No description available.

This thesis proposes, validates, and compares low-complexity algorithms for the fast-and-safe charge and balance of Li-ion batteries both for the single cell case and for the case of a serially-connected string of battery cells. The proposed algorithms are based on a reduced-order electrochemical model (Equivalent Hydraulic Model, EHM), and make use of constrained-control strategies to limit the main electrochemical degradation phenomena that may accelerate aging, namely: Lithium plating in the anode and solvent oxidation inthe cathode. To avoid the computational intensiveness of solving an online optimization as in the Model Predictive Control (MPC) framework, this thesis proposes the use of Reference Governor schemes. Variants of both the Scalar Reference Governors (SRG) and the Explicit Reference Governors (ERG) are developed to deal with the non-convex admissible region for the charge of a battery cell, while keeping a low computational burden. To evaluate the performance of the proposed techniques for the single cell case, they are experimentallyvalidated on commercial Turnigy LCO cells of 160 mAh at four different constant temperatures (10, 20, 30 and 40 °C). In the second part of this thesis, the proposed charging strategies are extended to take into account the balance of a serially-connected string of cells. To equalize possible mismatches, a centralized policy based on a shunting grid (active balance) connects or disconnects the cells during the charge. After a preliminary analysis, a simple mixed-integer algorithm was proposed. Since this method is computationally inefficient due to the high number of scenarios to be evaluated, this thesis proposes a ratio-based algorithm based on a Pulse-Width Modulation (PWM) approach. This approach can be used within both MPC and RG schemes. The numerical validations of the proposed algorithms for the case of a string of four battery cells are carried out using a simulator based on a full-order electrochemical model. Numerical validations show that the PWM-like approach charges in parallel all the cells within the pack, whereas the mixed-integer approach charges the battery cells sequentially from the battery cell with the lowest state of charge to the ones with the highest states of charge. On the basis of the simulations, an algorithm based on a mixed logic that allows to charge in a “sequential parallel” approach is proposed. Some conclusions and future directions of research are proposed at the end of the thesis. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Today the majority of the driver assistance systems are rule-basedcontrol systems that help the driver control the truck. But driversare looking for something more personal and exible that can controlthe truck in a human way with their own preferences. Machine learningand articial intelligence can help achieve this aim. In this studyArticial Neural Networks are used to model the driver steering behaviourin the Scania Lane Keeping Assist. Based on this, trajectoryplanning and steering wheel torque response are modelled to t thedriver preference. A model predictive controller can be used to maintainstate limitations and to weigh the two modelled driver preferencestogether. Due to the diculties in obtaining an internal plant modelfor the model predictive controller a variant of a PI-controller is addedfor integral action instead. The articial neural network also containsan online learning feature to further customize the t to the driverpreference over time. / Idag används till största del regelbaserade reglersystem förförarassistanssystem i lastbilar. Men lastbilschaufförer vill ha någotmer personligt och flexibelt, som kan styra lastbilen på ett mänskligtsätt med förarens egna preferenser. Maskininlärning och artificiell intelligenskan hjälpa till för att uppnå detta mål. I denna studie användsartificiella neurala nätverk för att modellera förarens styrbeteende genomScania Lane Keeping Assist. Med användning av detta modellerasförarens preferenser med avseende på placering på vägbanan och momentpåslag på ratten. En modell prediktiv kontroller kan användas föratt begränsa tillstånd och för att väga de två modellerade preferensernamot varann. Eftersom det var mycket svårt att ta fram den internaprocessmodellen som krävdes för regulatorn används istället en variantav en PI-kontroller för att styra lastbilen. De artificiella neuralanätverken kan också tillåtas att lära sig under körning för att anpassasig till förarens preferenser över tid.

