Orientador: Juan Francisco Camino dos Santos / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-28T04:17:59Z (GMT). No. of bitstreams: 1 Burghi_ThiagoBassinello_M.pdf: 1840182 bytes, checksum: 3a2bb5b751172b5b4c8d9b1647b20748 (MD5) Previous issue date: 2015 / Resumo: O controle do movimento de robôs móveis em altas velocidades e sob condições adversas do solo é um problema difícil, pois as rodas do robô podem estar sujeitas a diferentes tipos de deslizamento. O deslizamento lateral é um problema particularmente complicado quando se lida com robôs móveis de tração diferencial, já que suas rodas não podem produzir movimento nessa direção. Este trabalho apresenta uma aplicação de alguns resultados da Teoria de Lyapunov para sistemas não lineares perturbados. A abordagem proposta pode ser vista como um método de análise de controladores cinemáticos de robôs móveis sujeitos a deslizamentos laterais e longitudinais. Um exemplo de aplicação é dado ao se analisar a estabilidade de um robô móvel de tração diferencial quando este é controlado por uma lei adaptativa não linear cinemática capaz de estimar o deslizamento longitudinal. É mostrado que sob condições razoáveis, as soluções da dinâmica do erro de postura do robô são uniformemente finalmente limitadas. Simulações numéricas são apresentadas para ilustrar esse exemplo. Para tratar um problema de otimização que surge durante a análise de estabilidade, técnicas de decomposição em soma de quadrados (SOS) para otimização polinomial são estudadas e aplicadas. Um estudo minucioso dos recursos computacionais necessários para a resolução de problemas de decomposição SOS também é apresentado / Abstract: Motion control of mobile robots at high speeds and under adverse ground conditions is a difficult problem because the robots¿ wheels may be subject to different kinds of slip. Lateral slip is a particularly complicated problem for differential drive mobile robots to deal with, since their wheels cannot directly produce movement in that direction. This work presents an application of some results from Lyapunov Theory for nonlinear perturbed systems. The proposed approach can be seen as a method for analyzing kinematic controllers of mobile robots subject to longitudinal and lateral slip. An example of application is given by analyzing the stability of a differential drive mobile robot when it is controlled by an adaptive nonlinear kinematic controller capable of estimating longitudinal slip. It is shown that under reasonable conditions, the solutions to the robot¿s posture error dynamics are uniformly ultimately bounded. Numerical simulations are presented to illustrate this example. To tackle an optimization problem which arises during the stability analysis, SOS techniques for polynomial optimization are studied and applied. A thorough study of the computational resources required for solving SOS problems is also presented / Mestrado / Mecanica dos Sólidos e Projeto Mecanico / Mestre em Engenharia Mecânica / 33003017 / CAPES

Em um problema de natureza hierárquica, o nível mais influente toma certas decisões que afetam o comportamento dos níveis inferiores. Cada decisão do nível mais influente é considerada como fixa pelos níveis inferiores, que, com tais informações, tomam decisões que maximizam seus objetivos. Essas decisões podem influenciar os resultados obtidos pelo nível superior, que, por sua vez, também anseia pela decisão ótima. Em programação matemática, este problema é modelado como um problema de programação em níveis. Neste trabalho, consideramos uma classe particular de problemas de programação em níveis: os problemas de programação matemática em dois níveis. Estudamos uma técnica de resolução que consiste em substituir o problema do nível inferior por suas condições necessárias de primeira ordem, que podem ser formuladas de diversas maneiras, conforme as restrições de complementaridade são modificadas. O novo problema torna-se um problema de programação não linear e pode ser resolvido com algoritmos clássicos de otimização. Com o auxílio de condições de otimalidade de primeira e segunda ordem mostramos as relações entre o problema original e o problema reformulado. Aplicamos a técnica a problemas encontrados na literatura, analisamos o seu comportamento e apresentamos estratégias para eliminar certos inconvenientes encontrados. / In problems of hierarchical nature, the choices made by the most influential level - the so-called leader - affect the behavior of the lower levels. For each one of the leader\'s decisions there is a response from the lower levels, which maximizes the value of their respective objectives. These optimal choices, in return, may have influence in the results achieved by the leader, which also wants to make the optimal choices. In mathematical programming, this kind of problem is described as a multilevel programming problem. The present work considers a specific kind of multilevel problem: the bilevel mathematical problem. We study a resolution technique which consists in replacing the lower level problem by its necessary first order conditions, which can be formulated in various ways, as complementarity constraints occur and are modified. The new reformulated problem is a nonlinear programming problem which can be solved by classical optimization methods. Using first and second order optimality conditions, we show the relations between the original bilevel problem and the reformulated problem. We apply the described technique to solve a set of bilevel problems taken from the literature, analyse their behavior and discuss strategies to prevent undesirable difficulties that may arise.

