Commande par mode glissant de paliers magnétiques actifs économes en énergie : une approche sans modèle

Abstract : Over the past three decades, various fields have witnessed a successful application of active magnetic bearing (AMB) systems. Their favorable features include supporting high-speed rotation, low power consumption, and rotor dynamics control. Although their losses are much lower than roller bearings, these losses could limit the operation in some applications such as flywheel energy storage systems and vacuum applications. Many researchers focused their efforts on boosting magnetic bearings energy efficiency via minimizing currents supplied to electromagnetic coils either by a software solution or a hardware solution. According to a previous study, we adopt the hardware solution in this thesis. More specifically, we investigate developing an efficient and yet simple control scheme for regulating a permanent magnet-biased active magnetic bearing system. The control objective here is to suppress the rotor vibrations and reduce the corresponding control currents as possible throughout a wide operating range. Although adopting the hardware approach could achieve an energy-efficient AMB, employing an advanced control scheme could achieve a further reduction in power consumption. Many advanced control techniques have been proposed in the literature to achieve a satisfactory performance. However, the complexity of the majority of control schemes and the potential requirement of powerful platform could discourage their application in practice. The motivation behind this work is to improve the closed-loop performance without the need to do model identification and following the conventional procedure for developing a model-based controller. Here, we propose applying the hybridization concept to exploit the classical PID control and some nonlinear control tools such as first- and second-order sliding mode control, high gain observer, backstepping, and adaptive techniques to develop efficient and practical control schemes. All developed control schemes in this thesis are digitally implemented and validated on the eZdsp F2812 control board. Therefore, the applicability of the proposed model-free techniques for practical application is demonstrated. Furthermore, some of the proposed control schemes successfully achieve a good compromise between the objectives of rotor vibration attenuation and control currents minimization over a wide operating range.Résumé: Au cours des trois dernières décennies, divers domaines ont connu une application réussie des systèmes de paliers magnétiques actifs (PMA). Leurs caractéristiques favorables comprennent une capacité de rotation à grande vitesse, une faible consommation d'énergie, et le contrôle de la dynamique du rotor. Bien que leurs pertes soient beaucoup plus basses que les roulements à rouleaux, ces pertes pourraient limiter l'opération dans certaines applications telles que les systèmes de stockage d'énergie à volant d'inertie et les applications sous vide. De nombreux chercheurs ont concentré leurs efforts sur le renforcement de l'efficacité énergétique des paliers magnétiques par la minimisation des courants fournis aux bobines électromagnétiques soit par une solution logicielle, soit par une solution matérielle. Selon une étude précédente, nous adoptons la solution matérielle dans cette thèse. Plus précisément, nous étudions le développement d'un système de contrôle efficace et simple pour réguler un système de palier magnétique actif à aimant permanent polarisé. L'objectif de contrôle ici est de supprimer les vibrations du rotor et de réduire les courants de commande correspondants autant que possible tout au long d'une large plage de fonctionnement. Bien que l'adoption de l'approche matérielle pourrait atteindre un PMA économe en énergie, un système de contrôle avancé pourrait parvenir à une réduction supplémentaire de la consommation d'énergie. De nombreuses techniques de contrôle avancées ont été proposées dans la littérature pour obtenir une performance satisfaisante. Cependant, la complexité de la majorité des systèmes de contrôle et l'exigence potentielle d’une plate-forme puissante pourrait décourager leur application dans la pratique. La motivation derrière ce travail est d'améliorer les performances en boucle fermée, sans la nécessité de procéder à l'identification du modèle et en suivant la procédure classique pour développer un contrôleur basé sur un modèle. Ici, nous proposons l'application du concept d'hybridation pour exploiter le contrôle PID classique et certains outils de contrôle non linéaires tels que contrôle par mode glissement du premier et du second ordre, observateur à grand gain, backstepping et techniques adaptatives pour développer des systèmes de contrôle efficaces et pratiques. Tous les systèmes de contrôle développés dans cette thèse sont numériquement mis en oeuvre et évaluées sur la carte de contrôle eZdsp F2812. Par conséquent, l'applicabilité des techniques de modèle libre proposé pour l'application pratique est démontrée. En outre, certains des régimes de contrôle proposés ont réalisé avec succès un bon compromis entre les objectifs au rotor d’atténuation des vibrations et la minimisation des courants de commande sur une grande plage de fonctionnement