The potential of Unmanned Aerial Vehicles (UAVs) for surveillance and military applications is significant — with continued technical advances in the field. The number of incidents where UAVs have intruded into unauthorized areas has increased in recent years and armed drones are commonly used in modern warfare. It is therefore of great interest to investigate methods for UAVs to locate and track intruder drones to prevent and counter surveillance of unauthorized areas and attacks from intruder UAVs. This master’s thesis studied how two autonomous seeker UAVs can be used cooperatively to track and pursue a target UAV. To locate the target UAV, simulated measurements from received Radio Frequency (RF) signals were used by extracting bearing and Received Signal Strength (RSS) data. To track the target and predict its future position, the study employed an Extended Kalman Filter (EKF) on each seeker UAV, which acted together as a Mobile Wireless Sensor Network (MWSN). The thesis explored two formation control methods to keep the seeker UAVs in formation while pursuing the target drone. The formation methods used the predicted position of the target to produce reference positions and/or reference distances for a controller to follow. A Distributed Model Predictive Controller (DMPC) was implemented on the seeker UAVs to pursue the target while maintaining formation and avoiding collisions. The EKF, MPC, and formation methods were first evaluated individually in simulation to assess their performance and for parameter tuning. The respective modules were then combined into the complete system and tuned to achieve improved pursuit and formation in simulation. The results showed that, with the chosen parameters and with a high level of measurement noise, the seeker UAVs were able to pursue the target with a combined average distance error of less than 2 m when the target drone flew in a square pattern with a velocity of 2 m/s. The quality of the pursuit was highly affected by the increase in velocity of the target and the initial positions of the seekers, where a high velocity and a large initial deviation from the reference positions/distances resulted in poorer quality.

Energy storage systems with many Lithium Ion battery cells per string require sophisticated balancing hardware due to individual cells having manufacturing inconsistencies, different self discharge rates, internal resistances and temperature variations. For capacity maximization, safe operation, and extended lifetime, battery balancing is required. Redistributive Non-Dissipative balancing further improves the pack capacity and efficiency over a Dissipative approach where energy is wasted as heat across shunt resistors. Redistribution techniques dynamically shuttle charge to and from weak cells during operation such that all of the stored energy in the stack is utilized. This thesis identifies and develops different balancing control methods. These methods include a unconstrained optimization problem using a Linear Quadratic Regulator (LQR) and a constrained optimization problem using Model Predictive Control (MPC). These methods are benchmarked against traditional rule based (RB) balancing. The control systems are developed using MATLAB/Simulink and validated experimentally on a multiple transformer individual cell to stack topology. The implementation uses a DC2100A Demo-board from Linear Technology with bi-directional flyback converters to transfer the energy between the cells. The results of this thesis show that the MPC control method has the highest balancing efficiency and minimum balancing time. / Thesis / Master of Applied Science (MASc)

No description available.

[ES] En los últimos años la popularidad de los quadrotors se ha visto notablemente incrementada debido a la gran variedad de aplicaciones civiles que se encuentran en auge actualmente. Entre los principales nichos de mercado, cabe destacar el elevado potencial en cartografía, agricultura, prevención de incendios, y en general, todas aquellas actividades donde el uso de estos dispositivos pueda suponer una mejora del rendimiento, seguridad del proceso y reducción de costes. En este aspecto, se espera que el uso de los quadrotors se vea incrementado considerablemente en los próximos años. Dicho incremento de popularidad ha hecho que parte de la comunidad científica ponga el foco de atención en ellos para resolver los problemas que presentan actualmente. No obstante, aunque se ha avanzado mucho en los últimos años, existen en la actualidad líneas de investigación y desarrollo encaminadas a la mejora de aspectos importantes tales como la autonomía, la robustez y fiabilidad que permita tanto aumentar la eficiencia energética como incrementar la seguridad ante cualquier posible escenario. El objetivo de la presente tesis es contribuir al desarrollo de estrategias de control robustas para hacer frente a incertidumbres en el modelo, no linealidades, perturbaciones externas y retardos que puedan afectar al sistema a controlar. Este trabajo se fundamenta en la obtención de una estrategia de control basada en estimaciones de perturbaciones, con un ajuste sencillo y desacoplado del seguimiento de la referencia y rechazo de perturbaciones. A partir las estrategias de control desarrolladas, se presentan además diferentes extensiones que