Semi-autonomous uncrewed aerial vehicles (UAVs) are telerobotic operations by definition where the UAV assumes the role of a telerobot and the human assumes the role of a supervisor. All telerobotic operations are susceptible to time delays due to communication, mechanical, and other constraints. Typically, these delays are small and do not affect the telerobotic operation for most of the tasks. However, for long-distance telerobotic operations like interplanetary rovers, deep underwater vehicles, etc. the delays can be so significant that they can render the entire operation void. This dissertation investigates the use of a novel heterogeneous stereo-vision system to mitigate the effects of time delays in a UAV-based visual interface presented to a human operator. The heterogeneous stereo-vision system consists of an omnidirectional camera and a pan-tilt-zoom camera. Two predictive display setups were developed that modify the delayed video imagery that would otherwise be presented to the operator in a way that provides an almost immediate visual response to the operator's control actions. The usability of the system is determined through human performance testing with and without the predictive algorithms. The results indicate that the predictive algorithm allows more efficient, accurate, and user-friendly operation. The second half of the dissertation deals with improving the performance of the predictive display and expanding the concept of the prediction from a stationary gimbal-camera system to a moving 6 DoF aircraft. Specifically, it talks about a novel extended Kalman filter (EKF)-based nonlinear predictor – the extended Kalman predictor (EKP) – and compares its performance with two linear predictors, the Smith predictor (SP) and the Kalman predictor (KP). This dissertation provides the mathematical formulation of the EKP, as well as the two linear predictors, and describes their use with simulated flight data obtained using a nonlinear motion model for a small, fixed-wing UAV. The EKP performs comparably to the KP when the aircraft motion experiences small perturbations from a nominal trajectory, but the EKP outperforms the KP for larger excursions. The SP performs poorly in every case. / Doctor of Philosophy / Semi-autonomous uncrewed aerial vehicles (UAVs) are telerobotic operations by definition where the aerial vehicle assumes the role of a telerobot and the human assumes the role of a supervisor. This dissertation addresses the challenges posed by time delays in uncrewed aerial vehicle operations, particularly for long-distance operations such as interplanetary exploration and deep-sea missions. It investigates the use of a novel heterogeneous stereo-vision system to mitigate these delays, providing operators with nearly real-time visual feedback. Human performance testing confirms the predictive algorithm allows more efficient, accurate, and user-friendly operation. Additionally, the dissertation presents advancements in the predictive display performance for moving UAVs with six degrees of freedom. It introduces a novel extended Kalman predictor and compares it to traditional linear predictors like the Smith predictor and the Kalman predictor using simulated flight data. The extended Kalman predictor demonstrates superior performance for larger deviations from trajectory, highlighting its effectiveness in predicting the motion of an aircraft when there are time delays present.

With the rising popularity of ROVs and other UV solutions, more robust and high performance controllers have become a necessity. A model of the ROV or UV can be a valuable tool during control synthesis. The main objective of this thesis was to use a model in design and development of controllers for an ROV. In this thesis, an ROV from Blue Robotics was used. The ROV was equipped with 6 thrusters placed such that the ROV was capable of moving in 6-DOFs. The ROV was further equipped with an IMU, two pressure sensors and a magnetometer. The ROV platform was further developed with EKF-based sensor fusion, a control system and manual control capabilities. To model the ROV, the framework of Fossen (2011) was used. The model was estimated using two different methods, the prediction-error method and an EKF-based method. Using the prediction-error method, it was found that the initial states of the quaternions had a large impact on the estimated parameters and the overall fit to validation data. A Kalman smoother was used to estimate the initial states. To circumvent the problems with the initial quaternions, an \abbrEKF was implemented to estimate the model parameters. The EKF estimator was less sensitive to deviations in the initial states and produced a better result than the prediction-error method. The resulting model was compared to validation data and described the angular velocities well with around 70 % fit. The estimated model was used to implement feedback linearisation which was used in conjunction with an attitude controller and an angular velocity controller. Furthermore, a depth controller was developed and tuned without the use of the model. Performance of the controllers was tested both in real tests and simulations. The angular velocity controller using feedback linearisation achieved good reference tracking. However, the attitude controller could not stabilise the system while using feedback linearisation. Both controllers' performance could be improved further by tuning the controllers' parameters during tests. The fact that the feedback linearisation made the ROV unstable, indicates that the attitude model is not good enough for use in feedback linearisation. To achieve stability, the magnitude of the parameters in the feedback linearisation were scaled down. The assumption that the ROV's center of rotation coincides with the placement of the ROV's center of gravity was presented as a possible source of error. In conclusion, good performance was achieved using the angular velocity controller. The ROV was easier to control with the angular velocity controller engaged compared to controlling it in open loop. More work is needed with the model to get acceptable performance from the attitude controller. Experiments to estimate the center of rotation and the center of gravity of the ROV may be helpful when further improving the model.

