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In data intensive applications deployed in enterprise networks, especially applications utilizing peer-to-peer technology, locality is of high importance. Peers should aim to maximize data exchange with other peers where the connectivity is the best. In order to achieve this, locality information must be present which peers can base their decisions on. This information is not trivial to find as there is no readily available global knowledge of which nodes have good connectivity. Having each peer try other peers randomly until it finds good enough partners is costly and lowers the locality of the application until it converges. In this thesis a solution is presented which creates a logical topology of a peer-to-peer network, grouping peers into clusters based on their connectivity metrics. This can then be used to aid the peer-to-peer partner selection algorithm to allow for intelligent partner selection. A graph model of the system is created, where peers in the system are modelled as vertices and connections between peers are modelled as edges, with a weight in relation to the quality of the connection. The problem is then modelled as a weighted graph clustering problem which is a well-researched problem with a lot of published work tied to it. State-of-the-art graph community detection algorithms are researched, selected depending on factors such as performance and scalability, optimized for the current purpose and implemented. The results of running the algorithms on the streaming data are evaluated against known information. The results show that unsupervised graph community detection algorithm creates useful insights into networks connectivity structure and can be used in peer-to-peer contexts to find the best partners to exchange data with. / I dataintensiva applikationer i företagsnätverk, speciellt applikationer som använder sig av peer-to-peer teknologi, är lokalitet viktigt. Klienter bör försöka maximera datautbyte med andra klienter där nätverkskopplingen är som bäst. För att klienterna ska kunna göra sådana val måste information om vilka klienter som befinner sig vara vara tillgänglig som klienterna kan basera sina val på. Denna information är inte trivial att framställa då det inte finns någon färdig global information om vilka klienter som har bra uppkoppling med andra klienter och att låta varje klient prova sig fram blint tills de hittar de bästa partnerna är kostsamt och sänker applikationens lokalitet innan den konvergerar. I denna rapport presenteras en lösning som skapar en logisk vy över ett peer-to-peer nätverk, vilken grupperar klienter i kluster baserat på deras uppkopplingskvalitet. Denna vy kan sedan användas för att förbättra lokaliteten i peerto-peer applikationen. En grafmodell av systemet skapas, där klienter modelleras som hörn och kopplingar mellan klienter modelleras som kanter med en vikt i relation till uppkopplingskvaliteten. Problemet formuleras sedan som ett riktat grafklusterproblem vilket är ett väldokumenterat forskningsområde med mycket arbete publicerat kring. De mest framstående grafklusteralgoritmerna är sedan studerade, utvalda baserat på kravspecifikationer, optimerade för det aktuella problemet och implementerade. Resultaten som produceras av att algoritmerna körs på strömdata är evaluerade mot känd information. Resultaten visar att oövervakade grafklusteralgoritmer skapar användbar information kring nätverkens uppkopplingsstruktur och kan användas i peer-to-peerapplikationssammanhang för att hitta de bästa partnerna att utbyta data med.

The challenges imposed on Voltage Regulator Modules (VRM) become difficult to be achieved with the conventional multiphase buck converter commonly used on PC motherboards. For faster data transfer, a decrease in the output voltage is needed. This decrease causes small duty cycle that is accompanied by critical problems which impairs the efficiency. Therefore, these problems need to be addressed. Transformer-based non-isolated topologies are not new approaches to extend the duty cycle and avoid the associated drawbacks. High leakage, several added components and complicated driving and control schemes are some of the trade-offs to expand the duty cycle. The objective of this work is to present a new dc-dc buck-based topology, which extends the duty cycle with minimum drawbacks by adding two transformers that can be integrated to decrease the size and two switches with zero voltage switching (ZVS). Another issue addressed in this thesis is deriving a small signal model for a two-input two-phase buck converter as an introduction to a new evolving field of multi-input converters.

