abstract: According to the Center for Disease Control and Prevention report around 29,668 United States residents aged greater than 65 years had died as a result of a fall in 2016. Other injuries like wrist fractures, hip fractures, and head injuries occur as a result of a fall. Certain groups of people are more prone to experience falls than others, one of which being individuals with stroke. The two most common issues with individuals with strokes are ankle weakness and foot drop, both of which contribute to falls. To mitigate this issue, the most popular clinical remedy given to these users is thermoplastic Ankle Foot Orthosis. These AFO's help improving gait velocity, stride length, and cadence. However, studies have shown that a continuous restraint on the ankle harms the compensatory stepping response and forward propulsion. It has been shown in previous studies that compensatory stepping and forward propulsion are crucial for the user's ability to recover from postural perturbations. Hence, there is a need for active devices that can supply a plantarflexion during the push-off and dorsiflexion during the swing phase of gait. Although advancements in the orthotic research have shown major improvements in supporting the ankle joint for rehabilitation, there is a lack of available active devices that can help impaired users in daily activities. In this study, our primary focus is to build an unobtrusive, cost-effective, and easy to wear active device for gait rehabilitation and fall prevention in individuals who are at risk. The device will be using a double-acting cylinder that can be easily incorporated into the user's footwear using a novel custom-designed powered ankle brace. The device will use Inertial Measurement Units to measure kinematic parameters of the lower body and a custom control algorithm to actuate the device based on the measurements. The study can be used to advance the field of gait assistance, rehabilitation, and potentially fall prevention of individuals with lower-limb impairments through the use of Active Ankle Foot Orthosis. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2020

The aim of this diploma thesis is to design algorithms of semi-active suspension system for a quarter car model, compare their function with respect to ride comfort and drive safety. Consequently, setup control algorithms for using in the Adams software. The result of this thesis should be to determine the effect of semi-active suspension control system on vehicle behavior.

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<p dir="ltr">A broad scope of this dissertation is to verify that a nearby loss of generation event in power system can be distinguished from similar remote disturbances by analyzing the resulting local modes of oscillation. An oscillation-based index derived from methods like Fourier transform, sinc filters and resonant filters is devised and experimented in combination with a variant of df/dt index to jointly classify if a loss of generation event is nearby or remote. A phenomenon widely observed during a loss of generation event is the average decrease in the system’s frequency, typically monitored using the df/dt index. Under-frequency load-shedding (UFLS) relays that are based on df/dt are highly likely to trip for nearby frequency events when combined with the oscillation-based index we propose. Nearby in our context refers to geographical distance, which is correlated with electrical distance, and includes buses within about 50-100 miles of the event location.</p>

<p dir="ltr">The automotive industry has incorporated controls since the 1970s, starting with the pioneering application of an air-to-fuel ratio feedback control carburetor. Over time, significant advancements have been made in control strategies to meet industry standards for reduced fuel consumption, exhaust emissions, and enhanced safety. This thesis focuses on the implementation of advanced control strategies in heavy-duty diesel powertrains and their advantages over traditional control methods commonly employed in the automotive industry.</p><p dir="ltr">The initial part of the thesis demonstrates the utilization of model predictive control (MPC) to generate an optimized velocity profile for class 8 trucks. These velocity profiles are designed to minimize fuel consumption along a given route with known grade conditions, while adhering to the time constraints comparable to those of standard commercial cruise controllers. This methodology is further expanded to include the platooning of two trucks, with the rear truck following a desired gap (variable or fixed), resulting in additional fuel savings throughout the designated route. Through collaborative efforts involving Cummins, Peloton Technology, and Purdue University, these control strategies were implemented and validated through simulation, hardware-in-the-loop testing, and ultimately, in demonstration vehicles.</p><p dir="ltr">MPC is highly effective for vehicle-level controls due to the accurate plant model used for optimization. However, when it comes to engine controls, the plant model becomes highly nonlinear and loses accuracy when linearized [20]. To address this issue, robust control techniques are introduced to account for the inherent inaccuracies in the plant model, which can be represented as uncertainties.</p><p dir="ltr">The second study showcases the application of robust controllers in diesel engine operations, focusing on a 4.5L John Deere diesel engine equipped with an electrified intake boosting system. The intake boosting system is selectively activated during transient operations to mitigate drops in the air-to-fuel ratio (AFR), which can result in smoke emissions. Initially, a two-degree-of-freedom robustsingle-input single-output (SISO) eBooster controller is synthesized to control the eBooster during load transients. Although the robust SISO controller yields improvements, the eBooster alone does not encompass all factors affecting the gas exchange process. Other actuators, such as the exhaust throttle and EGR valve, need to be considered to enhance the air handling system. To achieve this, a robust model-basedmultiple-input multiple-output (MIMO) controller is developed to regulate the desired AFR, engine speed, and diluent air ratio (DAR) using various air handling actuators and fueling strategies. The robust MIMO controller is synthesized based on a physics-based mean value engine model, which has been calibrated to accurately reflect high-fidelity engine simulation software. The robust SISO and MIMO controllers are implemented in simulation using the high-fidelity engine simulation software. Following the simulation, the controllers are validated through experimental testing conducted in an engine dynamometer at University of Wisconsin. Results from these controllers are compared against a non-eBoosted engine, which serves as the baseline. While both the SISO and MIMO controllers show improvements in AFR (Air-Fuel Ratio), DAR (Diluent Air Ratio), and engine speed recovery during the load transients, the robust MIMO controller outperforms them by demonstrating the best overall engine performance. This superiority is attributed to its comprehensive understanding of the coupling between each actuator input and the model output. When the MIMO controller operates alongside the electrified intake boosting system, the engine exhibits remarkable enhancements. Not only does it recover back to a steady state 70% faster than the baseline, but it also reduces engine speed droop by 45%. Consequently, the engine's ability to accept load torque increases significantly.</p><p dir="ltr">As a result, a single robust MIMO controller can efficiently perform the same task instead of employing multiple PIDs or look-up tables for each actuator.</p>

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model.