Les entraîneurs en sports acrobatiques disposent de peu d’outils permettant d’améliorer leur compréhension des saltos vrillés et la performance des athlètes. L’objectif de ce mémoire était de développer un environnement graphique de simulation numérique réaliste et utile des acrobaties aériennes. Un modèle composé de 17 segments et de 42 degrés de liberté a été développé et personnalisé à une athlète de plongeon. Un système optoélectronique échantillonné à 300 Hz a permis l’acquisition de huit plongeons en situation réelle d’entraînement. La cinématique articulaire reconstruite avec un filtre de Kalman étendu a été utilisée comme entrée du modèle. Des erreurs quadratiques moyennes de 20° (salto) et de 9° (vrille) entre les performances simulées et réelles ont permis de valider le modèle. Enfin, une formation basée sur le simulateur a été offerte à 14 entraîneurs en sports acrobatiques. Une augmentation moyenne de 11 % des résultats aux questionnaires post-test a permis de constater le potentiel pédagogique de l’outil pour la formation. / Coaches need tools to better understand the mechanics of twisting somersaults and improve their knowledge and their athletes’ performance. The aim of this thesis was to provide them with a computer simulation model of aerial movements. An elite diver was modelled as a 17-segment 42-degree of freedom angle-driven model. The model was personalised to the diver so that simulation outputs could be compared with her actual performance. Input data were recorded by a 17-camera motion capture system sampled at 300 Hz. The joint angle time histories were reconstructed using an extended Kalman filter. The model was successfully evaluated and shown to produce realistic movements, with overall root-mean-square error of 20° (somersault) and 9° (twist) between reconstructed body kinematics and the corresponding simulations for eight dives. Finally, a workshop based on the simulation was offered to coaches and showed potential to improve their knowledge since the mean post-test result was increased by 11 %.

La commande sans capteur mécanique de la machine synchrone à aimants permanents est un sujet largement répandu dont les plus grandes difficultés connues, quel que soit l’observateur utilisé, sont celui du démarrage à vitesse nulle et plus largement de la commande aux basses vitesses, et celui du rejet des fortes perturbations du couple. Afin d’y faire obstacle, diverses adaptations des algorithmes d’observateur ont été proposées afin d’améliorer le comportement de la machine en commande sans capteur. Par ailleurs, il est couramment admis que les déchets de tension produit par l’onduleur sont nuisibles à l’observation de la position, les tensions de référence étant légèrement différentes des tensions appliquées aux enroulements de la machine. Quelques propositions apparaissent dans certaines publications notamment en établissant un algorithme de compensation. C’est ainsi que les travaux de cette thèse portent sur cette thématique, celle d’améliorer la commande sans capteur dans les situations d’observabilité difficile en proposant une solution originale afin de faire correspondre au mieux les tensions appliquées à la machine et les tensions de référence utiles à l’observateur. Les résultats montrent que la solution proposée et largement analysée améliore considérablement le comportement de la machine en commande aux basses vitesses et en rejet de perturbation, tant en régime permanent qu’en régime transitoire ; une analyse de Fourier des courants mesurés atteste l’efficacité de la méthode et une analyse des grandeurs observées par la statistique descriptive met en lumière l’intérêt de l’algorithme. Nous montrons ainsi que la solution proposée permet d’observer la vitesse et la position en deçà de la vitesse mécanique de 15 rad/s alors que la commande est instable en deçà de 20 rad/s quand la solution n’est pas mise en œuvre. Un constat similaire apparaît en rejet de perturbation. D’autres résultats montrent que l’observation à plus basse vitesse est entachée d’une perturbation liée à un couple pulsatoire dont l’origine peut être le couple de détente, lequel n’est pas pris en compte par le modèle de la machine. / The sensorless control of the permanent magnet synchronous machine is a subject widely spread. Two great difficulties are known; (i) the start at nil initial speed and more generally the control at very low speed whatever the observer used and (ii) the high torque disturbance rejection. In order to hinder these difficulties numerous modifications of observer algorithms were proposed to