With the recent advances in the field of unmanned aerial vehicles, many applications have been identified. In tasks that require high-payload-to-weight ratios, flight times in the order of days, reduced noise and/or hovering capabilities, lighter-than-air vehicles present themselves as a competitive platform compared to fixed-wing and rotor based vehicles. The limiting factor in their widespread use in autonomous applications comes from the complexity of the control task. The so-called airships are highly-susceptible to aerodynamic forces and pose complex nonlinear system dynamics that complicate their modeling and control. Model-free control lends itself well as a solution to this type of problem, as it derives its control policies using input-output data, and can therefore learn complex dynamics and handle uncertain or unknown parameters and disturbances. In this work, two multi-input multi-output algorithms are presented on the basis of optimal control theory. Leveraging results from reinforcement learning, a single layer, partially connected neural network is formulated as a value function appropriator in accordance with Weierstrass higher-order approximation theorem. The so-called critic-network is updated using gradient descent methods on the mean-squared error of the temporal difference equation. In the single-network controller, the control policy is formulated as a closed form equation that is parameterized on the weights of the critic-network. A second controller is proposed that uses a second single-layer partially connected neural network, the actor-network, to calculate the control action. The actor-network is also updated using gradient descent on the squared error of the temporal difference equation. The controllers are employed in a highly realistic simulation airship model in nominal conditions and in the presence of external disturbances in the form of turbulent wind. To verify the validity and test the sensitivity of the algorithms to design parameters (the initialization of certain terms), ablation studies are carried out with multiple initial parameters. Both of the proposed algorithms are able to track the desired waypoints in both the nominal and disturbed flight tests. Furthermore, the performance of the controllers is compared to a modern, state-of-the-art multi-input multi-output controller. The two proposed controllers outperform the comparison controller in all but one flight test, with up to four fold reduction in the integral absolute error and integral time absolute error metrics. On top of the quantitative improvements seen in the proposed controllers, both controllers demonstrate a reduction in system oscillation and actuator chattering with respect to the comparison algorithm.

Yes / This paper studies the predictive ability of corridor implied volatility (CIV) measure. It is motivated by the fact that CIV is measured with better precision and reliability than the model-free implied volatility due to the lack of liquid options in the tails of the risk-neutral distribution. By adding CIV measures to the modified GARCH specifications, the out-of-sample predictive ability of CIV is measured by the forecast accuracy of conditional volatility. It finds that the narrowest CIV measure, covering about 10% of the RND, dominate the 1-day ahead conditional volatility forecasts regardless of the choice of GARCH models in high volatile period; as market moves to non volatile periods, the optimal width broadens. For multi-day ahead forecasts narrow and mid-range CIV measures are favoured in the full sample and high volatile period for all forecast horizons, depending on which loss functions are used; whereas in non turbulent markets, certain mid-range CIV measures are favoured, for rare instances, wide CIV measures dominate the performance. Regarding the comparisons between best performed CIV measures and two benchmark measures (market volatility index and at-the-money Black–Scholes implied volatility), it shows that under the EGARCH framework, none of the benchmark measures are found to outperform best performed CIV measures, whereas under the GARCH and NAGARCH models, best performed CIV measures are outperformed by benchmark measures for certain instances.

This dissertation presents a new 2D ultrasound-based visual servoing method. The main goal is to automatically guide a robotized 2D ultrasound probe held by a medical robot in order to reach a desired cross-section ultrasound image of an object of interest. This method allows to control both the in-plane and out-of-plane motions of a 2D ultrasound probe. It makes direct use of the 2D ultrasound image in the visual servo scheme, where the feed-back visual features are combinations of image moments. To build the servo scheme, we develop the analytical form of the interaction matrix that relates the image moments time variation to the probe velocity. That modeling is theoretically verified on simple shapes like spherical and cylindrical objects. In order to be able to automatically position the 2D ultrasound probe with respect to an observed object, we propose six relevant independent visual features to control the 6 degrees of freedom of the robotic system. Then, the system is endowed with the capability of automatically interacting with objects without any prior information about their shape, 3D parameters, nor 3D location. To do so, we develop on-line estimation methods that identify the parameters involved in the built visual servo scheme. We conducted both simulation and experimental trials respectively on simulated volumetric objects, and on both objects and soft tissues immersed in a water-filled tank. Successful results have been obtained, which show the validity of the developed methods and their robustness to different errors and perturbations especially those inherent to the ultrasound modality. Keywords: Medical robotics, visual servoing, 2D ultrasound imaging, kinematics modeling, model-free servoing.