Regulación de tensión en convertidores DC-DC clásicos de segundo orden mediante la aplicación del control óptimo inverso con acción proporcional-integral

This article addresses the problem regarding power regulation in classical DC-DC second-order converters by means of a nonlinear control technique based on inverse optimal control theory. There are few papers that describe inverse optimal control for DC-DC converters in the literature. Therefore, this study constitutes a contribution to the state of the art on nonlinear control techniques for DC-DC converters. In this vein, the main objective of this research was to implement inverse optimal control theory with integral action to the typical DC-DC conversion topologies for power regulation, regardless of the load variations and the application. The converter topologies analyzed were: (i) Buck; (ii) Boost; (iii) Buck-Boost; and (iv) Non-Inverting Buck-Boost. A dynamical model was proposed as a function of the state variable error, which helped to demonstrate that the inverse optimal control law with proportional-integral action implemented in the different converters ensures stability in each closed-loop operation via Lyapunov’s theorem. Numerical validations were carried out by means of simulations in the PSIM software, comparing the established control law, the passivity-based PI control law, and an open-loop control. As a conclusion, it was possible to determine that the proposed model is easier to implement and has a better dynamical behavior than the PI-PBC, ensuring asymptotic stability from the closed-loop control design.Este artículo aborda el problema de regulación de tensión para convertidores DC-DC clásicos de segundo orden mediante una técnica de control no lineal basada en la teoría de control óptimo inverso. En la literatura hay pocos artículos que describen el control optimo inverso para convertidores DC-DC, por tanto, este estudio es una contribución al estado del arte en técnica de control no lineal para convertidores DC-DC. En este orden de ideas, el objetivo principal de esta investigación fue implementar la teoría de control óptimo inverso con acción integral a las topologías típicas de conversión DC-DC para regular tensión, independientemente de las variaciones de la carga y de la aplicación. Las topologías de los convertidores analizados fueron: (i) Buck; (ii) Boost; (iii) Buck-Boost; y (iv) Buck-Boost No Inversor. Se planteó un modelo dinámico en función del error de las variables de estado, el cual ayudó a demostrar que la ley de control óptimo inverso con acción proporcional-integral implementada para los diferentes convertidores garantiza la estabilidad para operación en lazo cerrado mediante el teorema de Lyapunov. Se realizó la validación numérica mediante simulaciones en el software PSIM, comparando la ley de control establecida, la ley de control PI basada en pasividad y un control en lazo abierto. Como conclusión, se pudo determinar que el método propuesto es más sencillo de implementar y con mejor comportamiento dinámico que el PI-PBC, garantizando la estabilidad asintótica desde el diseño de control en lazo cerrado

Novel methods for biological network inference: an application to circadian Ca2+ signaling network

