob hipóteses usuais. O primeiro algoritmo é baseado no método de Newton, e o segundo, no método tensorial de Chebyshev. O algoritmo baseado no método de Chebyshev pode ser visto como um método do tipo preditor-corretor. Tal algoritmo, quando aplicado a problemas em que as funções envolvidas são afins, e com escolhas adequadas dos parâmetros, torna-se o bem conhecido algoritmo preditor-corretor de Mehrotra. Também apresentamos resultados numéricos que ilustram a competitividade de ambas as propostas. / Abstract: In this work we reformulate the generalized nonlinear complementarity problem (GNCP) in polyhedral cones as a nonlinear system with nonnegativity in some variables and propose the resolution of such reformulation through interior-point methods. In particular we define two algorithms and prove the local convergence of these algorithms under standard assumptions. The first algorithm is based on Newton's method and the second, on the Chebyshev's tensorial method. The algorithm based on Chebyshev's method may be considered a predictor-corrector one. Such algorithm, when applied to problems for which the functions are affine, and the parameters are properly chosen, turns into the well-known Mehrotra's predictor corrector algorithm. We also present numerical results that illustrate the competitiveness of both proposals. / Doutorado / Otimização / Doutor em Matemática Aplicada

Les travaux présentés dans cette thèse ont été effectués au Centre de Recherche en Automatique de Nancy (CRAN). Ils portent sur l'observation et la commande des systèmes singuliers non linéaires. Dans un premier temps nous nous sommes intéressés à la synthèse d'observateur et au filtrage H infini des systèmes singuliers bilinéaires. Dans un deuxième temps, nous avons étudié la synthèse d'observateur pour les systèmes singuliers non linéaires Lipschitziens. La dernière partie de ce travail concerne la stabilisation et la commande basée observateurs des systèmes singuliers non linéaires. L'objectif de ce travail a été de proposer des résultats facilement implémentables et de couvrir une large classe de systèmes non linéaires. La contribution principale de ce mémoire a été de proposer des observateurs H infini pour les systèmes singuliers non linéaires, en utilisant le non biais de l'erreur d'estimation. Les paramètres de ces observateurs sont obtenus par la résolution des inégalités matricielles linéaires (LMIs). Le deuxième apport concerne la synthèse de commande stabilisante et l'utilisation d'un des observateurs proposés dans cette thèse pour la synthèse d'une commande basée observateur pour les systèmes singuliers non linéaires. Cette dernière est réalisée grâce à la réécriture des fonctions non linéaires sous des formes adéquates à l'application de la commande des systèmes / This thesis work is realized in the Research Center in Automatic Control of Nancy (CRAN). It concerns the observation and control of nonlinear singular systems. Firstly, we were interested in the observer design and H infinity filtering for singular bilinear systems. In a second step, we studied the observers design for Lipschitz nonlinear singular systems. The last part of this work relates to the stabilization and observer based controller for a classe of singular nonlinear systems. The objective is to develop a simple and straightforward results which covers a large class of nonlinear systems. The main contribution of this thesis is in the H infinity observers design for nonlinear singular systems. It is based on the parametrization of the solution of the constrained generalized Sylvester equation. The second contribution relates to the design of stabilizing control and using the proposed observer to design an obsever based controller for nonlinear singular systems. Solutions of these problems are obtained by using Linear Matrix Inequalities (LMI) Formulation

Esta tese apresenta novos algoritmos que resolvem problemas de estimativas filtrada, suavizadora e preditora para sistemas singulares no tempo discreto usando apenas argumentos determinísticos. Cada capítulo aborda inicialmente as estimativas para o sistema nominal e em seguida, as versões robustas para o sistema com incertezas limitadas. Os resultados encontrados podem ser aplicados tanto em sistemas invariantes como variantes no tempo discreto, utilizando a mesma estrutura do filtro de Kalman. Nos últimos anos, uma quantidade significativa de trabalhos envolvendo estimativas singulares foi publicada enfocando apenas a estimativa filtrada sob a justificativa de que a estimativa preditora era de significativa complexidade quando modelada pelo método dos mínimos quadrados. Por este motivo, poucos trabalhos, como NIKOUKHAH et al. (1992) e ZHANG et al. (1998), deduziram a estimativa preditora. Este último artigo apresentou também um algoritmo para a estimativa suavizadora, mas usando o modelo de inovação ARMA. No entanto, até onde foi possível identificar, nenhum trabalho até agora resolveu o problema de estimativa robusta, considerando incertezas nos parâmetros, para sistemas singulares. Para a dedução das estimativas singulares robustas, esta tese tomou como base SAYED (2001), que deduz o filtro de Kalman robusto com incertezas limitadas utilizando uma abordagem determinística, o chamado filtro BDU. Os filtros robustos para sistemas singulares apresentados nesta tese, são mais abrangentes que os apresentados em SAYED (2001). Quando particularizados para o espaço de estados sem incertezas, todos os filtros se assemelham ao filtro de Kalman. / New algorithms to optimal recursive filtering, smoothed and prediction for general time-invariant or time-variant descriptor systems are proposed in this thesis. The estimation problem is addressed as an optimal deterministic trajectory fitting. This problem is solved using exclusively deterministic arguments for systems with or without uncertainties. Kalman type recursive algorithms for robust filtered, predicted and smoothed estimations are derived. In the last years, many papers have paid attention to the estimation problems of linear singular systems. Unfortunately, all those works were concentrated only on the study of filtering problems, for nominal systems. The predicted and smoothed filters are more involved and were considered only by few works : NIKOUKHAH et al. (1992) and ZHANG et al. (1998) had proposed a unified approach for filtering, prediction and smoothing problems which were derived by using the projection formula and were calculated based on the ARMA innovation model, but they had not considered the uncertainties. In this thesis its applied for descriptor systems a robust procedure for usual state space systems developed by SAYED (2001), called BDU filter. It is obtained a robust descriptor Kalman type recursions for filtered, predicted and smoothed estimates. Considering the nominal state space, all descriptor filters developed in this work collapse to the Kalman filter.