The model-free analysis of NMR relaxation data, which is widely used for the study of protein dynamics, consists of the separation of the Brownian rotational diffusion from internal motions relative to the diffusion frame and the description of these internal motions by amplitude and timescale. Through parametric restriction and the addition of the Rex parameter a number of model-free models can be constructed. The model-free problem is often solved by initially estimating the diffusion tensor. The model-free models are then optimised and the best model is selected. Finally, the global model of all diffusion and model-free parameters is optimised. These steps are repeated until convergence. This thesis will investigate all aspects of the model-free data analysis chain. (For complete abstract open document)

Biological membranes form a protective barrier around cells and cellular compartments. A broad range of biochemical processes occur in or at membranes demonstrating that they are not only of structural but also of functional importance. One important class of membrane proteins are membrane-associated glycosyltransferases. WaaG is a representative of this class of proteins; its function is to catalyze one step in the synthesis of lipopolysaccharides, which are outer membrane lipids found in Gram-negative bacteria. To study protein-membrane complexes by biophysical methods, one must employ membrane mimetics, i.e. simplifications of natural membranes. One type of membrane mimetic often employed in solution-state NMR is small isotropic bicelles, obloid aggregates formed from a lipid bilayer that is dissolved in aqueous solvent by detergent molecules that make up the rim of the bicelle. In this thesis, fast dynamics of lipid atoms in bicelles containing lipid mixtures that faithfully mimic plant and bacterial membranes were investigated by NMR relaxation. Lipids were observed to undergo a broad range of motions; while the glycerol backbone was found to be rigid, dynamics in the acyl chains were much more rapid and unrestricted. Furthermore, by employing paramagnetic relaxation enhancements an ‘atomic ruler’ was developed that allows for measurement of the immersion depths of lipid carbon atoms. WaaG is a membrane-associated protein that adopts a GT-B fold. For proteins of this type, it has been speculated that the N-terminal domain anchors tightly to the membrane via electrostatic interactions, while the anchoring of the C-terminal domain is weaker. Here, this model was tested for WaaG. It was found by a set of circular dichroism, fluorescence, and NMR techniques that an anchoring segment located in the N-terminal domain termed MIR-WaaG binds electrostatically to membranes, and the structure and localization of isolated MIR-WaaG inside micelles was determined. Full-length WaaG was also found to bind membranes electrostatically. It senses the surface charge density of the membrane whilst not discriminating between anionic lipid species. Motion of the C-terminal domain could not be observed under the experimental conditions used here. Lastly, the affinity of WaaG to membranes is lower than expected, indicating that WaaG should not be classified as a monotopic membrane protein but rather as a peripheral one. / <p>At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 5: Manuscript.</p>

This thesis addresses visual tracking of a non-cooperative as well as a partially cooperative satellite, to enable close-range rendezvous between a servicer and a target satellite. Visual tracking and estimation of relative motion between a servicer and a target satellite are critical abilities for rendezvous and proximity operation such as repairing and deorbiting. For this purpose, Lidar has been widely employed in cooperative rendezvous and docking missions. Despite its robustness to harsh space illumination, Lidar has high weight and rotating parts and consumes more power, thus undermines the stringent requirements of a satellite design. On the other hand, inexpensive on-board cameras can provide an effective solution, working at a wide range of distances. However, conditions of space lighting are particularly challenging for image based tracking algorithms, because of the direct sunlight exposure, and due to the glossy surface of the satellite that creates strong reflection and image saturation, which leads to difficulties in tracking procedures. In order to address these difficulties, the relevant literature is examined in the fields of computer vision, and satellite rendezvous and docking. Two classes of problems are identified and relevant solutions, implemented on a standard computer are provided. Firstly, in the absence of a geometric model of the satellite, the thesis presents a robust feature-based method with prediction capability in case of insufficient features, relying on a point-wise motion model. Secondly, we employ a robust model-based hierarchical position localization method to handle change of image features along a range of distances, and localize an attitude-controlled (partially cooperative) satellite. Moreover, the thesis presents a pose tracking method addressing ambiguities in edge-matching, and a pose detection algorithm based on appearance model learning. For the validation of the methods, real camera images and ground truth data, generated with a laboratory tet bed similar to space conditions are used. The experimental results indicate that camera based methods provide robust and accurate tracking for the approach of malfunctioning satellites in spite of the difficulties associated with specularities and direct sunlight. Also exceptional lighting conditions associated to the sun angle are discussed, aimed at achieving fully reliable localization system in a certain mission.

