Industrial robot manipulators are general-purpose machines used for industrial automation in order to increase productivity, flexibility, and quality. Other reasons for using industrial robots are cost saving, and elimination of heavy and health-hazardous work. Robot motion control is a key competence for robot manufacturers, and the current development is focused on increasing the robot performance, reducing the robot cost, improving safety, and introducing new functionalities. Therefore, there is a need to continuously improve the models and control methods in order to fulfil all conflicting requirements, such as increased performance for a robot with lower weight, and thus lower mechanical stiffness and more complicated vibration modes. One reason for this development of the robot mechanical structure is of course cost-reduction, but other benefits are lower power consumption, improved dexterity, safety issues, and low environmental impact. This thesis deals with three different aspects of modeling and control of flexible, i.e., elastic, manipulators. For an accurate description of a modern industrial manipulator, the traditional flexible joint model, described in literature, is not sufficient. An improved model where the elasticity is described by a number of localized multidimensional spring-damper pairs is therefore proposed. This model is called the extended flexible joint model. This work describes identification, feedforward control, and feedback control, using this model. The proposed identification method is a frequency-domain non-linear gray-box method, which is evaluated by the identification of a modern six-axes robot manipulator. The identified model gives a good description of the global behavior of this robot. The inverse dynamics control problem is discussed, and a solution methodology is proposed. This methodology is based on a differential algebraic equation (DAE) formulation of the problem. Feedforward control of a two-axes manipulator is then studied using this DAE approach. Finally, a benchmark problem for robust feedback control of a single-axis extended flexible joint model is presented and some proposed solutions are analyzed.

La presente tesis estudia, propone y realiza sus principales aportaciones en el campo del control para el convertidor CC/CA de tres niveles, sobre la topología denominada Neutral-Point-Clamped, aunque se puede extender a otras topologías y/o número de niveles. Se presenta una metodología de modelado que emplea funciones de conmutación de fase, el operador de promediado y la transformación D-Q, tal que los modelos obtenidos en el dominio D-Q contienen una información completa sobre la dinámica del sistema. La estrategia de conmutación se puede entender como una extensión de la estrategia PWM senoidal de dos a tres niveles. Esta estrategia es simple y no realiza el control de ninguna de las variables del sistema. En esta tesis, el controlador se encarga de regular todas las variables del sistema, incluido el equilibrio del bus de continua. Este es un enfoque diferente del convencional, donde el equilibrio del bus de continua se consigue mediante la elección adecuada de los estados redundantes del convertidor en la estrategia de conmutación, mientras que el resto de variables se regulan a través del controlador. Para la realización del controlador, se propone la técnica de control lineal multivariable LQR (Linear Quadratic Regulator), complementada con la técnica de control no lineal adaptativo denominada programación de ganancia (Gain Scheduling). Se presenta, además, una metodología de cálculo del controlador. Este control es versátil, abierto y adaptable. En cualquier caso, el controlador se puede adaptar a las necesidades concretas de cada aplicación. El cálculo del controlador se realiza mediante simulación con MatLab-Simulink. Los modelos matemáticos que emplean las funciones de conmutación del convertidor son aquellos que ofrecen un mejor compromiso entre velocidad de simulación y precisión. Para validar el control propuesto, se ha diseñado y construido un equipo experimental donde el controlador se ha mostrado aplicable, útil y eficaz en la regulación de las distintas cargas y aplicaciones experimentadas, incluso con carga no lineal, bajo diferentes condiciones de trabajo y variables a controlar, tanto en régimen permanente como en procesos transitorios. La rapidez y calidad de la respuesta transitoria es comparable a la de otros sistemas de control publicados. Es especialmente interesante el excelente control conseguido del equilibrio del bus de continua. Además, la robustez del control permite cancelar el error estacionario