Techn. Universiẗat, Diss., 2005--Darmstadt.

[pt] Com o aumento da complexidade das aplicações de banco de dados a tarefa de sintonizar os sistemas de banco de dados para melhorar os tempos de resposta das consultas submetidas tem se tornado mais difícil. O uso de visões materializadas é uma forma de melhorar o desempenho do acesso aos dados. Trata-se de um objeto de um banco de dados relacional que armazena um conjunto de dados pré-calculados resultante de uma consulta. Esta dissertação propõe a criação automática de visões materializadas. Para tal utiliza uma arquitetura de auto-sintonia não-intrusiva, isto é, sem modificar o código do SGBD. São propostas métricas para estimar os custos envolvendo visões materializadas permitindo que se determine seu benefício efetivo. São apresentadas heurísticas para a tomada de decisão automática quanto à criação de visões materializadas em função de uma determinada carga de trabalho. São apresentados testes e simulações com o benchmark TPC-H na presença do SGBD MS SQL Server 2008. / [en] As database applications become more complex, tuning database systems in order to improve query response times also become harder. One could consider materialized views, a relational database object that stores data resulting from specific queries, to obtain better performances. This dissertation proposes the automatic creation of materialized views. A non-intrusive architecture is used in order to keep DBMS source codes unchanged. There is a need to estimate the creation cost and the benefits obtained from the presence of the materialized views. Heuristics are proposed to help with the automatic decision upon creation of these materialized views for a given workload. Simulation tests for TPC-H benchmark and MS SQL Server DBMS are presented.

Industrial robots rapidly gained popularity as they can perform tasks quickly, repeatedly and accurately in static environments. However, in modern manufacturing, robots should also be able to safely interact with arbitrary objects and dynamically adapt their behavior to various situations. The large masses and rigid constructions of industrial robots prevent them from easily being re-tasked. In this context, this work proposes an immediate solution to make rigid manipulators compliant and able to efficiently handle object interactions, with only an add-on module (a custom designed instrumented compliant wrist) and an original control framework which can easily be ported to different manipulators. The proposed system utilizes both offline and online trajectory planning to achieve fully automated object interaction and surface following with or without contact where no prior knowledge of the objects is available. To minimize the complexity of the task, the problem is formulated into four interaction motion modes: free, proximity, contact and a blend of those. The free motion mode guides the robot towards the object of interest using information provided by a RGB-D sensor. The RGB-D sensor is used to collect raw 3D information on the environment and construct an approximate 3D model of an object of interest in the scene. In order to completely explore the object, a novel coverage path planning technique is proposed to generate a primary (offline) trajectory. However, RGB-D sensors provide only limited accuracy on the depth measurements and create blind spot when it reaches close to surfaces. Therefore, the offline trajectory is then further refined by applying the proximity motion mode and contact motion mode or a blend of them (blend motion mode) that allow the robot to dynamically interact with arbitrary objects and adapt to the surfaces it approaches or touches using live proximity and contact feedback from the compliant wrist. To achieve seamless and efficient integration of the sensory information and smoothly switch between different interaction modes, an original hybrid switching scheme is proposed that applies a supervisory (decision making) module and a mixture of hard and blend switches to support data fusion from multiple sensing sources by combining pairs of the main motion modes. Experimental results using a CRS-F3 manipulator demonstrate the feasibility and performance of the proposed method.

