En bergslänts stabilitet styrs av berggrundens egenskaper, så som sprickegenskaper och bergkvalité. För att uppnå önskad stabilitet i en bergslänt behöver de bergmekaniska parametrarna kartläggas och analyseras för att fastställa risker och stabilitetsåtgärder. Syftet med studien är att utvärdera kvalitén på bergteknisk data från digitalfotogrammetriska 3D-modeller genom att jämföra resultatet med manuella mätningar från konventionell kartläggning. Målet är även att utforska potentialen för användning av fotogrammetrisk 3D-modellering vid stabilitetsanalyser i bergslänter genom att utvärdera den bergtekniska analys som kan göras utifrån fotogrammetrisk data. Sprickmätningar framtagna från 3D-modellen visade sig ha samma kvalité som manuella mätningar tagna enligt konventionell metod. Den UAS-baserade fotogrammetrin kan dock inte ersätta den konventionella analysen helt vid stabilitetsanalyser men kan användas som ett kompletterande verktyg i bergtekniska undersökningar. Fotogrammetrin möjliggör datainsamling från ett säkrare avstånd vilket minskar riskmomenten som den konventionella metoden medför vid arbete i fält. Den digitala metoden visade sig även ha fler fördelar såsom möjligheten av kartläggning och analysering framför datorn för mindre tids- och kostnadskrävande moment, digital datalagring samt att slänter med begränsad åtkomst kan karteras. / The stability of a rock slope is controlled by the rock’s mechanical properties, such as rock quality and facets. To achieve the desired stability in a rock slope, the mechanical parameters need to be mapped and analysed to determine possible failures and decide necessary stability measures. The purpose of this study is to evaluate the quality of rock technical data from digital photogrammetry 3D models by comparing the result with manual measurements from conventional mapping. The goal is also to explore the potential uses of photogrammetric 3D models for rock slope stability analyses by evaluate the photogrammetric data. Facets extracted from 3D models were found to have the same quality as manual measurements. However, the UAS-based method cannot completely replace the conventional method but can be useful as a complementary tool. Photogrammetry enables the collection of data from a safer distance, which reduces workplace hazards that the conventional method entails. The digital method also proved to have more advantages, such as the possibility of digital mapping and analysing which is less costly and time-consuming, digital data storage and the possibility to access outcrops that can’t be mapped with manually measurements due to inaccessibility.

Networked predictive control is a new research method for Networked Control Systems (NCS), which is able to handle network-induced problems such as time-delay, data dropouts, packets disorders, etc. while stabilizing the closed-loop system. This work is an extension and complement of networked predictive control methodology. There is always present model uncertainties or physical nonlinearity in the process of NCS. Therefore, it makes the study of the robust control of NCS and that of networked nonlinear control system (NNCS) considerably important. This work studied the following three problems: the robust control of networked predictive linear control systems, the control scheme for networked nonlinear control systems (NNCS) and the robust control of NNCS. The emphasis is on stability analysis and the design of robust control. This work adapted the two control schemes, namely, the time-driven and the event driven predictive controller for the implementation of NCS. It studied networked linear control systems and networked nonlinear control systems. Firstly, time-driven predictive controller is used to compensate for the networked-induced problems of a class of networked linear control systems while robustly stabilizing the closed-loop system. Secondly, event-driven predictive controller is applied to networked linear control system and NNCS and the work goes on to solve the robust control problem. The event-driven predictive controller brings great benefits to NCS implementation: it makes the synchronization of the clocks of the process and the controller unnecessary and it avoids measuring the exact values of the individual components of the network induced time-delay. This work developed the theory of stability analysis and robust synthesis of NCS and NNCS. The robust stability analysis and robust synthesis of a range of different system configurations have been thoroughly studied. A series of methods have been developed to handle the stability analysis and controller design for NCS and NNCS. The stability of the closed-loop of NCS has been studied by transforming it into that of a corresponding augmented system. It has been proved that if some equality conditions are satisfied then the closed-loop of NCS is stable for an upper-bounded random time delay and data dropouts. The equality conditions can be incorporated into a sub-optimal problem. Solving the sub-optimal problem gives the controller parameters and thus enables the synthesis of NCS. To simplify the calculation of solving the controller parameters, this thesis developed the relationship between networked nonlinear control system and a class of uncertain linear feedback control system. It proves that the controller parameters of some types of networked control system can be equivalently derived from the robust control of a class of uncertain linear feedback control system. The methods developed in this thesis for control design and robustness analysis have been validated by simulations or experiments.