improve the performances of the permanent magnet synchronous machine sensorless control. Moreover, we admit commonly that the drop voltages due to the inverter are prejudicial to the position estimated, because the difference between the voltage reference transmitted to the PWM (pulse width modulation) and the motor winding voltage is not negligible at low speed and low load torque. According to the literature, several papers propose some solutions by compensation algorithms and voltage estimator in particular. So, the goal of this thesis is to estimate the winding voltage and to apply the state observer by Extended Kalman Filtering to improve more finely the sensorless control. We propose an original solution to estimate the voltage references which is applied to the observer. Numerous experimental results show the attractive effects in marked contrast to the sensorless control results without estimation of the winding voltages. The results of sensorless control show that the solution proposed which widely analysed improves significantly the estimation errors of the motor running in low speed range and low torque disturbances range. Fourier analyses and statistic data obtained in steady state speed and results during the transient response indicate complementary results and highlight the interest of the estimation algorithm. Our study brings out that the estimation error reduction allows to running the motor at mechanical speed short of 15 rad/s. In the other hand, the system is instable with speed short of 20 rad/s if the voltage references are used by the observer rather than the estimation voltages. The same improvement appears in disturbance rejection. Other results show that the estimated position errors at lower speed increases in spite of the estimation algorithm. In fact, the torque disturbances are dominant at low speed, low load torque and are harmful to control the electromagnetic torque.

A demanda por mais flexibilidade nas fábricas e serviços originou um aumento no volume de operações internas de carga e descarga, devido à maior diversidade dos elementos transportados. Logo, na busca por um fluxo de materiais mais eficiente, as empresas passaram a investir em soluções tecnológicas, entre elas, o uso de Automated Guided Vehicles (AGVs), por conta do custo mais atrativo e do avanço em relação aos primeiros AGVs, que até então dependiam de uma infraestrutura adicional para suportar a navegação. Muitos AGVs modernos possuem movimentação livre e são orientados por sistemas que utilizam sensores para interpretar o ambiente, sendo assim, tornar os AGVs autônomos despertou o interesse de pesquisadores na área de robótica móvel para o desenvolvimento de sistemas capazes de auxiliar e coordenar a navegação. Novas técnicas de localização, tal como a localização baseada em marcadores reflexivos, e a construção de armazéns com layouts estruturados para a navegação viabilizaram o uso de AGVs autônomos, entretanto sua utilização em armazéns existentes ainda é um desafio. Neste contexto, o Laboratório de Robótica Móvel (LabRom) do Grupo de Mecatrônica da EESC/USP, através do projeto do Armazém Inteligente, tem pesquisado os problemas de: roteamento, gerenciamento das baterias, navegação e auto-localização. Robôs autônomos precisam de um sistema de auto-localização eficiente e preciso para navegar com segurança, o qual depende de um mapa e da interpretação do ambiente utilizando sensores embarcados. Para alcançar esse objetivo este trabalho propõe um Sistema de Auto-localização baseado no Extended Kalman Filter (EKF) como solução. O sistema, desenvolvido em linguagem C, interage com outros dois sistemas: roteamento e navegação e foi implementado em um armazém simulado utilizando o software Player/Stage, mostrando ser confiável no fornecimento de uma estimativa de localização baseada em odometria e landmarks com localização conhecida. O sistema foi novamente testado utilizando a odometria de um robô móvel Pioneer P3-AT e os valores de um sensor de medição laser 2D SICK LMS200 extraídos de um ambiente indoor real. Para este teste foi construído um feature-based map a partir de um desenho de planta baixa no formato CAD e utilizou-se o algoritmo de segmentação Iterative End-Point Fit (IEPF) para interpretar o ambiente. Os resultados mostraram que as vantagens oferecidas pelas características padronizadas de um ambiente indoor, semelhante a um armazém, podem viabilizar o uso do Sistema de Auto-localização em armazéns existentes. / The demand for more flexibility in factories and services led to an increase in the volume of internal