Biological processes involve complex biochemical interactions among a large number of species like cells, RNA, proteins and metabolites. Learning these interactions is essential to interfering artificially with biological processes in order to, for example, improve crop yield, develop new therapies, and predict new cell or organism behaviors to genetic or environmental perturbations. For a biological process, two pieces of information are of most interest. For a particular species, the first step is to learn which other species are regulating it. This reveals topology and causality. The second step involves learning the precise mechanisms of how this regulation occurs. This step reveals the dynamics of the system. Applying this process to all species leads to the complete dynamical network. Systems biology is making considerable efforts to learn biological networks at low experimental costs. The main goal of this thesis is to develop advanced methods to build models for biological networks, taking the circadian system of Arabidopsis thaliana as a case study. A variety of network inference approaches have been proposed in the literature to study dynamic biological networks. However, many successful methods either require prior knowledge of the system or focus more on topology. This thesis presents novel methods that identify both network topology and dynamics, and do not depend on prior knowledge. Hence, the proposed methods are applicable to general biological networks. These methods are initially developed for linear systems, and, at the cost of higher computational complexity, can also be applied to nonlinear systems. Overall, we propose four methods with increasing computational complexity: one-to-one, combined group and element sparse Bayesian learning (GESBL), the kernel method and reversible jump Markov chain Monte Carlo method (RJMCMC). All methods are tested with challenging dynamical network simulations (including feedback, random networks, different levels of noise and number of samples), and realistic models of circadian system of Arabidopsis thaliana. These simulations show that, while the one-to-one method scales to the whole genome, the kernel method and RJMCMC method are superior for smaller networks. They are robust to tuning variables and able to provide stable performance. The simulations also imply the advantage of GESBL and RJMCMC over the state-of-the-art method. We envision that the estimated models can benefit a wide range of research. For example, they can locate biological compounds responsible for human disease through mathematical analysis and help predict the effectiveness of new treatments

Adaptive and learning-based formation control of swarm robots

Autonomous aerial and wheeled mobile robots play a major role in tasks such as search and rescue, transportation, monitoring, and inspection. However, these operations are faced with a few open challenges including robust autonomy, and adaptive coordination based on the environment and operating conditions, particularly in swarm robots with limited communication and perception capabilities. Furthermore, the computational complexity increases exponentially with the number of robots in the swarm. This thesis examines two different aspects of the formation control problem. On the one hand, we investigate how formation could be performed by swarm robots with limited communication and perception (e.g., Crazyflie nano quadrotor). On the other hand, we explore human-swarm interaction (HSI) and different shared-control mechanisms between human and swarm robots (e.g., BristleBot) for artistic creation. In particular, we combine bio-inspired (i.e., flocking, foraging) techniques with learning-based control strategies (using artificial neural networks) for adaptive control of multi- robots. We first review how learning-based control and networked dynamical systems can be used to assign distributed and decentralized policies to individual robots such that the desired formation emerges from their collective behavior. We proceed by presenting a novel flocking control for UAV swarm using deep reinforcement learning. We formulate the flocking formation problem as a partially observable Markov decision process (POMDP), and consider a leader-follower configuration, where consensus among all UAVs is used to train a shared control policy, and each UAV performs actions based on the local information it collects. In addition, to avoid collision among UAVs and guarantee flocking and navigation, a reward function is added with the global flocking maintenance, mutual reward, and a collision penalty. We adapt deep deterministic policy gradient (DDPG) with centralized training and decentralized execution to obtain the flocking control policy using actor-critic networks and a global state space matrix. In the context of swarm robotics in arts, we investigate how the formation paradigm can serve as an interaction modality for artists to aesthetically utilize swarms. In particular, we explore particle swarm optimization (PSO) and random walk to control the communication between a team of robots with swarming behavior for musical creation

Energy Management of Prosumer Communities

The penetration of distributed generation, energy storages and smart loads has resulted in the emergence of prosumers: entities capable of adjusting their electricity production and consumption in order to meet environmental goals and to participate profitably in the available electricity markets. Significant untapped potential remains in the exploitation and coordination of small and medium-sized distributed energy resources. However, such resources usually have a primary purpose, which imposes constraints on the exploitation of the resource; for example, the primary purpose of an electric vehicle battery is for driving, so the battery could be used as temporary storage for excess photovoltaic energy only if the vehicle is available for driving when the owner expects it to be. The aggregation of several distributed energy resources is a solution for coping with the unavailability of one resource. Solutions are needed for managing the electricity production and consumption characteristics of diverse distributed energy resources in order to obtain prosumers with more generic capabilities and services for electricity production, storage, and consumption. This collection of articles studies such prosumers and the emergence of prosumer communities. Demand response-capable smart loads, battery storages and photovoltaic generation resources are forecasted and optimized to ensure energy-efficient and, in some cases, profitable operation of the resources

