The robotic platform presented in this thesis is underdamped with high inertia and can store potential energy in its compliant joints, making it ideal for many different types of real-world tasks for which traditional rigid-robots are ill-suited. Some real-world tasks suited to soft robots include high impact tasks like hammering a nail into a wall or moving heavy objects with other robot or human teammates while using relatively little power. Some of the same characteristics which make soft robots useful, such as their underdamped, highly compliant joints, also make motion planning and control for soft robots difficult. In this thesis, a novel method is introduced to take high-level, real world tasks and generate trajectories for soft robots to complete those real world tasks. The generated trajectories are designed to be dynamically and kinematically feasible for a soft robot. An optimization is introduced that uses a cost function to move the tip of a robot from point A to point B in task space. Experiments conducted in simulation and on hardware show that a soft robot with a length of 1.19 meters is able to track a high-speed and dynamic trajectory generated with this optimization with a reported median magnitude of error of 0.032 meters between the planned and actual end effector trajectories. This thesis also introduces an adaptation of a Model Reference Adaptive Controller (MRAC) that causes a high degree of freedom and nonlinear soft robot to behave like a 2nd-order, critically damped system. This allows us to approximate the dynamics of the robot as 2nd-order to more easily generate trajectories for highly dynamic tasks like throwing a ball. An optimization is developed to generate ball-throwing trajectories. Experiments conducted in simulation and on hardware show that a soft robot can throw a ball within 0.13 meters of a goal point in simulation (where the goal point is 2.85 meters from the robot) and 0.5 meters of a goal point on hardware (where the goal point is 2 meters from the robot). The methods developed in this thesis enable soft robots to more easily complete high-level tasks through dynamically and kinematically feasible task and joint space trajectory generation.

No description available.

Transient regimes experienced by dynamic systems may have severe impacts on the operation of the aircraft. They are often regulated by dynamic constraints, requiring the dynamic signals to remain within bounds whose values vary with time. The verification of these peculiar types of constraints, which generally requires high-fidelity time-domain simulation, intervenes late in the system development process, thus potentially causing costly design iterations. The research objective of this thesis is to develop a methodology that integrates the verification of dynamic constraints in the early specification of dynamic systems. In order to circumvent the inefficiencies of time-domain simulation, multivariate dynamic surrogate models of the original time-domain simulation models are generated using wavelet neural networks (or wavenets). Concurrently, an alternate approach is formulated, in which the envelope of the dynamic response, extracted via a wavelet-based multiresolution analysis scheme, is subject to transient constraints. Dynamic surrogate models using sigmoid-based neural networks are generated to emulate the transient behavior of the envelope of the time-domain response. The run-time efficiency of the resulting dynamic surrogate models enables the implementation of a data farming approach, in which the full design space is sampled through a Monte-Carlo Simulation. An interactive visualization environment, enabling what-if analyses, is developed; the user can thereby instantaneously comprehend the transient response of the system (or its envelope) and its sensitivities to design and operation variables, as well as filter the design space to have it exhibit only the design scenarios verifying the dynamic constraints. The proposed methodology, along with its foundational hypotheses, is tested on the design and optimization of a 350VDC network, where a generator and its control system are concurrently designed in order to minimize the electrical losses, while ensuring that the transient undervoltage induced by peak demands in the consumption of a motor does not violate transient power quality constraints.