>Magister Scientiae - MSc / We review a number of compartmental models in epidemiology which leads to a nonlinear system of ordinary differential equations. We focus an SIR, SEIR and SIS epidemic models with and without vaccination. A threshold parameter R0 is identified which governs the spread of diseases, and this parameter is known as the basic reproductive number. The models have at least two equilibria, an endemic equilibrium and the disease-free equilibrium. We demonstrate that the disease will die out, if the basic reproductive number R0 < 1. This is the case of a disease-free state, with no infection in the population. Otherwise the disease may become endemic if the basic reproductive number R0 is bigger than unity. Furthermore, stability analysis for both endemic and disease-free steady states are investigated and we also give some numerical simulations. The second part of this dissertation deals with optimal vaccination strategy in epidemiology. We use optimal control technique on vaccination to minimize the impact of the disease. Hereby we mean minimizing the spread of the disease in the population, while also minimizing the effort on vaccination roll-out. We do this optimization for the cases of SIR and SEIR models, and show how optimal strategies can be obtained which minimize the damage caused by the infectious disease. Finally, we describe the numerical simulations using the fourth-order Runge-Kutta method.

La thèse est relative à la compréhension de la physique et au contrôle des émissions acoustiques dans les jets turbulents simples et double-flux. La génération du bruit est associé à des structures turbulentes de grandes tailles caractéristiques et à la turbulence de petites échelles. i Il est maintenant admis que les structures de grandes échelles sont des instabilités se propageant dans un champ moyen turbulent. Ici elle sont analysées sur la base de la théorie linéaire non locale appelées PSE pour Parabolized Stability Equations. Ces instabilités inflexionnelles associées à la présence de couche de cisaillement sont des modes de Kelvin-Helmhotz. Dans le cas du jet sous détentu des cellules de choc apparaissent et influencent très fortement les taux d'amplification et fréquences des modes propres. Divers écoulements sont investigués, de faible nombre de Mach au jet double-flux supersonique dont le champ moyen provient de simulation LES (Cerfacs). Le champ acoustique lointain est déterminé par l'analogie de Ffowcs-Williams-Hawkings. Ensuite une étude de sensibilité originales des instabilités et du bruits par rapport à divers forage locaux est produite sur la base deséquations de stabilité PSE adjointes. Les fortes sensibilités apparaissent dans les couches de cisaillements et aussi dans une moindre mesure autour des cellules de chocs. Les sensibilités sont plus complexes pour le jet double flux et dépendent du mode instable étudié lié soit au jet primaire soit au jet secondaire. Les sensibilités maximales se trouvent auvoisinage de la sortie de la tuyère et à la limite ou à l’extérieur du cne potentiel. En complément une étudesur le jet simple flux permet de mettre en rapport les approches de quantification d'incertitude et la sensibilité calculée par des équations adjointes. Les résultats de sensibilité vont permettre de contribuer à proposer des stratégies de contrôle aero-acoustique dans les jets de turboréacteurs. / This thesis leads to a better knowledge of the physic and of the control of acoustic radiation in turbulent single and dual-stream jets.It is known that jet noise is produced by the turbulence present in the jet that can be separated in large coherent structures and fine structures. It is also concluded that these large-scale coherent structures are the instability waves of the jet and can be modelled as the flow field generated by the evolution of instability waves in a given turbulent jet. The growth rate and the streamwise wavenumber of a disturbance with a fixed frequency and azimuthal wavenumber are obtained by solving the non-local approach called Parabolized Stability Equations (PSE). Typically the Kelvin-Helmholtz instability owes its origin into the shear layer of the flow and, moreover, the inflection points of the mean velocity