operations of loading and unloading, due to the greater diversity of elements transported. Hence, in the search for a more efficient materials flow, companies went to invest in technology solutions, among them, the use of Automated Guided Vehicles (AGVs), on account of the more attractive cost and improvement over the first AGVs, which hitherto depended of an additional infrastructure to support navigation. Many modern AGVs have free movement and are guided by systems that use sensors to interpret the environment, thus make AGVs autonomous aroused the interest of researchers in the mobile robotics field to development of systems able to assist and coordinate the navigation. New localization techniques, such as localization based on reflective markers, and the construction of warehouses with structured layouts for navigation did feasible the use of autonomous AGVs, however its use in existing warehouses is still a challenge. In this context, the Mobile Robotics Lab (LabRom) of the Mechatronics Group of EESC/USP, through the Intelligent Warehouse Project, has researched the problems: routing, battery management, navigation and self-localization. Autonomous robots need an efficient and accurate self-localization system to safely navigate, which depends on one map and of the interpretation of the environment using embedded sensors. To achieve this goal, this work proposes a Self-Localization System based on the Extended Kalman Filter (EKF) as a solution. The system, developed in C language, interacts with two other systems: routing and navigation and was implemented in a simulated warehouse using the Player/Stage software, showing to be reliable in providing an estimative of localization based on odometry and landmarks with known localization. The system was again tested using the odometry of mobile robot Pioneer P3-AT and the values of a 2D Laser Rangefinder SICK LMS200 extracted from a real indoor environment. For this test was built a feature-based map from a floor plan design in CAD format and was used the segmentation algorithm Iterative End-Point Fit (IEPF) to interpret the environment. The results showed that the advantages offered by the standard features of indoor environment, like a warehouse, can enable the use of the Self-Localization System on the existing warehouses.

Neste trabalho, é abordado o problema da navegação de um veículo submarino autônomo. São propostos estimadores de estado que realizam fusão sensorial baseada em Filtro Estendido de Kalman. Esses estimadores de estado empregam as medidas dos seguintes sensores: uma unidade de medição inercial, um sensor de velocidade por efeito Doppler, um profundímetro e uma bússola. Primeiramente foi projetado um estimador de estados para o AUV Pirajuba, onde a estimação da orientação do veículo é realizada de forma desacoplada à estimação da velocidade e posição do veículo. Em seguida, foram desenvolvidos dois estimadores de estado que estimam orientação, velocidade e profundidade do veículo de forma acoplada. Para o projeto e testes dos estimadores mencionados anteriormente, foi empregada uma base de dados contendo um registro de medições reais dos sensores do veículo submarino autônomo Pirajuba, durante testes de campo no lago de uma represa. Os resultados dos testes validaram os estimadores de estado propostos nesse trabalho. Por último, foi realizada uma análise comparativa dos estimadores de estado mencionados. / This work concerns the navigation problem of an autonomous underwater vehicle. Some state estimators using sensorial fusion were proposed, the sensorial fusion is based in an Extended Kalman Filter. The state estimators are fed by measurements of the following sensors: an inertial measurements unit, a velocity sensor by Doppler effect, a depthmeter and a compass. In the first version of the EKF algorithm, the vehicles attitude estimation was decoupled from the vehicle velocity estimation. The second version considers the coupling between linear velocity and the attitude in the vehicle reference frame, taking the velocity reading for correction of the filter estimates. Finally, in the third version, the coupling between position and attitude is also considered, but the correction of the filters estimates is based on the depth readings. Experiments for supporting the design and validation of the navigation algorithms were based on a database constructed with motion measurements during the AUV maneuvers in the north coast of Sao Paulo, and the Guarapiranga lake in the São Paulo city. This work presents a comparative analysis of those algorithms.