[pt] Otimização estrutural sujeita a carregamentos dinâmicos é um problema desafiador em vários aspectos, a começar pelo grande número de restrições que devem ser atendidas em todos os instantes de tempo. Além disso, o custo computacional para avaliar os gradientes destas restrições é bastante elevado e requer um grande espaço de armazenamento. Na literatura, alguns métodos reduzem o número de restrições avaliando em instantes de tempo selecionados, como o pior caso por exemplo, ou ainda constroem um funcional equivalente, integrando as restrições violadas ao longo do tempo, assim eliminando essa dependência. Nesta dissertação, o método do Carregamento Estático Equivalente (ESL) é utilizado, no qual o problema dinâmico original é transformado em uma sequência de subproblemas de otimização linear estática com múltiplos casos de carga. Um atrativo deste método é a possibilidade da solução de problemas não lineares, evitando o alto custo devido às repetidas análises estruturais e cálculos das restrições. Problemas clássicos de treliças planas submetidas a carregamentos dinâmicos são resolvidos utilizando o método ESL. A função a ser minimizada é a massa da treliça, que está sob restrições de tensão e deslocamento, onde as variáveis de projeto são as áreas da seção transversal dos membros. Além disso, uma interface utilizando ANSYS e MATLAB é desenvolvida para uma abordagem modular, na qual a análise via elementos finitos e a otimização possam ser realizadas separadamente. Este processo viabiliza a otimização de estruturas que apresentam comportamentos não lineares a partir da utilização de diversos softwares comerciais disponíveis no mercado. / [en] Structural optimization subject to dynamic loading is a challenging problem in many aspects, starting with the large number of constraints that must be respected at all instants of time. Furthermore, the computational cost to evaluate the gradients of these constraints is significantly high and requires a large storage space. In the literature, some methods reduce the number of constraints evaluating at selected instants of time, such as the worst case. Alternatively, a single equivalent functional is constructed to eliminate the time dependence by integrating the violated constraints over time. In this work, the Equivalent Static Load (ESL) method is used, in which the original dynamic problem is reduced into a number of static linear optimization problems with multiple load cases. An attractive feature of this method is the possibility of solving non-linear problems, avoiding the high cost due to repeated structural analyzes and constraint calculations. Classical problems of plane trusses subjected to dynamic loads are solved using the ESL method. The function to be minimized is the truss mass, which is subjected to stress and displacement constraints, where the design variables are the cross-sectional areas of the members. In addition, an interface using ANSYS and MATLAB was developed for a modular approach, in which finite element analysis and optimization can be performed separately. This process makes possible the optimization of structures that present non-linear behavior from the use of most structural analysis software packages available on the market.

No description available.

Dans un contexte industriel aéronautique où les problématiques de sécurité constituent un facteur différentiateur clé, l’objectif de cette thèse est de répondre à la problématique ambitieuse de la réduction des accidents de type opérationnel. Les travaux de recherche s’inscrivent dans le domaine des systèmes d’alarmes pour l’évitement de collision qui ne font pas une analyse approfondie des solutions d’évitement par rapport à la situation de danger. En effet, les situations d’urgence en vol ne bénéficient pas à ce jour d’une représentation et d’un guide des solutions associées formels. Bien que certains systèmes d’assistance existent et qu’une partie de la connaissance associée aux situations d’urgence ait pu être identifiée, la génération dynamique d’une séquence de manœuvres sous fortes contraintes de temps et dans un environnement non connu à l’avance représente une voie d’exploration nouvelle. Afin de répondre à cette question et de rendre objective la notion de danger, les travaux de recherche présentés dans cette thèse mettent en confrontation la capacité d’évolution d’un aéronef dans son environnement immédiat avec une enveloppe physique devenant contraignante. Afin de mesurer ce danger, les travaux de recherche ont conduit à construire un module de trajectoires capable d’explorer l’espace en 3D. Cela a permis de tirer des enseignements en terme de flexibilité des manœuvres d’évitement possibles à l’approche du sol. De plus l’elicitation des connaissances des pilotes et des experts d’Airbus Helicopters (ancien Eurocopter) mis en situation d’urgence dans le cas d’accidents reconstitués en simulation a conduit à un ensemble de paramètres pour l’utilisation de la méthode multicritère PROMETHEE II dans le processus de prise de décision relatif au choix de la meilleure trajectoire d’évitement et par conséquent à la génération d’alarmes anti-collision. / In the aeronautics industrial context, the issues related to the safety constitute a highly differentiating factor. This PhD thesis addresses the challenge of operational type accident reduction. The research works are positioned and considered within the context of existing alerting equipments for collision avoidance, who don’t report a thorough analysis of the avoidance manoeuvres with respect to a possible threat. Indeed, in-flight emergency situations are various and do not all have a formal representation of escape procedures to fall back on. Much of operational accident scenarios are related to human mistakes. Even if systems providing assistance already exist, the dynamic generation of a sequence of manoeuvres under high constraints in an unknown environment remain a news research axis, and a key development perspective. In order to address this problematic and make the notion of danger objective, the research works presented in this thesis confront the capabilities of evolution of an aircraft in its immediate environment with possible physical constraints. For that purpose, the study has conducted to generate a module for trajectory generation in the 3D space frame, capable of partitioning and exploring the space ahead and around the aircraft. This has allowed to draw conclusions in terms of flexibility of escape manoeuvres on approach to the terrain. Besides, the elicitation of the Airbus Helicopters (former Eurocopter) experts knowledge put in emergency situations, for reconstituted accident scenarios in simulation, have permitted to derive a certain number of criteria and rules for parametrising the multicriteria method PROMETHEE II in the process for the relative decision-making of the best avoidance trajectory solution. This has given clues for the generation of new alerting rules to prevent the collisions.