profile has a crucial importance in the instability of such a flow. The problem is more complex in case of imperfectly expanded jet where shock-cells manifest inside the jet and strongly interaction with the instability waves has been observed. Several configurations are tested in this thesis, from a subsonic incompressible case to the dual-stream underexpanded supersonic jet obtained by solving Large Eddy Simulations LES (CERFACS). The acoustic far-field is determined by the Ffowcs-Williams-Hawkings acoustic analogy. Then a sensitivity analysis of the jet with respect to external forcing acting in a localized region of the flow are investigated by solving the adjoint PSE equations. High sensitivity appeared in the shear-layer of the flow showing, also, a high dependency in the streamwise and radial direction. In the case of dual-stream jet the propagation of the instability in the inner and outer shear layer should be taken into account. This configuration leads to two different distinct Klevin-Helmholtz modes that are computed separately. The highest sensitivity is determined in the exit of the nozzle outside of the potential core of the jet. In addition, comparison between sensitivity computed by adjoint equations and Uncertainty Quantification (UQ) methods has been done, in the case of a single-stream jet, showing a link between these two methods for small variations of the input parameters. This result leads to the application of a lower cost tool for mathematical analysis of complex problem of industrial interest. This work and in particular the sensitivity theory investigated in this thesis contribute to a development of a new noise control strategy for aircraft jet.

Doctor of Philosophy / Electrical and Computer Engineering / Balasubramaniam Natarajan / A cyber-physical system (CPS) typically consists of networked computational elements that control physical processes. As an integral part of CPS, the widespread deployment of communicable sensors makes the task of monitoring and control quite challenging especially from the viewpoint of scalability and complexity. This research investigates two unique aspects of overcoming such barriers, making a CPS more robust against data explosion and network vulnerabilities. First, the correlated characteristics of high-resolution sensor data are exploited to significantly reduce the fused data volume. Specifically, spatial, temporal and spatiotemporal compressed sensing approaches are applied to sample the measurements in compressed form. Such aggregation can directly be used in centralized static state estimation even for a nonlinear system. This approach results in a remarkable reduction in communication overhead as well as memory/storage requirement. Secondly, an agent based architecture is proposed, where the communicable sensors (identified as agents) also perform local information processing. Based on the local and underdetermined observation space, each agent can monitor only a specific subset of global CPS states, necessitating neighborhood information exchange. In this framework, we propose an agent based static state estimation encompassing local consensus and least square solution. Necessary bounds for the consensus weights are obtained through the maximum eigenvalue based convergence analysis and are verified for a radial power distribution network. The agent based formulation is also applied for a linear dynamical system and the consensus approach is found to exhibit better and more robust performance compared to a diffusion filter. The agent based Kalman consensus filter (AKCF) is further investigated, when the agents can choose between measurements and/or consensus, allowing the economic allocation of sensing and communication tasks as well as the temporary omission of faulty agents. The filter stability is guaranteed by deriving necessary consensus bounds through Lyapunov stability analysis. The states dynamically estimated from AKCF can be used for state-feedback control in a model predictive fashion. The effect of lossy communication is investigated and critical bounds on the link failure rate and the degree of consensus that ensure stability of the agent based control are derived and verified via simulations.