Heterogeneous robots: Model Predictive Control for bearing-only formation and tracking

openMulti-agent systems are systems composed by more than one autonomous robots which usually work under the assumption that they can communicate sending and receiving positions of other robots that operate in the network. The introduction of this kind of systems is due to the fact that in many situations it is preferable to use more than one robot in order to reach more complex goal without the help of the humans, especially in dangerous situations. In this thesis, the focus is on the heterogeneous robots which are robots whose components are heterogeneous in terms of actuation capabilities, even if it is assumed they can receive bearing information with respect to the other agents in the network. Hence, it is developed an heterogeneous MAS composed by 2 UGVs and 2 UAVs. The goals of the thesis is that the formation has to be maintained and the four agents has also to track a desired trajectory through a leader follower approach based on bearing-only implemented using MPC controllers. The role of the leader is to track the desired trajectory while the followers have to form and maintain the formation also during the tracking. The followers do not know the trajectory to be tracked, nor the distance to the other agents and the leader. The approach is based on decentralized leader follower control with bearing-only. The controllers used are the Model Predictive ones since this type of control allow to prevent the critical situations, solving an online optimization problem at each time instant to select the best control action that drives the predicted output to the reference. The proposed approach is implemented in Matlab and Simulink and the results obtained by the simulations will be discussed.Multi-agent systems are systems composed by more than one autonomous robots which usually work under the assumption that they can communicate sending and receiving positions of other robots that operate in the network. The introduction of this kind of systems is due to the fact that in many situations it is preferable to use more than one robot in order to reach more complex goal without the help of the humans, especially in dangerous situations. In this thesis, the focus is on the heterogeneous robots which are robots whose components are heterogeneous in terms of actuation capabilities, even if it is assumed they can receive bearing information with respect to the other agents in the network. Hence, it is developed an heterogeneous MAS composed by 2 UGVs and 2 UAVs. The goals of the thesis is that the formation has to be maintained and the four agents has also to track a desired trajectory through a leader follower approach based on bearing-only implemented using MPC controllers. The role of the leader is to track the desired trajectory while the followers have to form and maintain the formation also during the tracking. The followers do not know the trajectory to be tracked, nor the distance to the other agents and the leader. The approach is based on decentralized leader follower control with bearing-only. The controllers used are the Model Predictive ones since this type of control allow to prevent the critical situations, solving an online optimization problem at each time instant to select the best control action that drives the predicted output to the reference. The proposed approach is implemented in Matlab and Simulink and the results obtained by the simulations will be discussed

Modelling optimal plant carbon storage

As sessile organisms, plants are especially vulnerable to a wide range of abiotic and biotic pressures. Moreover, anthropogenic climate change has been causing increased intensity and frequency of stress events. To predict how environmental stress modifies vegetation function, we need to better understand plant stress tolerance mechanisms. One such mechanism is carbon storage: storage of non-structural carbohydrates provides plants with reserves during a stress period and expedites post-stress recovery. However, storing carbon requires an a priori action that only has a positive effect on survival during future stress, and may be detrimental, in the short-term, by re-directing carbon from other crucial processes such as growth. In this thesis, I focus on exploring the growth-storage trade-off involved in plant carbon storage in the presence of stress. I employ a range of modelling techniques to mathematically characterise the response of the optimal storage utilisation trajectory (OSUT). In Chapter 2, I explore the shape of OSUT during a single stress period. In Chapter 3, I explore the long-term success of alternative storage strategies for a community of plants experiencing stochastic stress events. Whilst Chapter 2 assumed that the evolved strategy is static, that is unrealistic. Hence in Chapter 4, I explore the acclimation of carbon storage to a stochastic environment. The results presented in this thesis identify candidate storage-related allocation traits that can link carbon storage strategies with other observable plant traits and processes. Such work would be vital in improving the representation of carbon storage in models. Therefore, the findings from this thesis provide new insights into how optimal carbon storage may be modelled and, further, underline the importance of capturing the trade-offs of growth-storage and the effects of stochasticity when exploring the process of carbon storage