aunque diferentes parámetros del sistema presenten desviaciones significativas respecto los valores esperados. El uso de la programación de ganancia junto con la técnica LQR se ha mostrado muy efectivo, puesto que permite realizar diferentes tipos de control. Se ha comprobado la congruencia entre simulaciones y resultados experimentales obtenidos, lo que valida los modelos de simulación empleados y el proceso de diseño del controlador mediante simulación. / This dissertation study, propose and carry out the main contributions in the field of three-level inverter control, using the topology Neutral-Point-Clamped, although results can be extended to other topologies and/or number of levels. A procedure for modelling is presented, based on line-switching functions, moving average operator and D-Q transformation. Then, the obtained models in D-Q frame contain complete information about system dynamics. Switching strategy is simple and can be considered as an extension of two-level sinusoidal PWM to three level. The system variables are not controlled by the switching strategy. In this work, all the system variables are controlled by the regulator, including DC-link balance. This control approach is different than the conventional one, where DC-link balance is achieved by means of a proper selection of redundant states in the switching strategy, and the other variables are controlled by the regulator. The regulator is based on the multivariable linear control technique LQR (Linear Quadratic Regulator), in combination with the non-linear adaptive control technique Gain Scheduling. Moreover, a methodology for the calculation of the controller is presented. This controller is versatile, open and adaptable. However, the controller can be built depending on the concrete specifications of each application. The controller is calculated by means of simulation using MatLab-Simulink. The mathematical models based on the switching functions of the converter give the best trade-off between simulation speed and precision. In order to validate the proposed controller, an experimental prototype has been designed and implemented. Experimental results show that the controller is useful and effective for the regulation of different loads and applications, even with non-linear loads, different operation points and variables to control, in steady-state and transitory operation. Dynamic response speed and quality are similar to other control systems in the literature. The DC-link balance control achieved is specially interesting. Furthermore, steady-state error is cancelled due to the robustness of the controller, even though significant deviation of different system parameters are present. The use of Gain-Scheduling in combination with LQR is effective, allowing the calculation of regulators with different control strategies. Good agreement between simulations and experimental results has been found. This result validates simulation models and the design method for the controller, based on simulations.

<p>Industrial robot manipulators are general-purpose machines used for industrial automation in order to increase productivity, flexibility, and quality. Other reasons for using industrial robots are cost saving, and elimination of heavy and health-hazardous work. Robot motion control is a key competence for robot manufacturers, and the current development is focused on increasing the robot performance, reducing the robot cost, improving safety, and introducing new functionalities. Therefore, there is a need to continuously improve the models and control methods in order to fulfil all conflicting requirements, such as increased performance for a robot with lower weight, and thus lower mechanical stiffness and more complicated vibration modes. One reason for this development of the robot mechanical structure is of course cost-reduction, but other benefits are lower power consumption, improved dexterity, safety issues, and low environmental impact.</p><p>This thesis deals with three different aspects of modeling and control of flexible, i.e., elastic, manipulators. For an accurate description of a modern industrial manipulator, the traditional flexible joint model, described in literature, is not sufficient. An improved model where the elasticity is described by a number of localized multidimensional spring-damper pairs is therefore proposed. This model is called the extended flexible joint model. This work describes identification, feedforward control, and feedback control, using this model.</p><p>The proposed identification method is a frequency-domain non-linear gray-box method, which is evaluated by the identification of a modern six-axes robot manipulator. The identified model gives a good description of the global behavior of this robot.</p><p>The inverse dynamics control problem is discussed, and a solution methodology is proposed. This methodology is based on a differential algebraic equation (DAE) formulation of the problem. Feedforward control of a two-axes manipulator is then studied using this DAE approach.</p><p>Finally, a benchmark problem for robust feedback control of a single-axis extended flexible joint model is presented and some proposed solutions are analyzed.</p>