abstract: In this thesis, we focus on some of the NP-hard problems in control theory. Thanks to the converse Lyapunov theory, these problems can often be modeled as optimization over polynomials. To avoid the problem of intractability, we establish a trade off between accuracy and complexity. In particular, we develop a sequence of tractable optimization problems - in the form of Linear Programs (LPs) and/or Semi-Definite Programs (SDPs) - whose solutions converge to the exact solution of the NP-hard problem. However, the computational and memory complexity of these LPs and SDPs grow exponentially with the progress of the sequence - meaning that improving the accuracy of the solutions requires solving SDPs with tens of thousands of decision variables and constraints. Setting up and solving such problems is a significant challenge. The existing optimization algorithms and software are only designed to use desktop computers or small cluster computers - machines which do not have sufficient memory for solving such large SDPs. Moreover, the speed-up of these algorithms does not scale beyond dozens of processors. This in fact is the reason we seek parallel algorithms for setting-up and solving large SDPs on large cluster- and/or super-computers. We propose parallel algorithms for stability analysis of two classes of systems: 1) Linear systems with a large number of uncertain parameters; 2) Nonlinear systems defined by polynomial vector fields. First, we develop a distributed parallel algorithm which applies Polya's and/or Handelman's theorems to some variants of parameter-dependent Lyapunov inequalities with parameters defined over the standard simplex. The result is a sequence of SDPs which possess a block-diagonal structure. We then develop a parallel SDP solver which exploits this structure in order to map the computation, memory and communication to a distributed parallel environment. Numerical tests on a supercomputer demonstrate the ability of the algorithm to efficiently utilize hundreds and potentially thousands of processors, and analyze systems with 100+ dimensional state-space. Furthermore, we extend our algorithms to analyze robust stability over more complicated geometries such as hypercubes and arbitrary convex polytopes. Our algorithms can be readily extended to address a wide variety of problems in control such as Hinfinity synthesis for systems with parametric uncertainty and computing control Lyapunov functions. / Dissertation/Thesis / Doctoral Dissertation Mechanical Engineering 2016

Orientador: Fábio Roberto Chavarette / Resumo: São diversos os equipamentos de engenharia que apresentam vibrações mecânicas, e estas podem ser observadas em forma de acelerações, deslocamentos e velocidade. Os primeiros estudos envolvendo vibrações foram direcionados aos fenômenos naturais e modelagem matemática de sistemas vibrantes, então, começou a aplicação desses estudos em equipamentos de engenharia. Vibrações mecânicas, na maioria dos sistemas dinâmicos, são consideradas como algo indesejado e podem ser danosos. Porém, existem situações que são utilizadas para melhorar o funcionamento e desempenho de máquinas. São diversas as causas de vibrações em sistemas de engenharia, neste trabalho, destaca-se as vibrações causadas por impacto. Quando componentes destes sistemas impactam entre si, causando ruídos de curta duração, são caracterizados como sistemas tipo vibro - impacto. Podem ser citados diversos equipamentos com essas características, como rolos compactadores de solo, martelos de impacto, perfuratrizes de solo, etc. Neste trabalho, demonstra-se o comportamento dinâmico de um sistema vibro – impactante. Para análise deste sistema, foram desenvolvidos códigos computacionais, através do software Octave. No diagrama de estabilidade de Lyapunov, verificou-se que, pontualmente o sistema se apresenta de forma estável. A partir da variação da frequência de excitação, foi observado através dos históricos no tempo, espectros de frequência, mapas de Poincaré e planos de fase, um comportamento periódico e estável, com sit... (Resumo completo, clicar acesso eletrônico abaixo) / Mestre