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This dissertation investigates the nonlinear wave propagation phenomena in nonlinear metamaterials with nonlinear chains and nonlinear resonators using analytical and spectro-spatial analyses. In the first part of the thesis, the nonlinear metamaterials are modeled as a chain of masses with multiple local resonators attached to each cell. The nonlinearity stems from the chain's stiffness in one case and the local resonator's stiffness in another. Analytical approximates solutions are obtained for each case using perturbation techniques. These results are validated through numerical simulations and the results show good agreement. To further demonstrate the nonlinear wave propagation characteristics, spectro-spatial analyses are conducted on the numerical integration data sets. The wave profiles, short-term Fourier transform spectrograms, and contour plots of 2D Fourier transform show the presence of solitary waves for both sources of nonlinearity. In addition, spectro-spatial features demonstrate the presence of significant frequency shifts at different wavelength limits. indent The second part of the thesis studies a nonlinear electromechanical metamaterial and examines how the electromechanical coupling in the local resonator affects the wave propagation. Numerical examples indicate that the system can be used for simultaneous energy harvesting and vibration attenuation without any degradation in the size of bandgaps. Spectro-spatial analyses conducted on the electromechanical metamaterial also reveal the presence of solitons and frequency shifts. The presence of solitary wave in the electromechanical metamaterial suggests a significant improvement in energy harvesting and sensing techniques. The obtained significant frequency shift is employed to design an electromechanical diode, allowing voltage to be sensed and harvested only in one direction. Design guidelines and the role of different key parameters are presented to help designers to select the type of nonlinearity and the system parameters to improve the performance of acoustic diodes. indent The last part of this thesis studies the passive self-tuning of a metastructure via a beam-sliding mass concept. The governing equations of motions of the holding structure, resonator, and sliding mass are presented and discretized into a system of ODEs using Galerkin's projection. Given that the spatial parameters of the system continuously change over time (i.e., mode shapes and frequencies), instantaneous exact mode shapes and frequencies are determined for all possible slider positions. The numerical integration is conducted by continuously updating the spatial state of the system. The obtained exact mode shapes demonstrate that the resonance frequency of the resonator stretches over a wide frequency band. This observation indicates that the resonator can attenuates vibrations at a wide frequency range. Experiments are also conducted to demonstrate the passive self-tunability of the metastructure and the findings colloborate the analytical results. / Doctor of Philosophy / Metamaterials are artificially engineered structures that can offer incredible dynamical properties, which cannot be found in conventional homogeneous structures. Consequently, the global metamaterials market is expected to display a 23.6$%$ compound annual growth rate through 2027. Some of these exciting properties include, but not limited to, negative stiffness, negative mass, negative Poisson's ratio. The unique dynamic properties show the importance of metamaterials in many engineering applications, such as vibration reduction, noise control, and waveguiding and localization. However, beyond the linear characteristics of metamaterials, nonlinear metamaterials can exhibit more interesting nonlinear wave propagation phenomena, such as solitons, cloaking, tunable bandgaps, and wave non-reciprocity. indent This research work investigates wave propagation characteristics in nonlinear locally resonant metamaterials using analytical, numerical, and signal processing techniques. The nonlinearity stems from the chain in one case and from the local resonator in another. Numerical examples show the presence of solitary waves in both types of nonlinearity and significant frequency shift in certain frequency/wavenumber regions. The obtained significant frequency shift can be utilized to design mechanical diodes, where its operation range can be increased by introducing nonlinearity in the resonator. indent For simultaneous energy harvesting and vibration attenuation, integrating the local resonator with piezoelectric energy harvesters is also investigated in this research work with the presence of both types of nonlinearities. For weak electromechanical coupling, the results demonstrate that the band structure of the system is not affected by the electromechanical coupling. Therefore, the system can also be used for energy harvesting without any degradation in the vibration attenuation performance. This observation is also validated experimentally for the linear limit. Spectro-spatial analyses also reveal the presence of solitary output voltage waves, which can enhance the energy harvesting and sensing. The obtained significant frequency shift can be utilized to design an electromechanical diode where the wave can propagate and be harvested only in one direction. Numerical examples show that the performance of the electromechanical diode can be significantly improved by including nonlinearities in the local resonator. indent Another goal of this research work is the introduction of passive self-tuning mechanism to design self-tuning metastructure. The design of such a metastructure is motivated by the need for broadband devices that can adapt to changing environment. The passive self-tuning concept is achieved by a sliding mass coupled with a resonator. Analytical and experimental results show the ability of this system to tune itself to the excitation frequency, and hence, can control vibrations over a significantly wider frequency band as compared to conventional resonators.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This works proposes parameters estimation algorithm to auto-tune the control laws of a speed sensorless servo. The identification process of the electrical and mechanical parameters is based on recursive least squares method (RLS) and utilizes just measured stator currents. The electrical parameters are obtained by the transfer function of the motor with locked rotor. Hence, this eliminates the need to realize classical tests for the electrical parameters obtention and impose robustness to the controller for parameters variations caused by aging of materials. Thus, the electrical parameters are used to project the current controllers and the rotor speed is estimated by a model reference adaptive systems (MRAS). The structure of MRAS is composed by two systems (reference model and adaptive system) based on instantaneous reactive power and using an adaptation mechanism. On the other hand, to obtain a robust control when the system is subject to disturbances or load s variations, mechanical parameters are identified using estimated rotor speed and mechanical model of the induction motor (IM). Finally, for the speed control is used a proportional plus integral controller (PI) self-tuned through the estimated inertia. / Este trabalho propõe um algoritmo de identificação paramétrica para auto-ajuste da lei de controle de um servo de velocidade sem sensor mecânico. O processo de identificação dos parâmetros elétricos e mecânicos do servo é baseado em algoritmos do tipo mínimos quadrados recursivo (RLS) e utiliza apenas as medidas das correntes estatóricas. Os parâmetros elétricos são identificados através da função de transferência do motor com rotor bloqueado. Isso elimina a necessidade de realizar ensaios clássicos para obtenção dos parâmetros elétricos e impõe robustez ao controlador frente a variações paramétricas que ocorrem devido aos desgastes e envelhecimento dos materiais que constituem o motor. Uma vez identificados, os parâmetros elétricos são utilizados no projeto dos controladores de corrente e a velocidade rotórica é estimada utilizando um sistema adaptativo por modelo de referência (MRAS). A estrutura do MRAS é composta por dois sistemas (modelo de referência e sistema adaptativo) baseados na potência reativa instantânea e utiliza um mecanismo de adaptação. Por outro lado, para impor robustez ao controlador frente a variações de carga, os parâmetros mecânicos são identificados a partir da velocidade rotórica estimada e do modelo mecânico do motor de indução (MI). Finalmente, para o controle de velocidade é usado um controlador proporcional e integral (PI) com seus ganhos sintonizados a partir da inércia estimada.