Relaxation in nuclear magnetic resonance is a powerful method for obtaining spatially resolved, timescale-specific dynamics information about molecular systems. However, dynamics in biomolecular systems are generally too complex to be fully characterized based on NMR data alone. This is a familiar problem, addressed by the Lipari-Szabo model-free analysis, a method that captures the full information content of NMR relaxation data in case all internal motion of a molecule in solution is sufficiently fast. We investigate model-free analysis, as well as several other approaches, and find that model-free, spectral density mapping, LeMaster’s approach, and our detector analysis form a class of analysis methods, for which behavior of the fitted parameters has a well-defined relationship to the distribution of correlation times of motion, independent of the specific form of that distribution. In a sense, they are all “model-free.” Of these methods, only detectors are generally applicable to solid-state NMR relaxation data. We further discuss how detectors may be used for comparison of experimental data to data extracted from molecular dynamics simulation, and how simulation may be used to extract details of the dynamics that are not accessible via NMR, where detector analysis can be used to connect those details to experiments. We expect that combined methodology can eventually provide enough insight into complex dynamics to provide highly accurate models of motion, thus lending deeper insight into the nature of biomolecular dynamics.

The three-dimensional structure of the world makes 3D as the natural evolution of a huge panel of applications. Many different 3D reconstruction algorithms have been implemented to meet different application needs. We target immersive applications. The reconstructed models of users and objects are inserted in 3D virtual environments creating the mixed reality, which is rendered on spatially immersive displays. The user sees its model on the projection walls, allowing him to interact with elements of the virtual world. Immersion requires small latency, high reconstruction rates and non-invasive systems. Furthermore, we choose to reconstruct arbitrary shapes with a geometric method. The review of the state of the art shows that all the acquisition devices cannot be connected to a single computer performing real time reconstruction. The system needs a cluster of computers and a strategy to share information between them. We present a distributed and scalable architecture for real time reconstruction of arbitrary shapes exploiting inter-frame redundancy. The architecture is composed of acquisition nodes and master nodes. Each acquisition node reconstructs partial models from its attached cameras and sends non-redundant information to its master. Each master node merges several partial models. The output of several masters can be merged by another master. We exploit the properties of volumetric algorithms, i.e. an efficient exploitation of inter-frame redundancy and an efficient merging of partial models, to increase performances. We test our volumetric architecture with an innovative implementation of the visual hull. We use a label that codes simultaneously occupancy, subdivision of space and visibility allowing each camera to see only part of the volume of interest. We test our system on a particular implementation of the framework composed of eight cameras and twelve cores, two per acquisition node and four for the master. We achieve fifteen reconstructions per second and less than 100 ms latency from segmentation to the display of the reconstructed model. System performances have been measured on sequences of more than 20 000 frames with unconstrained user’s movements. The system computes a fair approximation of the user in all situations. / La structure tridimensionnelle du monde fait de la 3D l’évolution naturelle d’un grand nombre d’applications. De nombreux algorithmes de reconstruction différents ont été développés pour satisfaire les besoins de différents types d’applications. On cible les applications immersives: Les modèles reconstruits de l’utilisateur ainsi que des objets qu’il porte sont insérés dans des environnements virtuels créant ainsi la réalité mixte. Cette dernière est affichée ce qui permet à l’utilisateur d’interagir avec des éléments virtuels. Le caractère immersif de l’application requiert une reconstruction temps réel à faible latence. Qui plus est, on désire la reconstruction de modèles de formes arbitraires à l’aide de méthodes géométriques. L’état de l’art montre que les différentes caméras ne peuvent pas être connectées à un seul ordinateur responsable de la reconstruction 3D. L’application requiert un cluster d’ordinateurs et une méthode étudiée afin de répartir la charge de travail et d’optimiser les performances. J’ai développé au cours de ma thèse une architecture volumétrique distribuée pour reconstruire des objets de forme arbitraire en temps réel et avec faible latence. Le système exploite les propriétés des algorithmes volumétriques pour améliorer les performances. Il est composé de deux types de nœuds: acquisition et fusion. Les nœuds de type acquisition reconstruisent des modèles partiels et envoient des informations non redondantes aux nœuds de type fusion. Chaque nœud fusion est responsable de la création d’un modèle global à partir de plusieurs modèles partiels. Grâce aux algorithmes développés, chaque étape de fusion rassemble les informations de plusieurs modèles partiels tout en ayant un impact faible sur la latence totale du système. L’architecture a été testée avec une implémentation particulière du Visual Hull permettant une disposition plus libre des caméras. Ces dernières ne doivent plus observer l’entièreté du volume d’intérêt. Chaque partie de l’utilisateur est modélisée grâce aux caméras qui l’observent. Notre système dispose de quatre nœuds d’acquisitions dual core et d’un nœud de fusion dual CPU dual core. On reconstruit quinze modèles par seconde avec une latence inférieure à 100 ms mesurée depuis la segmentation jusqu’au rendu. Quelques soient les mouvements de l’utilisateur et les objets qu’il manipule, le système est capable de le modéliser.