Neste trabalho, propomos um método de pontos interiores para minimização com restrições lineares de grande porte. Este método explora a linearidade das restrições, partindo de um ponto viável e preservando a viabilidade dos iterandos. Apresentamos os principais resultados de convergência global, além de uma descrição rica em detalhes de uma implementação prática de todos os passos do método. Para atestar a implementação do método, exibimos uma ampla experimentação numérica, e uma análise comparativa com métodos bem difundidos na comunidade de otimização contínua. / In this work, we propose an interior-point method for large-scale linearly constrained optimization. This method explores the linearity of the constraints, starting from a feasible point and preserving the feasibility of the iterates. We present the main global convergence results, together with a rich description of the implementation details of all the steps of the method. To validate the implementation of the method, we present a wide set of numerical experiments and a comparative analysis with well known softwares of the continuous optimization community.

Optimal Control (OC) is essentially a mathematical extremal problem. The procedure consists on the definition of a criterion to minimize (or maximize), some constraints that must be fulfilled and boundary conditions or disturbances affecting to the system behavior. The OC theory supplies methods to derive a control trajectory that minimizes (or maximizes) that criterion. This dissertation addresses the application of OC to automotive control problems at the powertrain level, with emphasis on the internal combustion engine. The necessary tools are an optimization method and a mathematical representation of the powertrain. Thus, the OC theory is reviewed with a quantitative analysis of the advantages and drawbacks of the three optimization methods available in literature: dynamic programming, Pontryagin minimum principle and direct methods. Implementation algorithms for these three methods are developed and described in detail. In addition to that, an experimentally validated dynamic powertrain model is developed, comprising longitudinal vehicle dynamics, electrical motor and battery models, and a mean value engine model. OC can be utilized for three different purposes: 1. Applied control, when all boundaries can be accurately defined. The engine control is addressed with this approach assuming that a the driving cycle is known in advance, translating into a large mathematical problem. Two specific cases are studied: the management of a dual-loop EGR system, and the full control of engine actuators, namely fueling rate, SOI, EGR and VGT settings. 2. Derivation of near-optimal control rules, to be used if some disturbances are unknown. In this context, cycle-specific engine calibrations calculation, and a stochastic feedback control for power-split management in hybrid vehicles are analyzed. 3. Use of OC trajectories as a benchmark or base line to improve the system design and efficiency with an objective criterion. OC is used to optimize the heat release law of a diesel engine and to size a hybrid powertrain with a further cost analysis. OC strategies have been applied experimentally in the works related to the internal combustion engine, showing significant improvements but non-negligible difficulties, which are analyzed and discussed. The methods developed in this dissertation are general and can be extended to other criteria if appropriate models are available. / El Control Óptimo (CO) es esencialmente un problema matemático de búsqueda de extremos, consistente en la definición de un criterio a minimizar (o maximizar), restricciones que deben satisfacerse y condiciones de contorno que afectan al sistema. La teoría de CO ofrece métodos para derivar una trayectoria de control que minimiza (o maximiza) ese criterio. Esta Tesis trata la aplicación del CO en automoción, y especialmente en el motor de combustión interna. Las herramientas necesarias son un método de optimización y una representación matemática de la planta motriz. Para ello, se realiza un análisis cuantitativo de las ventajas e inconvenientes de los tres métodos de optimización existentes en la literatura: programación dinámica, principio mínimo de Pontryagin y métodos directos. Se desarrollan y describen los algoritmos para implementar estos métodos así como un modelo de planta motriz, validado experimentalmente, que incluye la dinámica longitudinal del vehículo, modelos para el motor eléctrico y las baterías, y un modelo de motor de combustión de valores medios. El CO puede utilizarse para tres objetivos distintos: 1. Control aplicado, en caso de que las condiciones de contorno estén definidas. Puede aplicarse al control del motor de combustión para un ciclo de conducción dado, traduciéndose en un problema matemático de grandes dimensiones. Se estudian dos casos particulares: la gestión de un sistema de EGR de doble lazo, y el control completo del motor, en particular de las consignas de inyección, SOI, EGR y VGT. 2. Obtención de reglas de control cuasi-óptimas, aplicables en casos en los que no todas las perturbaciones se conocen. A este respecto, se analizan el cálculo de calibraciones de motor específicas para un ciclo, y la gestión energética de un vehículo híbrido mediante un control estocástico en bucle cerrado. 