The move toward electric vehicles (EVs) has a significant impact to reduce greenhouse gas (GHG) emissions and make transportation more eco-friendly. Fast-charging stations play a crucial role in this transition, making EVs more convenient for adoption specifically when driving in long distance. However, the challenge is to create a fast-charging system that can work with the different types of EVs and their varying power needs while still being efficient and effective. In this context, this thesis embarks on this journey by introducing an innovative solution for efficient universal fast charging, spanning both low voltage and high voltage battery systems. A novel, configurable dual secondary resonant converter is proposed, which empowers the charging module to extend its output range without imposing additional demands on the resonant tank components. This solution addresses the pressing need for a wide output voltage range in fast-charging standard in the growing EV landscape. To ensure optimal performance across a broad voltage and power range, the thesis employs an analytical model for LLC resonant converters to optimize the resonant components. This strategic component selection aims to achieve the desired output voltage and power range while minimizing conduction losses. The proposed topology and design methodology are rigorously validated through the development of a 10 kW prototype. Furthermore, the study introduces a two degrees of freedom (2DoF) control scheme for the proposed LLC resonant converter with the configurable dual secondary LLC converter topology. An analytical model is formulated to guide the selection of control parameters, ensuring coverage of the desired output voltage and power range without compromising system efficiency. The steady-state analytical model is utilized for determining optimized control parameters at each operating point within the converter's output range. To enhance the charging module's power density and efficiency, a high-frequency litz-wire transformer design methodology is introduced. The transformer's core size is optimized to achieve high power density and efficiency, while the winding configuration is chosen to minimize conduction losses. Finite Element Analysis (FEA) simulations validate transformer losses and operating temperatures. The culmination of this research is the development of a 30 kW charging module prototype. This prototype features an LLC resonant converter with a configurable dual secondary and two degrees of freedom control for output voltage control. The component ratings, estimated losses, and power board design are carefully considered to create a compact and efficient charging module. Experimental testing across a universal output voltage and power range con rms the effectiveness of the proposed solution. In summary, this thesis presents a comprehensive approach to design of a module for EV fast charging application addressing voltage range, efficiency, and component optimization, resulting in the successful development of a high-performance charging module prototype. / Thesis / Doctor of Engineering (DEng)

Multi-robot systems (MRSs) have gained significant momentum as of late in the robotics community as they find application in tasks such as unknown environment exploration, distributed surveillance, and search and rescue. Operating robot teams in real world environments introduces a notion of uncertainty into the system, especially when it comes to the ability of the MRS to reliably communicate. This poses a significant challenge as a stable communication topology is the backbone of the team's ability to coordinate. Additionally, as these systems continue to evolve and integrate further into our society, a growing threat of adversarial attackers pose the risk of compromising nominal operation. As such, this dissertation aims to model the effects of uncertainty in communication on the topology of the MRS using a probabilistic interaction model. More specifically we are interested in studying a probabilistic perspective to those topologies that pertain to the security and resilience of an MRS against adversarial attacks. Having a model that is capable of capturing how probabilistic topologies may evolve over time is essential for secure and resilient planning under communication uncertainty. As a result, we develop probabilistic models, both exact and approximate, for the topological properties of system left-invertibility and (r, s)-robustness that respectively characterize the security and resilience of an MRS. In our modeling, we use binary decision diagrams, convolutional neural networks, matroid theory and more to tackle the problems related to probabilistic security and resilience where we find exact solutions, calculate bounds, solve optimization problems, and compute informative paths for exploration. / Doctor of Philosophy / When robots coordinate and interact together to achieve a collaborative task as a team, we obtain what is known as a multi-robot system or MRS for short. MRSs have several advantages over single robots. These include reliability through redundancy, where several robots can perform a given task in case one of the robots unexpectedly fails. The ability to work faster and more efficiently by working in parallel and at different locations. And taking on more complex tasks that can be too demanding for a single robot to complete. Unfortunately, the advantages of MRSs come at a cost, they are generally harder to coordinate, the action of one robot often depends on the action of other robots in the system, and they are more vulnerable to being attacked or exploited by malicious attackers who want to disrupt nominal operation. As one would expect, communication plays a very important roles in coordinating a team of robots. Unfortunately, robots operating in real world environments are subject to disturbances such as noise, obstacles, and interference that hinders the team's ability to effectively exchange information. In addition to being crucial in coordination, effective information exchange plays a major role in detecting and avoiding adversarial robots. Whenever misinformation is being spread in the team, the best way to counter such adversarial behavior is to communicate with as much well-behaving robots as possible to identity and isolate inconsistencies. In this dissertation we try to study how uncertainty in communication affects a system's ability to detect adversarial behavior, and how we can model such a phenomenon to help us account for these uncertainties when designing secure and resilient multi-robot systems.

This dissertation presents voltage stabilization techniques for flying capacitors used in soft-switching multilevel active power filters. The proposed active filter has proved to be a solution for power system harmonics produced by static high power converters. However, voltage unbalance of the clamping capacitors in the active filter in practical applications was observed due to its unequal parameters. Thus, the fundamentals of flying capacitors were characterized dealing with voltage balancing between flying capacitors and dc capacitors under practical operation, rather than ideal conditions. The study of voltage balancing provides the fundamental high-level solutions to flying capacitor based multilevel converter and inverter applications without additional passive balancing circuits. The use of proposed voltage balancing techniques made it possible to have a simple structure for solving the problems associated with the conventional bulky passive resistors and capacitor banks. Furthermore, the proposed control algorithms can be implemented with a real time digital signal processor. It can achieve the high performance of the active filter by compensating an adaptive gain to the controller. The effectiveness of the proposed controller was confirmed through various simulations and experiments. The focus of this study is to identify and develop voltage stabilization techniques for flying capacitors used in a proposed active filter. The voltage unbalance is investigated and characterized to provide safe operations. After having defined the problems associated with the voltage unbalance, the most important voltage stabilization techniques are proposed to solve this problem, in conjunction with an instantaneous reactive power (IRP) control of an active filter. In order to reduce the switching losses and improve the efficiency of the active filter, the proposed soft-switching techniques were evaluated through simulation and experimentation. Experimental results indicate that the proposed active filter achieved zero-voltage conditions in all of the main switches and zero-current turn-off conditions to the auxiliary switches during commutation processes. Also, various studies on soft-switching techniques, multilevel inverters, control issues and dynamics of the proposed active filter are discussed and analyzed in depth. / Ph. D.