Ce mémoire s’applique à étudier d’abord, dans la première partie, la mesure de Mahler des polynômes à une seule variable. Il commence en donnant des définitions et quelques résultats pertinents pour le calcul de telle hauteur. Il aborde aussi le sujet de la question de Lehmer, la conjecture la plus célèbre dans le domaine, donne quelques exemples et résultats ayant pour but de résoudre la question. Ensuite, il y a l’extension de la mesure de Mahler sur les polynômes à plusieurs variables, une démarche semblable au premier cas de la mesure de Mahler, et le sujet des points limites avec quelques exemples. Dans la seconde partie, on commence par donner des définitions concernant un ordre supérieur de la mesure de Mahler, et des généralisations en passant des polynômes simples aux polynômes à plusieurs variables. La question de Lehmer existe aussi dans le domaine de la mesure de Mahler supérieure, mais avec des réponses totalement différentes. À la fin, on arrive à notre objectif, qui sera la démonstration de la généralisation d’un théorème de Boyd-Lawton, ce dernier met en évidence une relation entre la mesure de Mahler des polynômes à plusieurs variables avec la limite de la mesure de Mahler des polynômes à une seule variable. Ce résultat a des conséquences en termes de la conjecture de Lehmer et sert à clarifier la relation entre les valeurs de la mesure de Mahler des polynômes à une variable et celles des polynômes à plusieurs variables, qui, en effet, sont très différentes en nature. / This thesis applies to study first, in part 1, the Mahler measure of polynomials in one variable. It starts by giving some definitions and results that are important for calculating this height. It also addresses the topic of Lehmer’s question, an interesting conjecture in the field, and it gives some examples and results aimed at resolving the issue. The extension of the Mahler measure to several variable polynomials is then considered including the subject of limit points with some examples. In the second part, we first give definitions of a higher order for the Mahler measure, and generalize from single variable polynomials to multivariable polynomials. Lehmer’s question has a counterpart in the area of the higher Mahler measure, but with totally different answers. At the end, we reach our goal, where we will demonstrate the generalization of a theorem of Boyd-Lawton. This theorem shows a relation between the limit of Mahler measure of multivariable polynomials with Mahler measure of polynomials in one variable. This result has implications in terms of Lehmer's conjecture and serves to clarify the relationship between the Mahler measure of one variable polynomials, and the Mahler measure of multivariable polynomials, which are very different.

RÉSUMÉ Objectif: Évaluer l'efficacité du dépistage de l’hypertension gestationnelle par les caractéristiques démographiques maternelles, les biomarqueurs sériques et le Doppler de l'artère utérine au premier et au deuxième trimestre de grossesse. Élaborer des modèles prédictifs de l’hypertension gestationnelle fondées sur ces paramètres. Methods: Il s'agit d'une étude prospective de cohorte incluant 598 femmes nullipares. Le Doppler utérin a été étudié par échographie transabdominale entre 11 +0 à 13 +6 semaines (1er trimestre) et entre 17 +0 à 21 +6 semaines (2e trimestre). Tous les échantillons de sérum pour la mesure de plusieurs biomarqueurs placentaires ont été recueillis au 1er trimestre. Les caractéristiques démographiques maternelles ont été enregistrées en même temps. Des courbes ROC et les valeurs prédictives ont été utilisés pour analyser la puissance prédictive des paramètres ci-dessus. Différentes combinaisons et leurs modèles de régression logistique ont été également analysés. Résultats: Parmi 598 femmes, on a observé 20 pré-éclampsies (3,3%), 7 pré-éclampsies précoces (1,2%), 52 cas d’hypertension gestationnelle (8,7%) , 10 cas d’hypertension gestationnelle avant 37 semaines (1,7%). L’index de pulsatilité des artères utérines au 2e trimestre est le meilleur prédicteur. En