3. Empleo de trayectorias de CO como comparativa o referencia para tareas de diseño y mejora, ofreciendo un criterio objetivo. La ley de combustión así como el dimensionado de una planta motriz híbrida se optimizan mediante el uso de CO. Las estrategias de CO han sido aplicadas experimentalmente en los trabajos referentes al motor de combustión, poniendo de manifiesto sus ventajas sustanciales, pero también analizando dificultades y líneas de actuación para superarlas. Los métodos desarrollados en esta Tesis Doctoral son generales y aplicables a otros criterios si se dispone de los modelos adecuados. / El Control Òptim (CO) és essencialment un problema matemàtic de cerca d'extrems, que consisteix en la definició d'un criteri a minimitzar (o maximitzar), restriccions que es deuen satisfer i condicions de contorn que afecten el sistema. La teoria de CO ofereix mètodes per a derivar una trajectòria de control que minimitza (o maximitza) aquest criteri. Aquesta Tesi tracta l'aplicació del CO en automoció i especialment al motor de combustió interna. Les ferramentes necessàries són un mètode d'optimització i una representació matemàtica de la planta motriu. Per a això, es realitza una anàlisi quantitatiu dels avantatges i inconvenients dels tres mètodes d'optimització existents a la literatura: programació dinàmica, principi mínim de Pontryagin i mètodes directes. Es desenvolupen i descriuen els algoritmes per a implementar aquests mètodes així com un model de planta motriu, validat experimentalment, que inclou la dinàmica longitudinal del vehicle, models per al motor elèctric i les bateries, i un model de motor de combustió de valors mitjans. El CO es pot utilitzar per a tres objectius diferents: 1. Control aplicat, en cas que les condicions de contorn estiguen definides. Es pot aplicar al control del motor de combustió per a un cicle de conducció particular, traduint-se en un problema matemàtic de grans dimensions. S'estudien dos casos particulars: la gestió d'un sistema d'EGR de doble llaç, i el control complet del motor, particularment de les consignes d'injecció, SOI, EGR i VGT. 2. Obtenció de regles de control quasi-òptimes, aplicables als casos on no totes les pertorbacions són conegudes. A aquest respecte, s'analitzen el càlcul de calibratges específics de motor per a un cicle, i la gestió energètica d'un vehicle híbrid mitjançant un control estocàstic en bucle tancat. 3. Utilització de trajectòries de CO com comparativa o referència per a tasques de disseny i millora, oferint un criteri objectiu. La llei de combustió així com el dimensionament d'una planta motriu híbrida s'optimitzen mitjançant l'ús de CO. Les estratègies de CO han sigut aplicades experimentalment als treballs referents al motor de combustió, manifestant els seus substancials avantatges, però també analitzant dificultats i línies d'actuació per superar-les. Els mètodes desenvolupats a aquesta Tesi Doctoral són generals i aplicables a uns altres criteris si es disposen dels models adequats. / Reig Bernad, A. (2017). Optimal Control for Automotive Powertrain Applications [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90624 / TESIS

The HIV/AIDS epidemic and the COVID-19 pandemic have ruined many people's lives. Antiretroviral therapy (ART) has controlled the HIV/AIDS epidemic and COVID-19 vaccine is expected to ease confusion caused by the pandemic. However, the supply of health-resource falls far short of the demand in resource-constrained countries; thus, decision-making about resource allocation should be discussed. Botswana, as a resource-constrained country with a high prevalence of HIV, needs to construct its own framework for ART allocation. We propose an equitable framework for ART and COVID-19 vaccine allocation in Botswana based upon the egalitarian principle, which provides each individual has an equal chance of receiving them. We use a spatial mathematical model of treatment accessibility with an equity objective function, and sequential quadratic programming is used to address the nonlinear programming model. Considering Botswana's current health infrastructure, our strategy brings the most equal health outcomes. However, the disparity of accessibility still exists between rural and urban areas even from our equitable strategy. We present proposals that can increase the accessibility of rural areas using sensitivity analysis. Our work can be applied to different contexts, especially in sub-Saharan Africa.