The aim of this thesis is to improve our understanding of the neural systems involved in schizophrenia by suggesting possible avenues for future computational modelling in an attempt to make sense of the vast number of studies relating to the symptoms and cognitive deficits relating to the disorder. This multidisciplinary research has covered three different levels of analysis: abnormalities in the microscopic brain structure, dopamine dysfunction at a neurochemical level, and interactions between cortical and subcortical brain areas, connected by cortico-basal ganglia circuit loops; and has culminated in the production of five models that provide useful clarification in this difficult field. My thesis comprises three major relevant modelling themes. Firstly, in Chapter 3 I looked at an existing neural network model addressing the Neurodevelopmental Hypothesis of Schizophrenia by Hoffman and McGlashan (1997). However, it soon became clear that such models were overly simplistic and brittle when it came to replication. While they focused on hallucinations and connectivity in the frontal lobes they ignored other symptoms and the evidence of reductions in volume of the temporal lobes in schizophrenia. No mention was made of the considerable evidence of dysfunction of the dopamine system and associated areas, such as the basal ganglia. This led to my second line of reasoning: dopamine dysfunction. Initially I helped create a novel model of dopamine neuron firing based on the Computational Substrate for Incentive Salience by McClure, Daw and Montague (2003), incorporating temporal difference (TD) reward prediction errors (Chapter 5). I adapted this model in Chapter 6 to address the ongoing debate as to whether or not dopamine encodes uncertainty in the delay period between presentation of a conditioned stimulus and receipt of a reward, as demonstrated by sustained activation seen in single dopamine neuron recordings (Fiorillo, Tobler &amp; Schultz 2003). An answer to this question could result in a better understanding of the nature of dopamine signaling, with implications for the psychopathology of cognitive disorders, like schizophrenia, for which dopamine is commonly regarded as having a primary role. Computational modelling enabled me to suggest that while sustained activation is common in single trials, there is the possibility that it increases with increasing probability, in which case dopamine may not be encoding uncertainty in this manner. Importantly, these predictions can be tested and verified by experimental data. My third modelling theme arose as a result of the limitations to using TD alone to account for a reinforcement learning account of action control in the brain. In Chapter 8 I introduce a dual weighted artificial neural network, originally designed by Hinton and Plaut (1987) to address the problem of catastrophic forgetting in multilayer artificial neural networks. I suggest an alternative use for a model with fast and slow weights to address the problem of arbitration between two systems of control. This novel approach is capable of combining the benefits of model free and model based learning in one simple model, without need for a homunculus and may have important implications in addressing how both goal directed and stimulus response learning may coexist. Modelling cortical-subcortical loops offers the potential of incorporating both the symptoms and cognitive deficits associated with schizophrenia by taking into account the interactions between midbrain/striatum and cortical areas.