Contributions to impedance shaping control techniques for power electronic converters

El conformado de la impedancia o admitancia mediante control para convertidores electrónicos de potencia permite alcanzar entre otros objetivos: mejora de la robustez de los controles diseñados, amortiguación de la dinámica de la tensión en caso de cambios de carga, y optimización del filtro de red y del controlador en un solo paso (co-diseño). La conformación de la impedancia debe ir siempre acompañada de un buen seguimiento de referencias. Por tanto, la idea principal es diseñar controladores con una estructura sencilla que equilibren la consecución de los objetivos marcados en cada caso. Este diseño se realiza mediante técnicas modernas, cuya resolución (síntesis del controlador) requiere de herramientas de optimización. La principal ventaja de estas técnicas sobre las clásicas, es decir, las basadas en soluciones algebraicas, es su capacidad para tratar problemas de control complejos (plantas de alto orden y/o varios objetivos) de una forma considerablemente sistemática. El primer problema de control por conformación de la impedancia consiste en reducir el sobreimpulso de tensión ante cambios de carga y minimizar el tamaño de los componentes del filtro pasivo en los convertidores DC-DC. Posteriormente, se diseñan controladores de corriente y tensión para un inversor DC-AC trifásico que logren una estabilidad robusta del sistema para una amplia variedad de filtros. La condición de estabilidad robusta menos conservadora, siendo la impedancia de la red la principal fuente de incertidumbre, es el índice de pasividad. En el caso de los controladores de corriente, el impacto de los lazos superiores en la estabilidad basada en la impedancia también se analiza mediante un índice adicional: máximo valor singular. Cada uno de los índices se aplica a un rango de frecuencias determinado. Finalmente, estas condiciones se incluyen en el diseño en un solo paso del controlador de un convertidor back-to-back utilizado para operar generadores de inducción doblemente alimentados (aerogeneradores tipo 3) presentes en algunos parques eólicos. Esta solución evita los problemas de oscilación subsíncrona, derivados de las líneas de transmisión con condensadores de compensación en serie, a los que se enfrentan estos parques eólicos. Los resultados de simulación y experimentales demuestran la eficacia y versatilidad de la propuesta.Impedance or admittance shaping by control for power electronic converters allows to achieve among other objectives: robustness enhancement of the designed controls, damped voltage dynamics in case of load changes, and grid filter and controller optimization in a single step (co-design). Impedance shaping must always be accompanied by a correct reference tracking performance. Therefore, the main idea is to design controllers with a simple structure that balance the achievement of the objectives set in each case. This design is carried out using modern techniques, whose resolution (controller synthesis) requires optimization tools. The main advantage of these techniques over the classical ones, i.e. those based on algebraic solutions, is their ability to deal with complex control problems (high order plants and/or several objectives) in a considerably systematic way. The first impedance shaping control problem is to reduce voltage overshoot under load changes and minimize the size of passive filter components in DC-DC converters. Subsequently, current and voltage controllers for a three-phase DC-AC inverter are designed to achieve robust system stability for a wide variety of filters. The least conservative robust stability condition, with grid impedance being the main source of uncertainty, is the passivity index. In the case of current controllers, the impact of higher loops on impedance-based stability is also analyzed by an additional index: maximum singular value. Each of the indices is applied to a given frequency range. Finally, these conditions are included in the one-step design of the controller of a back-to-back converter used to operate doubly fed induction generators (type-3 wind turbines) present in some wind farms. This solution avoids the sub-synchronous oscillation problems, derived from transmission lines with series compensation capacitors, faced by these wind farms. Simulation and experimental results demonstrate the effectiveness and versatility of the proposa