Coordenação de robôs móveis é um tópico importante de pesquisa dado que existem tarefas que podem ser desenvolvidas de forma mais eficiente e com menor custo por um grupo de robôs do que por um só robô. Nesta dissertação é apresentado um estudo sobre coordenação de robôs móveis para o problema de navegação em ambientes externos. Para isso, foi desenvolvido um sistema de localização utilizando os dados de odometria e do receptor GPS, e um sistema de desvio de obstáculos para planejar a trajetória livre de obstáculos. Os movimentos coordenados foram realizados em função de um líder e qualquer robô da formação pode assumir a liderança. A liderança é assumida pelo robô que ultrapassar a distância mínima a um obstáculo. Movimentos estáveis são gerados através de uma lei de controle descentralizada baseada nas coordenadas dos robôs. Para garantir a estabilidade da formação quando há alternância de líder ou remoção de robôs, foi feito controle tolerante a falhas para um grupo de robôs móveis. O controle tolerante a falhas é baseado em controle H \'INFINITO\' por realimentação da saída de sistemas lineares sujeitos a saltos Markovianos para garantir a estabilidade da formação quando um dos robôs é perdido durante o movimento coordenado. Os resultados do sistema de localização mostram que o uso de filtro robusto para a fusão de dados produz uma melhor estimativa da posição do robô móvel. Os resultados também mostram que o sistema de desvio de obstáculos é capaz de gerar uma trajetória livre de obstáculos em ambientes desconhecidos. E por fim, os resultados do sistema de coordenação mostram que o grupo de robôs mantém a formação desejada percorrendo a trajetória de referência na presença de distúrbios ou quando um robô sai da formação. / Coordination of mobile robots is an important topic of research because there are tasks that may be too difficult for a single robot to perform alone, these tasks can be performed more efficiently and cheaply by a group of mobile robots. This dissertation presents a study on the coordination of mobile robots to the problem of navigation in outdoor environments. To solve this problem, a localization system using data from odometry and GPS receiver, and an obstacle avoidance system to plan the collision-free trajectory, were developed. The coordinated motions are performed by the robots that follow a leader, and any robot of the formation can assume the leadership. The leadership is assumed by a robot when it exceeds the threshold distance to an obstacle. Stable motions are generated by a decentralized control law based on the robots coordinates. To ensure the stability formation when there is alternation of leader or one of the robots is removed, we made a fault tolerant control for a group of mobile robots. The fault tolerant approach is based on output feedback H \'INFINITE\' control of Markovian jump linear systems to ensure stability of the formation when one of the robots is lost during the coordinated motion. The results of the localization system show that the use of robust filter for data fusion produces a better estimation of the mobile robots position. The results also show that the obstacle avoidance system is capable of generating a path free from obstacles in unknown environments. Finally, the results of the coordination system show that the group of robots maintain the desired formation along the reference trajectory in the presence of disturbance or removal of one of them.