Inspiré par les limitations de contrôleurs PID traditionnels et les différentes performances dans les cas idéals et réalistes, les quadrotors existants, leurs applications et leurs méthodes de contrôle ont été intensivement étudiés dans cette thèse. De nombreux challenges sont dévoilés: les systèmes embarqués ont des limites des ressources de calcul et de l'énergie; la dynamique est assez complexe et souvent mal connu; l'environnement a beaucoup de perturbations et d'incertitudes; de nombreuses méthodes de contrôle ont été proposées dans des scénarios idéaux dans la littérature sans comparaison avec d’autres méthodes. Par conséquent, cette thèse porte sur ces principaux points dans le contrôle de quadrotors.Tout d'abord, les modèles cinématiques et dynamiques sont proposés, y compris toutes les forces et couples aérodynamiques importants. Un modèle dynamique simplifié est également proposé pour certaines applications. Ensuite, la dynamique de quadrotor est analysée. En utilisant la théorie de la forme normale, le modèle de quadrotor est simplifié à une forme plus simple nommée la forme normale, qui présente toutes les propriétés dynamiques possibles du système d'origine. Les bifurcations de cette forme normale sont étudiées, et le système est simplifié à son point de bifurcation en utilisant la théorie de la variété du centre. Basé sur l’étude des applications de quadrotors, cinq scénarios réalistes sont proposés : un cas idéal, les cas avec la perturbation du vent, les incertitudes des paramètres, les bruits de capteurs et les fautes de moteur. Ces cas réalistes peuvent montrer plus globalement les performances des méthodes de contrôle par rapport aux cas idéaux. Un schéma déclenché par événements est également proposé avec le schéma déclenché par. Ensuite, la commande sans modèle est présentée, Il s'agit d'une technique simple mais efficace pour la dynamique non-linéaire, inconnue ou partiellement connue. La commande par backstepping et la commande par mode glissant sont également proposées pour la comparaison.Toutes les méthodes de contrôle sont mises en œuvre sous les schémas déclenchés par temps et par événements dans cinq scénarios différents. Basé sur l’étude des applications de quadrotors, dix critères sont choisis pour évaluer les performances des méthodes de contrôle, telles que l'erreur maximale absolue de suivi, la variance de l'erreur, le nombre d’actionnement, la consommation d'énergie, etc. / Inspired by the limitations of traditional PID controllers and the different performance in ideal and realistic cases, the existing quadrotors, their applications and control methods have been intensively studied in this dissertation. Many challenges are shown: embedded quadrotor systems have limit computational resources and energy; the aerodynamic dynamics is rather complex and poorly known; environment has many disturbances and uncertainties; many control methods have been proposed in ideal scenarios in literature without comparison. Therefore, this dissertation focuses on these main points in control of quadrotors.A kinematic model and a dynamic model are proposed, including all the important aerodynamic forces and moments. A simplified dynamic model is also given based on some applications. Then, the dynamics of quadrotor is analyzed. Using the normal form theory, the model of quadrotor is simplified to a simplest form named the normal form, which exhibits all possible dynamic properties of the original system. The bifurcations of its normal form are then studied, and the system can be further simplified at its bifurcation point using the center manifold theory.Based on the research of the applications in the first chapter, five typical realistic scenarios are proposed: an ideal case, the cases with wind disturbance, parameter uncertainties, sensor noises and actuator faults. These realistic cases can show comprehensively the performance of control methods respect to the ideal cases. An event triggered scheme is also proposed with the time triggered scheme in order to further save computational resources. Then, a newly proposed method the model free control is presented. It is a simple but efficient technique for the nonlinear, unknown or partially known dynamics. A backstepping control and a sliding mode control are also proposed for the sake of comparison.All the control methods are implemented in the time and event triggered schemes in five different scenarios. In order to keep closer to realistic situations, the control gains of each methods are not changed in different scenarios. Based on the study in the first chapter, ten criteria are chosen for measuring the performance of control methods, such as the maximum absolute tracking error, the error variance, the actuation steps, the energy consumption, etc.