permiten mejorar la robustez del vehículo. La construcción de un observador de la pérdida de eficiencia de los motores, que permita detectar cuando se produce un fallo crítico y aterrizar el vehículo de forma segura. Conjuntamente, se desarrolla un algoritmo óptimo que permite estabilizar los diferentes lazos de control en el caso que saturen las acciones de control de los motores que no corresponden explícitamente a las salidas de los lazos de control internos. Debido al extendido uso del controlador PID, se obtiene un equivalente entre la estrategia propuesta y los parámetros de un PID de dos grados de libertad, generalizándose para plantas de primer y segundo orden con retardos. Además, para el caso de retardos variables aleatorios en los canales de sensor-controlador y controlador-actuador además de la presencia de perturbaciones, se desarrolla un predictor junto con un observador de perturbaciones para poder controlar dichos sistemas. Todas las estrategias propuestas se han validado de forma satisfactoria en las plataformas experimentales disponibles. Entre otros aspectos, cabe destacar la eficiencia computacional de las leyes de control propuestas, tanto en fase de diseño y ajuste como en la fase de ejecución. / [CA] En els darrers anys la popularitat dels quadrotors s'ha vist notablement incrementada a causa de la gran varietat d'aplicacions civils que es troben actualment en auge. Entre els principals nínxols de mercat, cal destacar l'elevat potencial en cartografia, agricultura, prevenció d'incendis i, en general, totes aquelles activitats on l'ús d'aquests dispositius supose una millora del rendiment, la seguretat del procés i la reducció de costos. En aquest aspecte, s'espera que l'ús d'aquestes aeronaus s'incremente considerablement en els pròxims anys. Aquest increment de popularitat ha fet que part de la comunitat científica pose el focus d'atenció per resoldre els problemes que presenten actualment. No obstant això, encara que ha evolucionat molt en els darrers anys, actualment existeixen línies de recerca i desenvolupament encaminades a la millora d'aspectes importants com l'autonomia, la robustesa i fiabilitat que permitisca tant augmentar l'eficiència energètica com incrementar la seguretat davant qualsevol possible escenari. L'objectiu d'aquesta tesi és contribuir al desenvolupament d'estratègies de control robustes per fer front a incerteses en el model, no linealitats, pertorbacions externes i retards que puguen afectar el sistema a controlar. Aquest treball es fonamenta en obtindre una estratègia de control basada en estimacions de pertorbacions, amb un ajust senzill i desacoblat del seguiment de la referència i rebuig de pertorbacions. A partir d'aquesta estratègia desenvolupada, es presenten diferents extensions que permeten millorar la robustesa del vehicle. La construcció d'un observador de la pèrdua d'eficiència dels motors, que permeta detectar quan es produeix una fallada crítica i aterrar el vehicle de manera segura. Conjuntament, es desenvolupa un algorisme òptim que permeta estabilitzar els diferents bucles de control en cas que saturen les accions de control dels motors que no corresponen explícitament a les eixides dels bucles de control interns. A causa del ampli ús del controlador PID, s'obté un equivalent entre l'estratègia proposada i els paràmetres d'un PID de dos graus de llibertat, generalitzant-se per a plantes de primer i segon ordre amb retards. A més, per al cas de retards variables aleatoris als canals de sensor-controlador i controlador-actuador a més de la presència de pertorbacions, es desenvolupa un predictor juntament amb un observador de pertorbacions per poder controlar aquests sistemes. Totes les estratègies proposades s'han validat de forma satisfactòria amb les plataformes experimentals disponibles. Entre altres aspectes, cal destacar l'eficiència computacional de les lleis de control proposades, tant en fase de disseny i ajustament com en fase d'execució. / [EN] In recent years the popularity of quadrotors has increased significantly due to the wide variety of civil applications that are currently booming. Among the main market niches, it is worth the high potential in cartography, agriculture, fire prevention and in general, all those activities where the use of these devices can improve performance, process safety and cost reduction. In this regard, the use of these aircraft is expected to increase considerably in the coming years. This increase in popularity has led part of the scientific community to focus on them to solve the problems they have. However, although much progress has been made in recent years, there are currently lines of research and development aimed at improving important aspects such as autonomy, robustness and reliability to increase energy efficiency and safety against any possible scenario. The objective of this thesis is to contribute to the development of robust control strategies to deal with model uncertainties, nonlinearities, external disturbances and delays which may affect the controlled system. This work is based on obtaining a control strategy based on disturbance observers, with a simple and decoupled tuning of reference tracking and disturbance rejection. From this developed strategy, different extensions are developed to improve the robustness of the vehicle: the construction of an observer of the loss of efficiency of the motors, which allows to detect when a critical failure occurs and land the vehicle safely; and the development of an optimal algorithm to stabilize the inner control loops in the case that saturate the control actions of the motors, which do not correspond explicitly to the outputs of the inner control loops. Due to the widespread use of the PID controller, an equivalent tuning is obtained between the proposed strategy and the parameters of a PID of two degrees of freedom, generalizing for first and second order plants with delays. Moreover, for the case of random variable delays in the sensor-controller and controller-actuator channels and the presence of disturbances, a predictor together with a disturbance observer is developed in order to control such systems. All the proposed strategies have been successfully validated on the experimental platforms. Among other aspects, it is worth mentioning the computational efficiency of the proposed control laws, both in the design and adjustment phase and in the execution phase. / Quiero dar gracias a la Universitat Politècnica de València por las ayudas FPI-UPV PAID-01-17 y las ayudas para la movilidad 2019 FPI-UPV sin las cuales no hubiese podido terminar esta tesis. / Balaguer Garín, V. (2024). Diseño de estrategias de control robusto aplicadas a vehículos aéreos no tripulados tipo quadrotor [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/204746

Le problème de l'efficacité énergétique dans le domaine des transports a comme principal défi savoir comment utiliser la source d'énergie pour que l'efficacité énergétique puisse être maximisée, c'est-à-dire comment le véhicule doit être conduit de telle sorte que la quantité minimale d’énergie est utilisée. Ce problème est le principal problème considéré dans cette thèse. Le véhicule est un prototype impliqué dans la course européenne Shell Eco-Marathon. La dynamique du véhicule est d'abord obtenu par l'identification expérimentale des paramètres. Une stratégie en boucle ouverte de conduite optimale en termes de consommation électrique est calculée. Plusieurs approches ont été étudiées pour le suivi de la référence optimale (stratégie de conduite optimale). Ces approches doivent prendre en compte les ressources limitées en taille mémoire et capacité de calcul. Une commande prédictive (MPC) basée sur la dynamique linéarisée est tout d'abord synthétisée. Le problème de poursuite nécessite une MPC avec contraintes variant dans le temps. La stabilité et la convergence de la commande prédictive sont prouvées à l'aide du formalisme des ensembles invariants. En troisième partie, à partie du modèle LPV, une adaptation de techniques standards basées sur des fonctions de Lyapunov quadratiques et à paramètres variants avec calculs hors-ligne est proposée. Elle est implémentée sur un banc de test. Enfin, une technique adaptative robuste avec identification en ligne de la dynamique est proposée et implémentée dans le véhicule. Cette technique a été testée et validée en course. Les résultats expérimentaux obtenus montrent de bonnes performances de la stratégie de conduite / In the field of transportation, the research on energy efficiency has been carried out for few decades by the automotive industry, where one of the main objectives is to reduce the energetic consumption. This particular problem can be rephrased as how the vehicle must be driven so that the minimum quantity of energy is used. This is the optimal driving strategy. In this project, a suitable model of the Vir'volt electric vehicle involved in the European Shell Eco-Marathon is obtained. The unknown parameters involved in the vehicle dynamics are estimated using Parameter identification from experimental data. The identified dynamics is used to derive an optimal driving strategy that is intended to be tracked on-line during the driving task. The tracking task is subject to time-varying polytopic constraint on the input and/or the state. A MPC-based tracking strategy that uses an homothetic transformation as a suitable time-varying invariant set is used. The time-varying invariant set guarantees the asymptotic stability of the control law. The problem of the MPC tracking for Linear Parametric Varying (LPV) systems is introduced. A new explicit MPC strategy for LPV systems is developed. This strategy uses a Parameter dependent Lyapunov Function (PDLF) to involve explicitly the time-varying parameter in the control law and so it reduces conservatism. A benchmark is used to test the performances of the optimal driving strategy and the explicit MPC tracking strategy. Finally, a robust adaptive technique with on-line identification of the dynamics is has been proposed and tested in the race showing good performances of the adaptive driving strategy