La pile à combustible (PàC) est une source d’énergie qui produit de l’électricité à partir de l’hydrogène et de l’oxygène.Elles sont très prometteuses pour la production d'énergie électrique. Néanmoins, la PàC souffre encore d’imperfections limitant ainsi sa commercialisation à grande échelle, tout particulièrement pour les applications de transport.C’est pourquoi, l’hybridation des différentes sources d’énergies est devenue une réalité pour les applications non-stationnaires telles que les véhicules tout électriques.Cependant ces applications nécessitent des solutions de gestion de l’énergie fiables prenant en compte toutes les contraintes du système électrique hybride.Par conséquent, le développement de plateforme de validation est nécessaire.Dans ce contexte, le Hardware In the Loop (HIL) est une technique très prometteuse, où une partie d’un système réel peut être remplacée par un système virtuel tout en respectant la communication entre ces sous-systèmes physiques et virtuels.Ce mémoire détaille des modèles dynamiques d'une pile à combustible échangeuse de proton (PEMFC) hybridée à des supercondensateurs.Par ailleurs, on détaille la gestion d’énergie entre ces deux sources, ainsi que le pronostic de la pile basé d’une part d’un filtre de Kalman étendu (EKF) pour l’estimation de l’état de santé (SoH) réel de la pile, et d’autre part, de la méthode Inverse First Order Reliability Method (IFORM) en vue d’estimer la durée de vie utile restante de la pile, tout cela dans une approche Hardware-In-The-Loop (HIL). / The fuel cell is a source of energy that generates electricity from hydrogen and oxygen.They are very promising candidates for the production of electric power.Nevertheless, the fuel cell still suffers from imperfections limiting its commercialization on a full scale, in particular for transport applications.This is the reason why, hybridization of different energy sources has become a reality for non-stationary applications such as all-electric vehicles.However, these applications require reliable energy management solutions that take into account all the constraints of the hybrid electrical system.Therefore, the development of validation platform is necessary.In this context, the Hardware In the Loop (HIL) is a very promising technique, where part of a real system can be replaced by a virtual system while respecting the communication between these physical and virtual subsystems.This document details the dynamic models of a proton exchange membrane fuel cell (PEMFC) associated with supercapacitors.Furthermore, the energy management between these two sources and the prognostic of the fuel cell composed of a extenced Kalman Filter filter (EKF) for the estimation of the real state of health (SoH) of the stack and, on the other hand, of the Inverse First Order Reliability Method (IFORM) in order to estimate the remaining useful life of the stack, all implemented in an FPGA control board in a Hardware-In-The-Loop (HIL) context.

L'objectif du travail réalisé dans le cadre de cette thèse est de montrer l'intérêt d'utiliser les FPGAs (Field Programmable Gate Array) comme support pour l'implantation d'algorithmes complexes dédiés à la commande de machines électriques. Pour ce faire, une commande sans capteur mécanique utilisant un filtre de Kalman étendu et basée sur FPGA est réalisée. Cette commande est destinée à piloter une machine synchrone à pôles saillants. Le modèle d-q de la machine basé sur l'approximation d'inertie infinie est implanté. L'ordre du Filtre de Kalman est donc égal à 4 et la complexité totale de la boucle de régulation est évaluée à près de 700 opérations arithmétiques (dont plus de 53% de multiplications). Les apports des solutions FPGAs en termes de performances de contrôle et en termes de capacité d'intégration sont quantifiés.En terme de performances de contrôle, il a été démontré qu'en utilisant de telles solutions matérielles, le temps de calcul est très réduit (de l'ordre de 5µs, 5% de la période d'échantillonnage). Cette rapidité de calcul permet d'avoir un contrôle quasi-instantané ce qui améliore la bande passante de la boucle de régulation. A ce sujet, une comparaison avec les performances obtenues avec une solution logicielle telle que le DSP est effectuée. Dans les deux cas, le comportement dynamique de la boucle de régulation s de vitesse ans capteur est quantifié.En termes de capacité d'intégration, il est possible de développer une architecture commune qui peut être adaptée à plusieurs systèmes. A titre d'exemple, il est possible de développer un filtre de Kalman sur un même FPGA capable d'estimer les grandeurs de plusieurs systèmes sans pour autant affecter les performances de contrôle. En outre, une méthodologie de développement dédiée à de tels algorithmes complexes est proposée. Il s'agit là d'une adaptation des méthodologies proposées dans des travaux de thèse précédents, [62] et [63]. En effet, une étape de spécification préliminaire du système ainsi