La propulsion des véhicules électriques hybrides parallèles est généralement assurée par un moteur à combustion interne combiné à une machine électrique réversible. Les flux de puissance entre ces deux organes de traction sont déterminés par un algorithme de supervision, qui vise à réduire la consommation de carburant et éventuellement les émissions de certains polluants. Dans la littérature, la théorie de la commande optimale est maintenant reconnue comme étant un cadre puissant pour l’élaboration de lois de commande pour la gestion énergétique des véhicules full-hybrides. Ces stratégies, dénommée « Stratégies de Minimisation de la Consommation Equivalente » (ECMS) sont basée sur le principe du Maximum de Pontryagin. Pour démontrer l’optimalité de l’ECMS, on doit supposer que les limites du système de stockage ne sont pas atteintes durant le cycle de conduite. Il n’est plus possible de faire cette hypothèse lorsque l’on considère les véhicules micro et mild hybrides étudiés dans cette thèse car la variable d’état atteint généralement plusieurs fois les bornes. Des outils mathématiques adaptés à l’étude des problèmes de commande avec contraintes sur l’état sont présentés et appliqués à deux problèmes en lien avec la gestion énergétique. Le premier problème consiste à déterminer le profil optimal de la tension aux bornes d’un pack d’ultra-capacités. Le second problème se concentre sur un système électrique intégrant deux stockeurs. L’accent est mis sur l’étude des conditions d’optimalités valables lorsque les contraintes sur l’état sont actives. Les conséquences de ces conditions pour la commande en ligne sont mises en avant et exploitées afin de concevoir une commande en temps réel. Les performances sont évaluées à l’aide d’un prototype. Une comparaison avec une approche de type ECMS plus classique est également présentée. / Parallel hybrid electric vehicles are generally propelled by an internal combustion engine, which is combined to a reversible electric machine. The power flows between these two traction devices are determined by a supervisory control algorithm, which aims at reducing the fuel consumption and possibly some polluting emissions. In the literature, optimal control theory is now recognized as a powerful framework for the synthesis of energy management strategies for full hybrid vehicles. These strategies are referred to as “Equivalent Consumption Minimization Strategies” (ECMS) and are based on the Pontryagin Maximum Principle. To demonstrate the optimality of ECMS, it must be assumed that the storage system limits are not reached during the drive cycle. This hypothesis cannot be made anymore when considering the micro and mild hybrid vehicles studied in this thesis because the state variable generally reaches several times the boundaries. Some mathematical tools suitable for the study of state constrained optimal control problems are introduced and applied to two energy management problems. The first problem consists in determining the optimal profile of the voltage across a pack of ultra-capacitors. The second problem focuses on a dual storage system. The stress is put on the study of the optimality conditions holding in case of active state constraints. Some consequences of these conditions for the online control are pointed out are exploited for the design of a real-time controller. Its performances are assessed using a demonstrator vehicle. A comparison with a classical ECMS-based approach is also provided.

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Le nombre de robot humanoïde s’est accru ces dernières années pour pouvoir collaborer avec l’homme ou le remplacer dans des tâches fastidieuses. L’objectif de cette thèse est de transférer aux robots humanoïdes, des habilités ou compétences humaines, en particulier pour des mouvements impliquant une coordination entre les deux bras. Dans la première partie de la thèse, un processus de conversion d’un mouvement humain vers un mouvement de robot, dans un objectif d’imitation est proposé. Comme les humains possèdent beaucoup plus de degrés de liberté qu’un robot humanoïde, les mouvements identiques ne peuvent pas être produits, les caractéristiques(longueurs des corps) peuvent aussi être différentes. Notre processus de conversion prend en compte l’enregistrement des localisations de marqueurs attachés aux corps de l’humain et des articulations pour améliorer les processus d’imitation. La deuxième partie de la thèse vise à analyser les stratégies de génération du mouvement utilisées par l’homme. Les mouvements humains sont supposés optimaux et notre objectif est de trouver un critère à minimiser pendant les manipulations. Nous faisons l’hypothèse que ce critère est une combinaison de critères classiquement utilisés en robotique et nous recherchons les poids de chaque critère qui représente au mieux le mouvement humain. De cette façon, une approche de commande cinématique optimale peut ensuite être utilisée pour générer des mouvements du robot humanoïde. / The number of humanoid robots has increased in recent years to be able to collaborate with humans or replace them in tedious tasks. The objective of this thesis is to transfer to humanoid robots, skills or human competences, in particular for movements involving coordination between the two arms. In the first part of the thesis, a process of conversion from a human movement to a robot movement, with the aim of imitation is proposed. Since humans have much more freedom than a humanoid robot, identical movements cannot be produced, the characteristics (body lengths) canal so be different. Our conversion process takes into account the recording of marker locations attached to human bodies and joints to improve the imitation processes. The second part of the thesis aims at analyzing the strategies used by humans to generate movement. Human movements are assumed to be optimal and our goal is to find criteria minimized during manipulations. We hypothesize that this criterion is a combination of classical criteria used in robotics and we look for the weights of each criterion that best represents human movement. In this way, an optimal kinematic control approach can then be used to generate movements of the humanoid robot.