analyse de régression logistique multivariée, la meilleure valeur prédictive au 1er et au 2e trimestre a été obtenue pour la prévision de la pré-éclampsie précoce. Le dépistage combiné a montré des résultats nettement meilleurs comparés avec les paramètres maternels ou Doppler seuls. Conclusion: Comme seul marqueur, le Doppler utérin du deuxième trimestre a la meilleure prédictive pour l'hypertension, la naissance prématurée et la restriction de croissance. La combinaison des caractéristiques démographiques maternelles, des biomarqueurs sériques maternels et du Doppler utérin améliore l'efficacité du dépistage, en particulier pour la pré-éclampsie nécessitant un accouchement prématuré. Mot clés: Hypertension gestationnelle, Doppler utérins, Biomarqueurs sériques maternels, Caractéristiques démographiques maternelles, Dépistage, Modèle prédictif Multivarié. / ABSTRACT Objective: To evaluate the screening efficacy of maternal demographic characteristics, serum biomarkers and uterine artery Doppler (uaD) during the first and the second trimester for the hypertensive disorders of pregnancy. To elaborate prediction models of these diseases based on the combination of selected maternal demographic characteristics, maternal serum biomarkers and uaD indexes. Methods: This is a prospective pregnant cohort study of 598 singleton nulliparous consecutive women. UaD investigation was performed by transabdominal sonography between 11+0 and 13+6 weeks, and between 17+0 and 21+6 weeks. All the serum samples for measurement of several placental biomarkers were collected at the first trimester. Maternal demographic characteristics were recorded at the same time. Receiver operating characteristic curves and predictive values were used to analyze the predictive powers of the above parameters. Different combinations and their logistic regression predictive models were analyzed. Results: Among 598 women, 20 developed preeclampsia (3.3%), 7 developed early-onset preeclampsia (1.2%), 52 developed gestational hypertension (8.7%), 10 developed gestational hypertension with delivery before 37 weeks (1.7%). Second trimester uterine artery pulsatility index was the best predictor with statistical significance for all the outcomes. In the multivariable logistic regression analysis, the best predictive value in the first and second trimester was obtained for the prediction of early onset preeclampsia. The combined screening showed significantly better results compared to either maternal parameters or Doppler alone. Conclusion: As a single marker, second trimester Doppler has the highest predictive value for hypertensive disorders, preterm birth and SGA. Combination of the maternal demographic characteristics, maternal serum biomarker and uaD improves the screening efficacy, especially when this necessitates early delivery. Key words: Hypertensive disorders of pregnancy, Doppler, Maternal serum biomarkers, Maternal demographic characteristics, Screening, Multivariable predictive model.

En écologie, dans le cadre par exemple d’études des services fournis par les écosystèmes, les modélisations descriptive, explicative et prédictive ont toutes trois leur place distincte. Certaines situations bien précises requièrent soit l’un soit l’autre de ces types de modélisation ; le bon choix s’impose afin de pouvoir faire du modèle un usage conforme aux objectifs de l’étude. Dans le cadre de ce travail, nous explorons dans un premier temps le pouvoir explicatif de l’arbre de régression multivariable (ARM). Cette méthode de modélisation est basée sur un algorithme récursif de bipartition et une méthode de rééchantillonage permettant l’élagage du modèle final, qui est un arbre, afin d’obtenir le modèle produisant les meilleures prédictions. Cette analyse asymétrique à deux tableaux permet l’obtention de groupes homogènes d’objets du tableau réponse, les divisions entre les groupes correspondant à des points de coupure des variables du tableau explicatif marquant les changements les plus abrupts de la réponse. Nous démontrons qu’afin de calculer le pouvoir explicatif de l’ARM, on doit définir un coefficient de détermination ajusté dans lequel les degrés de liberté du modèle sont estimés à l’aide d’un algorithme. Cette estimation du coefficient de détermination de la population est pratiquement non biaisée. Puisque l’ARM sous-tend des prémisses de discontinuité alors que l’analyse canonique de redondance (ACR) modélise des gradients linéaires continus, la comparaison de leur pouvoir explicatif respectif permet entre autres de distinguer quel type de patron la réponse suit en fonction des variables explicatives. La comparaison