que des procédures d'optimisation supplémentaires y sont introduites. Ces dernières sont particulièrement nécessaires dans le cas de commandes complexes et permettent une adéquation entre l'algorithme développé et l'architecture FPGA correspondante. De plus, cette méthodologie a été organisée de façon à distinguer l'étape du développement de l'algorithme et l'étape du développement de l'architecture FPGA. Un état de l'art sur les technologies FPGA est également proposé. La structure interne des FPGAs récents est décrite. Leur contribution dans le domaine de la commande des machines électriques est quantifiée. Les différentes étapes de la méthodologie de développement sont présentées. Le développement d'une commande numérique (basée sur FPGA) d'une machine synchrone à aimant permanent associée à un capteur de position Resolver est par la suite traité. Cette application s'inscrit dans un contexte avionique où l'objectif était d'avoir une solution FPGA hautement intégrée. Pour ce faire, le FPGA Actel Fusion est utilisé. Ce composant intègre un convertisseur analogique numérique. La commande, le traitement des signaux Resolver ainsi que la conversion analogique numériques sont implantés sur le même composant.En ce qui concerne la commande sans capteur basée sur le filtre de Kalman étendu, il a été décidé de structurer les chapitres correspondants à travers la méthodologie de développement proposée. Ainsi, la phase de spécification préliminaire du système, la phase du développement de l'algorithme, la phase du développement de l'architecture FPGA et la phase d'expérimentation sont séparément traitées. Durant la phase d'expérimentation, la procédure «Hardware-In-the-Loop (HIL)» est incluse afin de valider le fonctionnement de l'architecture développée une fois la phase d'implantation physique achevée. / The aim of this thesis is to present the interest of using Field Programmable Gate Array (FPGA) devices for the implementation of complex AC drive controllers. The case of a sensorless speed controller using the Extended Kalman Filter (EKF) has been chosen and applied to a Salient Synchronous Machine (SSM). The d-q model based on the infinite inertia hypothesis has been implemented. The corresponding EKF order is then equal to 4 and the complexity of the whole sensorless controller is equal to 700 arithmetic operations (more than 53% of multiplications). The contribution of FPGAs in this field has been quantified in terms of control performances and in terms of system integration. In terms of control performances, the proposed FPGA-based solution ensures a short execution time which is around 5µs (5% of the sampling period). This treatment fastness ensures a quasi-instantaneous control which improves the control bandwidth. To this purpose, a comparison with a software DSP-based solution is made. The dynamic behavior and the influence of the execution time, in both cases, on the control bandwidth have been quantified. In terms of integration capacity, it is possible to implement a generic FPGA architecture that can be adapted to the control of several systems. Thus, it is possible to develop a common EKF architecture that is able to estimate variables from many systems without affecting the control performances.In addition, a design methodology adapted to such complex controllers has been proposed. The particularity of this updated methodology, compared to the previous ones ([62], [63]), is to provide an enlarged set of steps starting from the preliminary system specification to the ultimate experimentation. Optimization procedures have also been introduced. These optimizations are necessary in case of complex controllers and lead to the adequation between the developed algorithm and the corresponding hardware FPGA architecture. A state of the art FPGA technology is also presented. The internal structure of the recent devices and their corresponding technology are discussed. Their contribution in the field of AC drive applications is quantified. An in-depth presentation of the proposed design methodology is made.Besides, the development of a fully integrated FPGA-based controller for a Permanent Magnet Synchronous Machine (PMSM) associated with a Resolver sensor is presented. This controller has been developed in for an aircraft application where the main objective was to develop a fully integrated FPGA solution. The Actel Fusion FPGA device has been used. This device integrates an Analog to Digital Converter (ADC). The current controller, the Resolver Processing Unit (RPU) and the analog to digital conversion are implemented within the same device. When it comes to the sensorless controller, the corresponding chapters have been structured according to the presented design methodology: the preliminary system specification, the algorithm development, the FPGA architecture development and finally the experimentation. The latter includes Hardware-In-the-Loop (HIL) tests and the final experimental validation.