Les maladies ostéoarticulaires représentent environ 10% de l'ensemble des pathologies identifiées en France chaque année. Pour l'instant aucun traitement permettant la réparation du tissu cartilagineux n'est vraiment disponible, hormis la pose d'un implant articulaire. Mais, malgré de nombreux efforts pour développer de nouveaux matériaux pour les implants articulaires leur durée de vie in vivo s'avère souvent très décevante par rapport aux extrapolations faites à partir de simulations ex-vivo. Les discordances entre les durées de vie in vivo et ex vivo sont principalement imputées aux conditions d'essais ex vivo insuffisamment réalistes vis-à-vis des propriétés physico-chimiques des lubrifiants biologiques. Dans ce contexte, ce travail vise à agir sur la réactivité physicochimique des surfaces frottantes des implants articulaires en UHMWPE afin de maîtriser l'accrochage des molécules lubrifiantes de type phospholipidique et ainsi d'augmenter leurs performances tribologiques. Les résultats montre que l'activation physichochimique des surfaces de UHMWPE par des couche de MPC peut diminuer l'usure des surfaces polymères d'implant mais cela nécessite un contrôle de la qualité de la couche MPC greffée (densité surfacique, épaisseur, accrochage chimique, adsorption physico-chimique) afin de garantir une bonne tenue mécanique et tribologique. D'autre part il a été montré que la présence de lubrifiant biologique (substitut du fluide synovial à base de liposomes) réduit l'usure des surfaces de UHWPE même si la couche de MPC est peu dense et peu épaisse

Cette thèse s'inscrit dans le cadre du projet collaboratif MICROSOL, mené par Schneider Electric, et qui oeuvre pour le développement de micros centrales solaires thermodynamiques destinées à la production d'électricité en sites isolés (non connectés au réseau électrique) en exploitant l'énergie thermique du soleil. Le but de cette thèse étant le développement de lois de commande innovantes et efficaces pour la gestion de l'énergie de deux types de micros centrales solaires thermodynamiques : à base de moteur à cycle de Stirling et à base de machines à Cycle de Rankine Organique (ORC). Dans une première partie, nous considérons une centrale solaire thermodynamique à base de machine à cycle de Stirling hybridée à un supercondensateur comme moyen de stockage d'énergie tampon. Dans ce cadre, nous proposons une première loi de commande validée expérimentalement, associée au système de conversion d'énergie du moteur Stirling, qui dote le système de performances quasi optimales en termes de temps de réponse ce qui permet de réduire la taille du supercondensateur utilisé. Une deuxième loi de commande qui gère explicitement les contraintes du système tout en dotant ce dernier de performances optimales en terme de temps de réponse, est également proposée. Cette dernière loi de commande est en réalité plus qu'un simple contrôleur, elle constitue une méthodologie de contrôle applicable pour une famille de systèmes de conversion de l'énergie.Dans une deuxième partie, nous considérons une centrale solaire thermodynamique à base de machine à cycle de Rankine Organique (ORC) hybridée à un banc de batteries comme moyen de stockage d'énergie tampon. Etant donné que ce système fonctionne à vitesse de rotation fixe pour la génératrice asynchrone qui est connectée à un système de conversion d'énergie commercial, nous proposons une loi de commande prédictive qui agit sur la partie thermodynamique de ce système afin de le faire passer d'un point de fonctionnement à un autre, lors des appels de puissance des charges électriques, le plus rapidement possible (pour réduire le dimensionnement des batteries) tout en respectant les contraintes physiques du système. La loi de commande prédictive développée se base sur un modèle dynamique de la machine ORC identifié expérimentalement grâce à un algorithme d'identification nonlinéaire adéquat. / This Ph.D thesis was prepared in the scope of the MICROSOL project, ledby Schneider Electric, that aims at developing Off-grid solar thermodynamic micro powerplants exploiting the solar thermal energy. The aim of this thesis being the development of innovative and efficient control strategies for the energy management of two kinds of solar thermodynamic micro power plants: based on Stirling engine and based and Organic RankineCycle (ORC) machines.In a first part, we consider the Stirling based solar thermodynamic micro power planthybridized with a supercapacitor as an energy buffer. Within this framework, we propose afirst experimentally validated control strategy, associated to the energy conversion system ofthe Stirling engine, that endows the system with quasi optimal performances in term of settlingtime enabling the size reduction of the supercapacitor. A second control strategy that handlesexplicitly the system constraints while providing the system with optimal performances interm of settling time , is also proposed. This control strategy is in fact more than a simplecontroller, it is a control framework that holds for a family of energy conversion systems.In a second part, we consider the Organic Rankine Cycle (ORC) based thermodynamicmicro power plant hybridized with a battery bank as an energy buffer. Since this system worksat constant speed for the asynchronous generator electrically connected to a commercial energyconversion system, we propose a model predictive controller that acts on the thermodynamicpart of this system to move from an operating point to another, during the load power demandtransients, as fast as possible (to reduce the size of the battery banks) while respecting thephysical system constraints. The developed predictive controller is based upon a dynamicmodel, for the ORC power plant, identified experimentally thanks to an adequate nonlinearidentification algorithm.