du pouvoir explicatif entre l’ACR et l’ARM a été motivée par l’utilisation extensive de l’ACR afin d’étudier la diversité bêta. Toujours dans une optique explicative, nous définissons une nouvelle procédure appelée l’arbre de régression multivariable en cascade (ARMC) qui permet de construire un modèle tout en imposant un ordre hiérarchique aux hypothèses à l’étude. Cette nouvelle procédure permet d’entreprendre l’étude de l’effet hiérarchisé de deux jeux de variables explicatives, principal et subordonné, puis de calculer leur pouvoir explicatif. L’interprétation du modèle final se fait comme dans une MANOVA hiérarchique. On peut trouver dans les résultats de cette analyse des informations supplémentaires quant aux liens qui existent entre la réponse et les variables explicatives, par exemple des interactions entres les deux jeux explicatifs qui n’étaient pas mises en évidence par l’analyse ARM usuelle. D’autre part, on étudie le pouvoir prédictif des modèles linéaires généralisés en modélisant la biomasse de différentes espèces d’arbre tropicaux en fonction de certaines de leurs mesures allométriques. Plus particulièrement, nous examinons la capacité des structures d’erreur gaussienne et gamma à fournir les prédictions les plus précises. Nous montrons que pour une espèce en particulier, le pouvoir prédictif d’un modèle faisant usage de la structure d’erreur gamma est supérieur. Cette étude s’insère dans un cadre pratique et se veut un exemple pour les gestionnaires voulant estimer précisément la capture du carbone par des plantations d’arbres tropicaux. Nos conclusions pourraient faire partie intégrante d’un programme de réduction des émissions de carbone par les changements d’utilisation des terres. / In ecology, in ecosystem services studies for example, descriptive, explanatory and predictive modelling all have relevance in different situations. Precise circumstances may require one or the other type of modelling; it is important to choose the method properly to insure that the final model fits the study’s goal. In this thesis, we first explore the explanatory power of the multivariate regression tree (MRT). This modelling technique is based on a recursive bipartitionning algorithm. The tree is fully grown by successive bipartitions and then it is pruned by resampling in order to reveal the tree providing the best predictions. This asymmetric analysis of two tables produces homogeneous groups in terms of the response that are constrained by splitting levels in the values of some of the most important explanatory variables. We show that to calculate the explanatory power of an MRT, an appropriate adjusted coefficient of determination must include an estimation of the degrees of freedom of the MRT model through an algorithm. This estimation of the population coefficient of determination is practically unbiased. Since MRT is based upon discontinuity premises whereas canonical redundancy analysis (RDA) models continuous linear gradients, the comparison of their explanatory powers enables one to distinguish between those two patterns of species distributions along the explanatory variables. The extensive use of RDA for the study of beta diversity motivated the comparison between its explanatory power and that of MRT. In an explanatory perspective again, we define a new procedure called a cascade of multivariate regression trees (CMRT). This procedure provides the possibility of computing an MRT model where an order is imposed to nested explanatory hypotheses. CMRT provides a framework to study the exclusive effect of a main and a subordinate set of explanatory variables by calculating their explanatory powers. The interpretation of the final model is done as in nested MANOVA. New information may arise from this analysis about the relationship between the response and the explanatory variables, for example interaction effects between the two explanatory data sets that were not evidenced by the usual MRT model. On the other hand, we study the predictive power of generalized linear models (GLM) to predict individual tropical tree biomass as a function of allometric shape variables. Particularly, we examine the capacity of gaussian and gamma error structures to provide the most precise predictions. We show that for a particular species, gamma error structure is superior in terms of predictive power. This study is part of a practical framework; it is meant to be used as a tool for managers who need to precisely estimate the amount of carbon recaptured by tropical tree plantations. Our conclusions could be integrated within a program of carbon emission reduction by land use changes.