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-06-06T12:39:52Z No. of bitstreams: 1 viniciuscampistabrum.pdf: 846002 bytes, checksum: 5ac93812c3739c70741f6052b77b22c8 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-06-06T14:06:19Z (GMT) No. of bitstreams: 1 viniciuscampistabrum.pdf: 846002 bytes, checksum: 5ac93812c3739c70741f6052b77b22c8 (MD5) / Made available in DSpace on 2017-06-06T14:06:19Z (GMT). No. of bitstreams: 1 viniciuscampistabrum.pdf: 846002 bytes, checksum: 5ac93812c3739c70741f6052b77b22c8 (MD5) Previous issue date: 2015-08-28 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Análise de agrupamento é uma tarefa descritiva e não-supervisionada de mineração de dados que utiliza amostras não-rotuladas com o objetivo de encontrar grupos naturais, isto é, grupos de amostras fortemente relacionadas de forma que as amostras que per-tençam a um mesmo grupo sejam mais similares entre si do que amostras em qualquer outro grupo. Avaliação ou validação é considerada uma tarefa essencial dentro da análise de agrupamento. Essa tarefa apresenta técnicas que podem ser divididas em dois tipos: técnicas não-supervisionadas ou de validação interna e técnicas supervisionadas ou de va-lidação externa. Trabalhos recentes introduziram uma abordagem de validação interna que busca avaliar e melhorar a estabilidade do algoritmo de agrupamento por meio de identificação e remoção de amostras que são consideradas prejudiciais e, portanto, de-veriam ser estudadas isoladamente. Por meio de experimentos foi identificado que essa abordagem apresenta características indesejáveis que podem resultar em remoção de todo um grupo e ainda não garante melhoria de estabilidade. Considerando essas questões, neste trabalho foi desenvolvida uma abordagem mais ampla utilizando algoritmo genético para análise de agrupamento e estabilidade de dados. Essa abordagem busca garantir melhoria de estabilidade, reduzir o número de amostras para remoção e permitir que o usuário controle o processo de análise de estabilidade, o que resulta em maior aplicabi-lidade e confiabilidade para tal processo. A abordagem proposta foi avaliada utilizando diferentes algoritmos de agrupamento e diferentes bases de dados, sendo que uma base de dados genotípicos também foi utilizada com o intuito de aquisição e validação de conhe-cimento. Os resultados mostram que a abordagem proposta é capaz de garantir melhoria de estabilidade e também é capaz de reduzir o número de amostras para remoção. Os resultados também sugerem a utilização da abordagem como uma ferramenta promissora para aquisição e validação de conhecimento em estudos de associação ampla do genoma (GWAS). Este trabalho apresenta uma abordagem que contribui para aquisição e valida-ção de conhecimento por meio de análise de agrupamento e estabilidade de dados. / Clustering analysis is a descriptive and unsupervised data mining task, which uses non-labeled samples in order to find natural groups, i.e. groups of closely related samples such that samples within the same cluster are more similar than samples within the other clusters. Evaluation and validation are considered essential tasks within the clustering analysis. These tasks present techniques that can be divided into two kinds: unsuper-vised or internal validation techniques and supervised or external validation techniques. Recent works introduced an internal clustering validation approach to evaluate and im-prove the clustering algorithm stability through identifying and removing samples that are considered harmful and therefore they should be studied separately. Through experi-mentation, it was identified that this approach has two undesirable characteristics, it can remove an entire cluster from dataset and still decrease clustering stability. Taking into account these issues, in this work a broader approach was developed using genetic algo-rithm for clustering and data stability analysis. This approach aims to increase stability, to reduce the number of samples for removal and to allow the user control the stability analysis process, which gives greater applicability and reliability for such process. This approach was evaluated using different kinds of clustering algorithm and datasets. A genotype dataset was also used in order to knowledge acquisition and validation. The results show the approach proposed in this work is able to increase stability, and it is also able to reduce the number of samples for removal. The results also suggest the use of this approach as a promising tool for knowledge acquisition and validation on genome-wide association studies (GWAS). This work presents an approach that contributes for knowledge acquisition and validation through clustering and data stability analysis.