The idea of this diploma thesis is an origin application of optimization models to solve a wage funds allocation problem on various institutes of each faculty. This diploma thesis includes an outline of linear programming models, nonlinear programming models, multiply programming models and parametric programming models. Studied questions are debating in wider context of distributing financial resources from the Budget of the Czech republic, through Ministry of education, youth and sports, universities, faculties after as much as various institutes. The accent is given on question of definition assessment scales of achievement criteria with general-purpose kvantification.

Les bruits et les polluants atmosphériques émis par les avions commerciaux représentent un défi environnemental important, un problème de santé publique et une contrainte économique pour le développement durable du transport aérien. D'un autre côté, le développement économique des régions est intimement lié au secteur du transport aérien. Ce dernier agit comme un multi-capteur économique pour supporter le développement régional et desservir les grands centres. Cette réalité s'explique entre autres par le fait que la mondialisation des marchés impose l'utilisation de moyens rapides et compétitifs pour le transport des voyageurs et des marchandises. Notre approche est une modélisation mathématique du problème de choix des trajectoires de vol dans un domaine continu. La première étape dans la modélisation d'un tel problème est l'écriture des équations qui traduisent la dynamique de vol de l'avion. Ensuite, vient la modélisation est la synthèse des critères d'optimisation. Les critères qu'on a retenus dans notre travail sont la consommation de carburant (critère d'énergie) et le bruit perçu au sol (critère de la gêne occasionnée pour les riverains). En combinant les deux parties "modèle de la dynamique du vol" et "critères d'optimisation", et en intégrant d'autres contraintes liées à la sécurité du vol, on aboutit à un modèle mathématique qui appartient à la classe des problèmes non linéaires de contrôle optimal. C'est une classe difficile de problèmes d'optimisation qui pose un certain nombre de difficultés lors de la construction d'algorithmes de résolution. Pour résoudre le problème ainsi posé, deux approches distinctes peuvent être envisagées : méthodes directes et méthodes indirectes. Nous avons implémenté une méthode dite " pseudo spectrale de Gauss " pour la résolution du problème de contrôle. Le choix de cette méthode est basé sur une propriété très importante et qui garantit l'équivalence entre l'application des deux schémas : direct et indirects. Des résultats sont présentés et discutés. Nos résultats donnent des pistes sur de nouvelles procédures de vol qui minimisent le bruit et la consommation de carburant durant les phases d'atterrissage et de décollage. Par ailleurs, la résolution numérique consolide également le potentiel des approches CDA recommandées par l'OACI. Une comparaison aux procédures standards et une analyse de sensibilité aux critères est présentée / Noise and air pollution from commercial aircraft represent a significant environmental challenge, a public health problem and an economic constraint to the sustainable development of air transport. On the other hand, the economical development of the regions is closely linked to the airline industry. This fact is partly explained by the the globalization of markets that requires the use of fast and competitive means to transport people and goods. We propose a mathematical model to tackle this problem by optimizing flight paths in order to minimize noise emission and fuel consumption. The first step is to express the dynamics of flight of the aircraft. Then comes the synthesis of optimization criteria. The criteria we used in our work are the fuel consumption (criterion of energy) and the perceived noise levels at the ground (criterion of inconvenience for local residents). By combining the two previous parts, and incorporating other constraints related to flight safety, we obtain a mathematical model that belongs to a class of nonlinear optimal control problems. It is a difficult class of optimization problems that raises several difficulties during the construction of solving algorithms. Two different ways can be considered to solve this problem : direct methods and indirect methods. We have developed and implemented a direct method called "Gauss Pseudo-spectral Method" to solve the optimal control problem that we obtained. The choice of this method is based on a very important property that guarantees the equivalence between the use of two schemes : direct and indirect. Results are presented and discussed. Our results provide a new view on flight procedures that minimize noise and fuel consumption during landings and takeoffs. Moreover, the numerical solution also consolidates the potential of CDA approaches which are recommended by ICAO. A comparison with standard procedures and a sensitivity analysis are presented