This dissertation presents the kinematics study on two cases of parallel locomotion mechanisms. A parallel locomotion mechanism can be defined as "a mechanism with parallel configuration and discrete contact with respect to the ground which renders a platform the ability to move". The first case is a tripedal robot and the second case is an actuated spoke wheel robot. The kinematics study on these two mobile robots mainly includes mobility, inverse and forward kinematics, instantaneous kinematics, singularity and so on. The tripedal robot STriDER (Self-excited Tripedal Dynamic Experimental Robot) is expected to walk utilizing its built-in passive dynamics, but in its triple stance phase, the kinematic configuration of the robot behaves like an in-parallel manipulator. The locomotion of this novel walking robot and its unique tripedal gait are discussed, followed by the definitions of its coordinate frames. Geometric methods are adopted for the forward and inverse displacement analysis in its triple stance phase. Simulations are presented to validate both the inverse and the forward displacement solutions. The instantaneous kinematics and singularity analysis are developed respectively. Based on the screw theory, the Jacobian matrices are assembled. Using Grassmann Line Geometry, each row of the Jacobian matrices is interpreted as a line in 3D space and the analytical conditions of the linear dependency cases are identified, which corresponds to the forward singular configurations of the robot. The actuated spoke wheel robot IMPASS (Intelligent Mobility Platform with Active Spoke System) is investigated as the second case. It is revealed that this robot has multiple modes of locomotion on the ground and it is able to change its topology by changing the contact scheme of its spokes with the ground. This robot is treated as a mechanism with variable topologies and Modified Grübler-Kutzbach criterion and Grassmann Line Geometry are adopted to identify the degrees of freedom (DOF) for each case of its topological structures. The characteristic DOF are then verified through the testing on the robot prototype. The forward and inverse kinematics is investigated for two cases of its topologies. In order to improve the computation efficiency of the inverse kinematics formulation, virtual serial manipulator models are constructed. The effectiveness of the virtual serial manipulator models has been validated with numerical simulations. In conclusion, kinematics analyses have been successfully performed on the two parallel locomotion mechanisms. The results are utilized to control the robots' motions in specific configurations. The foundation has been laid for the future development of the robot prototypes and the future research on dynamics, control, intelligence and so on. / Ph. D.

Lors de la phase de dimensionnement d’un générateur électrique, des choix préliminaires imposent généralement la topologie. Cette thèse a pour objectif d’apporter une aide décisionnelle au choix des structures de générateurs de fortes puissances. L’intérêt des machines à haute efficacité énergétique est porté par des objectifs environnementaux forts. En conséquence, maîtriser et comprendre l’origine des pertes dans les machines de production d’électricité est un enjeu capital. Ainsi, une méthodologie de calculs de pertes fer est développée pour des générateurs de fortes puissances.Dans les secteurs de la production et conversion d’énergie, les Machines Synchrones à Double Excitation présentent un fort potentiel pour répondre aux défis de la transition énergétique. Dès lors, il est important de quantifier l’impact de ces nouvelles structures par rapport aux solutions existantes. Cette thèse propose une modélisation par méthodes analytiques et semi-analytiques dans l’objectif de concevoir un ensemble de structures de générateurs. La modélisation est également comparée à deux prototypes de fortes puissances, dont un pour une application éolienne à attaque directe.Ensuite, cette modélisation est employée dans un processus de conception par optimisation. Les structures Pareto optimales sont comparées suivant différents cahiers des charges. Ces optimisations permettent de mettre en avant des gains significatifs par rapport aux solutions existantes notamment sur des données statistiques de fonctionnement éolien. / During the design phase of an electrical generator, the topology is generally imposed by preliminary criteria. This thesis aims at providing a decision support for the choice of high power generator structures. The interest for high efficiency machines is driven by strong environmental objectives. Consequently, understanding the origin of losses in power generation machines is a major issue. Thus, a methodology for iron loss calculation is developed for high power generators.In the energy production and conversion sectors, Hybrid Excitation Synchronous Machines have a great potential to respond to the challenges of energy transition. It is important to quantify the impact of these new structures compared with existing solutions. This thesis proposes analytical and lumped models to design a set of generator structures. The modeling approach is also compared with two high power generators, including one for a direct drive wind turbine. Then, this modeling is used in an optimization design process. The optimal Pareto structures are compared according to different specifications. These optimized designs show significant gains compared to the existing solutions, especially on wind profile from a Weibull probability density function.