Magister Scientiae - MSc / Efficient numerical approaches for parameter dependent problems have been an inter- esting subject to numerical analysts and engineers over the past decades. This is due to the prominent role that these problems play in modeling many real life situations in applied sciences. Often, the choice and the e ciency of the approaches depend on the nature of the problem to solve. In this work, we consider the general linear first-order singularly perturbed Volterra integro-differential equations (SPVIDEs). These singularly perturbed problems (SPPs) are governed by integro-differential equations in which the derivative term is multiplied by a small parameter, known as "perturbation parameter". It is known that when this perturbation parameter approaches zero, the solution undergoes fast transitions across narrow regions of the domain (termed boundary or interior layer) thus affecting the convergence of the standard numerical methods. Therefore one often seeks for numerical approaches which preserve stability for all the values of the perturbation parameter, that is "numerical methods. This work seeks to investigate some "numerical methods that have been used to solve SPVIDEs. It also proposes alternative ones. The various numerical methods are composed of a fitted finite difference scheme used along with suitably chosen interpolating quadrature rules. For each method investigated or designed, we analyse its stability and convergence. Finally, numerical computations are carried out on some test examples to con rm the robustness and competitiveness of the proposed methods.

Alors qu'il est bien connu que le phénomène d'instabilité de Faraday est une manifestation d'ondes de gravité capillaire, son comportement lorsque les effets capillaires et gravitationnels disparaissent reste inexploré théoriquement et expérimentalement. Une étude expérimentale et théorique détaillée est réalisée pour comprendre la physique de ce phénomène dans une petite cavité rectangulaire où la proximité des murs entraîne des contraintes considérables sur les parois latérales. Un couple de liquides binaires est utilisé avec une faible tension interfaciale pour une interface presque plate. Le contrôle thermique de ce système de fluide est utilisé pour diminuer la force capillaire et d’étudier ainsi les instabilités de Faraday dans les fluides miscibles où la tension interfaciale s’annule. Afin de prendre en compte les effets gravitationnels, l'expérience a été réalisée dans des campagnes de vols paraboliques. Pour l'approche théorique, une analyse de stabilité linéaire est effectuée à l'aide d'équations de Navier-Stokes dans un système de fluide visqueux incompressible et newtonien. Ceci est réalisé grâce à une méthode de Fourier-Floquet résultant en un problème aux valeurs propres. Les comparaisons montrent des différences non négligeables. Les équations sont ensuite résolues en incluant des effets d'amortissement visqueux pour compenser les contraintes des parois latérales. Les fluides binaires ont fourni une option commode pourchanger le coefficient de tension interfaciale en augmentant la température jusqu’à la température critique, ce qui a permis de passer d’un système de fluides non miscibles à celui des fluides miscibles tout en restant au-dessous de la température d’ébullition. Le taux d'amortissement visqueux linéaire est mesuré expérimentalement. La correction des calculs théoriques en prenant en compte le taux d'amortissement visqueux a permis une amélioration nette des résultats et donc de mieux comprendre la prédiction de l'amplitude critique expérimentale pour les modes sous-harmonique et harmonique. / While it is well known that the phenomenon of Faraday instability is a manifestation of vibrational acceleration, its behaviour when both the capillary and gravitational effects vanish, remains unexplored theoretically and experimentally. A detailed experimental and theoretical study is performed to understand the physics of this phenomenon in small rectangular geometry where the proximity of wall results in considerable sidewall stresses. A novel binary liquids system is utilized with low interfacial tension for a near flat interface. Thermal control of fluid system is utilized for achieving reduction in capillary force with study of miscible fluids where interfacial tension reduces to almost zero. In order to discriminate between gravity and capillarity effects, experiments were performed in parabolic flight campaigns. . For the theoretical approach a linear stability analysis is performed through Navier-Stokes equations in a Newtonian incompressible viscous fluid system. This is achieved through a Fourier Floquet method resulting into an eigenvalue problem. Equations are solved by including viscous damping effects for compensating sidewall stresses. Experimentally binary fluids provided a convenient option of changing the coefficient of interfacial tension by temperature control and going through immiscible to miscible system without change of liquid charge. Viscous damping rate is determined experimentally by measuring the linear damping rate. The correction in the theoretical calculations with the viscous damping rate helped in achieving a better understanding of the prediction of the experimental critical amplitude for sub-harmonic and harmonic modes.