Made available in DSpace on 2016-08-31T13:33:39Z (GMT). No. of bitstreams: 1 ClaytonAMO_DISSERT.pdf: 1420692 bytes, checksum: 6fff19d912e4ebade2d582644a6d1364 (MD5) Previous issue date: 2014-02-21 / In this paper, we propose an appropriate genetic algorithm to design state observers for multivariable control systems, which response time meets the specifications previously provided by the user of the system, in terms of the maximum overshoot, and in terms of the settling time. For this, will be designed and evaluated different forms of initialization and different forms of setup the genetic algorithm. Furthermore, we intend to investigate the performance results of this technique in control systems utilizing state observers full order or reduced order. Through this analysis, intend to contribute to the specification of an appropriate genetic algorithm to design state observers for multivariable control systems, by making this an efficient alternative to traditional methods in the literature / Neste trabalho, será proposto um algoritmo genético adequado ao projeto de observadores de estado para sistemas de controle multivariável, cuja resposta temporal atenda às especificações previamente fornecidas pelo usuário do sistema, tanto em termos do máximo sobressinal, quanto em termos do tempo de acomodação. Para isso, serão concebidas e avaliadas diferentes formas de inicialização e diferentes formas de configuração de algoritmo genético. Por outro lado, pretende-se investigar os resultados de desempenho desta técnica em sistemas de controle que utilizem os observadores de estado de ordem plena, ou de ordem reduzida. Por meio desta análise, pretendemos contribuir com a especificação de um algoritmo genético adequado ao projeto de observadores de estado para sistemas de controle multivariável, fazendo-se desta uma alternativa eficiente aos métodos tradicionais presentes na literatura

Made available in DSpace on 2014-12-17T14:56:16Z (GMT). No. of bitstreams: 1 AmandaDOSD_DISSERT.pdf: 3108692 bytes, checksum: 6c24c65f349d3aca5d9122aa78c3b00c (MD5) Previous issue date: 2013-07-26 / A modelagem de processos industriais tem auxiliado na produ??o e minimiza??o de custos, permitindo a previs?o dos comportamentos futuros do sistema, supervis?o de processos e projeto de controladores. Ao observar os benef?cios proporcionados pela modelagem, objetiva-se primeiramente, nesta disserta??o, apresentar uma metodologia de identifica??o de modelos n?o-lineares com estrutura NARX, a partir da implementa??o de algoritmos combinados de detec??o de estrutura e estima??o de par?metros. Inicialmente, ser? ressaltada a import?ncia da identifica??o de sistemas na otimiza??o de processos industriais, especificamente a escolha do modelo para representar adequadamente as din?micas do sistema. Em seguida, ser? apresentada uma breve revis?o das etapas que comp?em a identifica??o de sistemas. Na sequ?ncia, ser?o apresentados os m?todos fundamentais para detec??o de estrutura (Modificado Gram- Schmidt) e estima??o de par?metros (M?todo dos M?nimos Quadrados e M?todo dos M?nimos Quadrados Estendido) de modelos. No trabalho ser? tamb?m realizada, atrav?s dos algoritmos implementados, a identifica??o de dois processos industriais distintos representados por uma planta de n?vel did?tica, que possibilita o controle de n?vel e vaz?o, e uma planta de processamento prim?rio de petr?leo simulada, que tem como objetivo representar um tratamento prim?rio do petr?leo que ocorre em plataformas petrol?feras. A disserta??o ? finalizada com uma avalia??o dos desempenhos dos modelos obtidos, quando comparados com o sistema. A partir desta avalia??o, ser? poss?vel observar se os modelos identificados s?o capazes de representar as caracter?sticas est?ticas e din?micas dos sistemas apresentados nesta disserta??o

Para aplicações de extração de petróleo de poços em terra foi desenvolvido pelo Laboratório de Eletromagnetismo Aplicado (LMAG) da Escola Politécnica da Universidade de São Paulo um protótipo de motor de indução linear tubular (MILT), onde o movimento axial do secundário do motor aciona diretamente a bomba de extração situada no fundo do poço. Numa segunda etapa, foi prevista a substituição dos mancais mecânicos por dois mancais magnéticos ativos (AMBs), que permitem melhor movimentação e praticamente nenhum atrito, reduzindo o desgaste causado por impurezas contidas no petróleo extraído, e consequentemente os esforços de manutenção. Todavia, o protótipo atual possui apenas um mancal magnético, e o outro é mecânico. O presente trabalho apresenta a instalação do segundo mancal magnético ao protótipo do MILT, e propõe