A demanda por mais flexibilidade nas fábricas e serviços originou um aumento no volume de operações internas de carga e descarga, devido à maior diversidade dos elementos transportados. Logo, na busca por um fluxo de materiais mais eficiente, as empresas passaram a investir em soluções tecnológicas, entre elas, o uso de Automated Guided Vehicles (AGVs), por conta do custo mais atrativo e do avanço em relação aos primeiros AGVs, que até então dependiam de uma infraestrutura adicional para suportar a navegação. Muitos AGVs modernos possuem movimentação livre e são orientados por sistemas que utilizam sensores para interpretar o ambiente, sendo assim, tornar os AGVs autônomos despertou o interesse de pesquisadores na área de robótica móvel para o desenvolvimento de sistemas capazes de auxiliar e coordenar a navegação. Novas técnicas de localização, tal como a localização baseada em marcadores reflexivos, e a construção de armazéns com layouts estruturados para a navegação viabilizaram o uso de AGVs autônomos, entretanto sua utilização em armazéns existentes ainda é um desafio. Neste contexto, o Laboratório de Robótica Móvel (LabRom) do Grupo de Mecatrônica da EESC/USP, através do projeto do Armazém Inteligente, tem pesquisado os problemas de: roteamento, gerenciamento das baterias, navegação e auto-localização. Robôs autônomos precisam de um sistema de auto-localização eficiente e preciso para navegar com segurança, o qual depende de um mapa e da interpretação do ambiente utilizando sensores embarcados. Para alcançar esse objetivo este trabalho propõe um Sistema de Auto-localização baseado no Extended Kalman Filter (EKF) como solução. O sistema, desenvolvido em linguagem C, interage com outros dois sistemas: roteamento e navegação e foi implementado em um armazém simulado utilizando o software Player/Stage, mostrando ser confiável no fornecimento de uma estimativa de localização baseada em odometria e landmarks com localização conhecida. O sistema foi novamente testado utilizando a odometria de um robô móvel Pioneer P3-AT e os valores de um sensor de medição laser 2D SICK LMS200 extraídos de um ambiente indoor real. Para este teste foi construído um feature-based map a partir de um desenho de planta baixa no formato CAD e utilizou-se o algoritmo de segmentação Iterative End-Point Fit (IEPF) para interpretar o ambiente. Os resultados mostraram que as vantagens oferecidas pelas características padronizadas de um ambiente indoor, semelhante a um armazém, podem viabilizar o uso do Sistema de Auto-localização em armazéns existentes. / The demand for more flexibility in factories and services led to an increase in the volume of internal operations of loading and unloading, due to the greater diversity of elements transported. Hence, in the search for a more efficient materials flow, companies went to invest in technology solutions, among them, the use of Automated Guided Vehicles (AGVs), on account of the more attractive cost and improvement over the first AGVs, which hitherto depended of an additional infrastructure to support navigation. Many modern AGVs have free movement and are guided by systems that use sensors to interpret the environment, thus make AGVs autonomous aroused the interest of researchers in the mobile robotics field to development of systems able to assist and coordinate the navigation. New localization techniques, such as localization based on reflective markers, and the construction of warehouses with structured layouts for navigation did feasible the use of autonomous AGVs, however its use in existing warehouses is still a challenge. In this context, the Mobile Robotics Lab (LabRom) of the Mechatronics Group of EESC/USP, through the Intelligent Warehouse Project, has researched the problems: routing, battery management, navigation and self-localization. Autonomous robots need an efficient and accurate self-localization system to safely navigate, which depends on one map and of the interpretation of the environment using embedded sensors. To achieve this goal, this work proposes a Self-Localization System based on the Extended Kalman Filter (EKF) as a solution. The system, developed in C language, interacts with two other systems: routing and navigation and was implemented in a simulated warehouse using the Player/Stage software, showing to be reliable in providing an estimative of localization based on odometry and landmarks with known localization. The system was again tested using the odometry of mobile robot Pioneer P3-AT and the values of a 2D Laser Rangefinder SICK LMS200 extracted from a real indoor environment. For this test was built a feature-based map from a floor plan design in CAD format and was used the segmentation algorithm Iterative End-Point Fit (IEPF) to interpret the environment. The results showed that the advantages offered by the standard features of indoor environment, like a warehouse, can enable the use of the Self-Localization System on the existing warehouses.