Esta tese apresenta novos algoritmos que resolvem problemas de estimativas filtrada, suavizadora e preditora para sistemas singulares no tempo discreto usando apenas argumentos determinísticos. Cada capítulo aborda inicialmente as estimativas para o sistema nominal e em seguida, as versões robustas para o sistema com incertezas limitadas. Os resultados encontrados podem ser aplicados tanto em sistemas invariantes como variantes no tempo discreto, utilizando a mesma estrutura do filtro de Kalman. Nos últimos anos, uma quantidade significativa de trabalhos envolvendo estimativas singulares foi publicada enfocando apenas a estimativa filtrada sob a justificativa de que a estimativa preditora era de significativa complexidade quando modelada pelo método dos mínimos quadrados. Por este motivo, poucos trabalhos, como NIKOUKHAH et al. (1992) e ZHANG et al. (1998), deduziram a estimativa preditora. Este último artigo apresentou também um algoritmo para a estimativa suavizadora, mas usando o modelo de inovação ARMA. No entanto, até onde foi possível identificar, nenhum trabalho até agora resolveu o problema de estimativa robusta, considerando incertezas nos parâmetros, para sistemas singulares. Para a dedução das estimativas singulares robustas, esta tese tomou como base SAYED (2001), que deduz o filtro de Kalman robusto com incertezas limitadas utilizando uma abordagem determinística, o chamado filtro BDU. Os filtros robustos para sistemas singulares apresentados nesta tese, são mais abrangentes que os apresentados em SAYED (2001). Quando particularizados para o espaço de estados sem incertezas, todos os filtros se assemelham ao filtro de Kalman. / New algorithms to optimal recursive filtering, smoothed and prediction for general time-invariant or time-variant descriptor systems are proposed in this thesis. The estimation problem is addressed as an optimal deterministic trajectory fitting. This problem is solved using exclusively deterministic arguments for systems with or without uncertainties. Kalman type recursive algorithms for robust filtered, predicted and smoothed estimations are derived. In the last years, many papers have paid attention to the estimation problems of linear singular systems. Unfortunately, all those works were concentrated only on the study of filtering problems, for nominal systems. The predicted and smoothed filters are more involved and were considered only by few works : NIKOUKHAH et al. (1992) and ZHANG et al. (1998) had proposed a unified approach for filtering, prediction and smoothing problems which were derived by using the projection formula and were calculated based on the ARMA innovation model, but they had not considered the uncertainties. In this thesis its applied for descriptor systems a robust procedure for usual state space systems developed by SAYED (2001), called BDU filter. It is obtained a robust descriptor Kalman type recursions for filtered, predicted and smoothed estimates. Considering the nominal state space, all descriptor filters developed in this work collapse to the Kalman filter.

L'objectif de cette thèse est de développer des méthodes de synthèses d'observateurs et des contrôleurs basés sur un observateur pour les systèmes à retard. Différentes classes de systèmes ont été traitées avec différents types de retard. Trois méthodes ont été développées. La première méthode traite des systèmes non linéaires avec des non-linéarités lipschitziennes et consiste à transformer le système d'origine à un système LPV grâce à une reformulation de la propriété classique de Lipschitz. Cette technique est formulée pour les cas continu et discret, respectivement. Nous avons démontré, à travers des exemples numériques, que cette technique offre des conditions de synthèse moins restrictives par rapport aux résultats existants dans la littérature. La seconde méthode est développée pour une classe de systèmes singuliers avec des perturbations. La principale difficulté résidait dans la présence des dérivées des perturbations qui entravent l'analyse de la stabilité et pour laquelle deux approches ont été proposées: une approche $\mathcal{H}_{\infty}$ en utilisant une fonctionnelle de Lyapunov-Krasovskii spéciale dépendante des perturbations et une approche basée sur l'utilisation d'un critère de performance $\mathcal{W}^{1,2}$. La dernière méthode est basée sur l'utilisation des matrices de pondération libres pour résoudre le problème de contrôle des systèmes non-linéaires à retards inconnus. La solution proposée fournit une condition de synthèse LMI garantissant la stabilisation du système en boucle fermée malgré la présence du retard inconnu, au lieu d'une inégalité matricielle linéaire itérative ILMI trouvée habituellement dans la littérature / The objective of this dissertation is to develop observers and observer-based controllers synthesis methods for time-delay systems. Different classes of systems were treated with different types of delay. Three different methods were developed. The first one treats nonlinear systems with Lipschitz nonlinearities and consists in transforming the original system into an LPV system based on a reformulation of the classical Lipschitz property. This technique was formulated for continuous and discrete cases respectively and it was proven to provide less restrictive synthesis conditions when compared to the existing results in the literature. The second method deals with singular systems with disturbances. The main difficulty lay in the presence of the derivatives of the disturbances which hinder the stability analysis and for which two approaches are proposed:~a $\mathcal{H}_{\infty}$ criterion combined with a special Lyapunov-Krasovskii functional depending on disturbances and a $\mathcal{W}^{1,2}$ criterion based on the use of Sobolev norms. The last method is based on the Free Weighting Matrices technique to solve the observation and control problems of a class of nonlinear systems with unknown delays. The proposed solution provides a sufficient LMI synthesis condition ensuring the asymptotic stabilization of the closed loop system, instead of the iterative LMI condition usually found in the literature