realizar o controle do sistema de mancais magnéticos para o MILT, tendo em vista um problema multivariável, onde as posições do secundário do motor em relação aos dois mancais são correlacionadas, bem como as ações de controle sobre os mesmos. O trabalho faz uma revisão do sistema atual com um AMB, abordando sua concepção física, modelagem e o controlador, e tal controlador é replicado para o segundo AMB. Um novo modelo é apresentado, considerando o comportamento multivariável dos dois AMBs, e um sistema de controle robusto multivariável é projetado, através da técnica LQG/LTR. Resultados de simulação do novo controlador são analisados e comparados com os resultados experimentais do controlador atual aplicado aos dois AMBs, e apresentam-se as conclusões. / For onshore oil extraction applications, a tubular linear induction motor (TLIM) prototype was developed by Applied Electromagnetism Laboratory (LMAG) of Escola Politécnica da Universidade de São Paulo, on which the axial movement of the motor secondary drives the suction pump, placed in the down hole of the oil well. In a second step, it was planned to replace the mechanical bearings by two Active Magnetic Bearings (AMB), in order to have better movement and practically no friction, reducing damages caused by impurities in the oil, thus reducing maintenance effort. Nevertheless, the actual prototype has only one AMB, being the other one a mechanical bearing. This paper presents the installation of the second AMB onto TLIM prototype, and a proposal to implement the control algorithm for the TLIM magnetic bearing system, considering now a multivariable problem, where the position of the motor secondary for both AMB are related, as well as control efforts. The present work review the actual system with only one AMB, approaching its physical construction, mathematical model and applied control system; and this control system is applied to the second AMB. A new model is presented, considering the AMB system multivariable behavior, and a multivariable robust control system is then designed, using LQG/LTR approach. Simulation results for the new controller are analyzed and compared to experimental results from the actual controller applied to both AMB, and some conclusions are presented.

Made available in DSpace on 2016-08-17T14:53:16Z (GMT). No. of bitstreams: 1 Leandro Rocha Lopes.pdf: 1075564 bytes, checksum: 01e184ed6d7c65323c0dfc1515da19a3 (MD5) Previous issue date: 2011-04-04 / Due to the increasing of technological development and its associated industrial applications, control design methods to attend high performance requests and reinforcement learning are been developed, not only, to solve new problems, as well as, to improve the performance of implemented controllers in the real systems. The reinforcement learning (RL) and discrete linear quadratic regulator (DLQR) approaches are connected by adaptive dynamic programming (ADP). This connection is oriented to the design of optimal controller for multivariable systems (MIMO). The proposed method for DLQR controllers tuning can been heuristic guidance for biased variations in weighting matrices of instantenous reward. The heuristics performance are evaluated in terms of convergence of heuristic dynamic programming (HDP) and action dependent (AD-HDP) algorithms. The algorithms and tuning are evaluated by the capability to map the plane-Z in MIMO dynamic system of third order. / Em decorrência do crescente desenvolvimento tecnológico e das consequentes aplicações industriais, técnicas de controle de alto desempenho e aprendizado por reforço estão sendo desenvolvidas não só para solucionar novos problemas, mas também para melhorar o desempenho de controladores já implementados em sistemas do mundo real. As abordagens do aprendizado por reforço e do regulador linear quadrático discreto (DLQR) são conectadas pelos métodos de programação dinâmica adaptativa. Esta união é orientada para o projeto de controladores ótimos em sistemas multivariáveis (MIMO). O método proposto para sintonia de controladores DLQR fornece diretrizes para construção de heurísticas polarizadas que são aplicadas na seleção das matrizes de ponderação da recompensa instantânea. Investiga-se o desempenho das heurísticas associadas com a sintonia de controladores lineares discretos e aspectos de convergência que estão relacionados com as variações QR nos algoritmos de programação dinâmica heurística (HDP) e Ação Dependente (ADHDP). Os algoritmos e a sintonia são avaliados pela capacidade em estabelecer a política de controle ótimo que mapeia o plano-Z em um sistema dinãmico multivariável de terceira ordem.