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Zweitveröffentlichung, ursprünglich veröffentlicht: Jonas Holley: Stress-Constrained Topology Optimization with Application to the Design of Electrical Machines. München: Verlag Dr. Hut, 2023, 199 Seiten, Dissertation Humboldt-Universität Berlin (2023). ISBN 978-3-8439-5378-8 / Während des Designprozesses physischer Gegenstände stellt die mechanische Stabilität in nahezu jedem Anwendungsbereich eine essentielle Anforderung dar. Stabilität kann mittels geeigneter Kriterien, die auf dem mechanischen Spannungstensor basieren, mathematisch quantifiziert werden. Dies dient dem Ziel der Vermeidung von Schädigung in jedem Punkt innerhalb des Gegenstands. Die vorliegende Arbeit behandelt die Entwicklung einer Methode zur Lösung von Designoptimierungsproblemen mit punktweisen Spannungsrestriktionen. Zunächst wird eine Regularisierung des Optimierungsproblems eingeführt, die einen zentralen Baustein für den Erfolg einer Lösungsmethode darstellt. Nach der Analyse des Problems hinsichtlich der Existenz von Lösungen wird ein Gradientenabstiegsverfahren basierend auf einer impliziten Designdarstellung und dem Konzept des topologischen Gradienten entwickelt. Da der entwickelte Ansatz eine Methode im Funktionenraum darstellt, ist die numerische Realisierung ein entscheidender Schritt in Richtung der praktischen Anwendung. Die Diskretisierung der Zustandsgleichung und der adjungierten Gleichung bildet die Basis für eine endlich-dimensionale Version des Optimierungsverfahrens. Im letzten Teil der Arbeit werden numerische Experimente durchgeführt, um die Leistungsfähigkeit des entwickelten Algorithmus zu bewerten. Zunächst wird das Problem des minimalen Volumens unter punktweisen Spannungsrestriktionen anhand der L-Balken Geometrie untersucht. Ein Schwerpunkt wird hierbei auf die Untersuchung der Regularisierung gelegt. Danach wird das multiphysikalische Design einer elektrischen Maschine adressiert. Zusätzlich zu den punktweisen Restriktionen an die mechanischen Spannungen wird die Maximierung des mittleren Drehmoments berücksichtigt, um das elektromagnetische Verhalten der Maschine zu optimieren. Der Erfolg der numerischen Tests demonstriert das Potential der entwickelten Methode in der Behandlung realistischer industrieller Problemstellungen. / In the process of designing a physical object, the mechanical stability is an essential requirement in nearly every area of application. Stability can be quantified mathematically by suitable criteria based on the stress tensor, aiming at the prevention of damage in each point within the physical object. This thesis deals with the development of a framework for the solution of optimal design problems with pointwise stress constraints. First, a regularization of the optimal design problem is introduced. This perturbation of the original problem represents a central element for the success of a solution method. After analyzing the perturbed problem with respect to the existence of solutions, a line search type gradient descent scheme is developed based on an implicit design representation via a level set function. The core of the optimization method is provided by the topological gradient, which quantifies the effect of an infinitesimal small topological perturbation of a given design on an objective functional. Since the developed approach is a method in function space, the numerical realization is a crucial step towards its practical application. The discretization of the state and adjoint equation provide the basis for developing a finite-dimensional version of the optimization scheme. In the last part of the thesis, numerical experiments are conducted in order to assess the performance of the developed algorithm. First, the stress-constrained minimum volume problem for the L-Beam geometry is addressed. An emphasis is put on examining the effect of the proposed regularization. Afterwards, the multiphysical design of an electrical machine is addressed. In addition to the pointwise constraints on the mechanical stress, the maximization of the mean torque is considered in order to improve the electromagnetic performance of the machine. The success of the numerical tests demonstrate the potential of the developed design method in dealing with real industrial problems.

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