As device feature sizes shrink to nano-scale, continuous technology scaling has led to a large increase in parameter variability during semiconductor manufacturing process. According to the source of uncertainty, parameter variations can be classified into three categories: process variations, environmental variations, and temporal variations. All these variation sources exert significant influences on circuit performance, and make it more challenging to characterize parameter variability and achieve robust, low-power designs. The scope of this dissertation is conquering parameter variability and successfully designing efficient yet robust integrated circuit (IC) systems. Previous experiences have indicated that we need to tackle this issue at every design stage of IC chips. In this dissertation, we propose several robust techniques for accurate variability characterization and efficient performance prediction under parameter variations. At pre-silicon verification stage, a robust yield prediction scheme under limited descriptions of parameter uncertainties, a robust circuit performance prediction methodology based on importance of uncertainties, and a robust gate sizing framework by ElasticR estimation model, have been developed. These techniques provide possible solutions to achieve both prediction accuracy and computation efficiency in early design stage. At on-line validation stage, a dynamic workload balancing framework and an on-line self-tuning design methodology have been proposed for application-specific multi-core systems under variability-induced aging effects. These on-line validation techniques are beneficial to alleviate device performance degradation due to parameter variations and extend device lifetime.

[pt] Uma dentre as muitas tarefas desempenhadas por DBAs consiste em tentar garantir que os tempos de respostas dos comandos submetidos por usuários a um grande SGBDR não excedam valores previamente acordados. Esta dissertação segue uma linha de estudos denominada auto-sintonia de índices, que preconiza a realização de ajustes automáticos na execução de consultas SQL, visando reduzirlhes tempos de resposta, a partir de alterações no conjunto de índices: criação, eliminação e recriação. Este trabalho teve como ponto de partida a dissertação de Marcos Salles [32], que seguiu a mesma linha, propondo um mecanismo automático de criação de índices. Esta dissertação estende [32], primeiro submetendo sua implementação a uma carga de trabalho alternativa e depois realizando eliminações e reconstruções de índices automáticas, levando em consideração níveis de preenchimento de páginas alternativos. Também foram realizados testes utilizando ferramentas comerciais, Oracle 10g e SQL Server 2005, para avaliar quão eficaz comportou-se a implementação proposta em [32]. Vale ressaltar que os testes realizados limitaram-se à criação de índices, já que as ferramentas não oferecem facilidades de reconstrução automática. Diferentemente dos trabalhos publicados nessa linha de estudos e das ferramentas comerciais disponíveis, foi criado um protótipo que não se limita a sugerir novos índices; também são eliminados os que deixaram de ser interessantes, porém, antes ocorre uma avaliação para verificar se a reconstrução não seria mais adequada. Criou-se, inclusive, uma heurística rudimentar que avalia um índice a ser destruído e recomenda sua reconstrução, caso atenda a determinados requisitos. / [en] One of the most important tasks of Database Administrators certainly is to guarantee optimal response times to statements submitted by users of big RDBMS. Our dissertation deals with Index Self-tuning, which means creating, dropping or recreating indexes automatically, in order to decrease SQL queries durations. We start from Marcos Salles´ dissertation [32], which proposed an automatic way of creating indexes. We extend [32] in many ways: first using a different workload, TPC-H like. Second, following created indexes inspecting its usage. Finally, we have gotten to drop and, mostly, recreate indexes using different fillfactor in leaf pages. Also, we have elaborated many tests using commercial tools, Microsoft SQL Server 2005 and Oracle 10g in order to ratify [32] ideas. Unfortunatelly, we could not test automatic dropping and recreating in these tools, as long as they do not offer this kind of functionalities. Unlike related work and commercial tools, we have created a code prototype that not only suggests new indexes creations, but also drops and recreates indexes using an own heuristics. To validate our ideas we have used a TPC-C like workload, but we had to make some changes to increase updates and force reindexing.

The simplest form of induction motors, known as AC squirrel cage motor, is the universal workhorse of industrial and commercial premises. For many years it was restricted to constant speed applications while DC motors were preferred for high-performance variable speed and servo drives. With modern advances in semiconductor and digital signal processing technologies, it is now possible to operate induction motors in high-performance drives at a reasonable cost with Field Oriented Control methods. The latter have made induction motor drives equivalent to DC drives in terms of independent control of flux and torque; and superior to them in terms of dynamic performance. In developing Field Oriented Control for induction motors engineers are faced with two major challenges: (1) the estimation of rotor data to compute for the slip gain, and (2) the compensation of changes in drive operating conditions and parameters in order to maintain the drive performance high at all time. This thesis addresses these issues by introducing two independent control systems. The first system is designed to estimate online the value of the slip gain in the entire torque-speed plane in order to maintain decoupled control of torque and flux despite the so-called detuning effects. It is based on evaluating the operating condition of the drive in terms frequency and load torque, and selecting the appropriate estimation method accordingly. A fuzzy controller is used to generate the distribution factor for the methods. The second system is a fuzzy self-tuning speed controller, with reduced sensitivity to motor parameters and operating condition changes. It has the ability to adjust its gains in real time according to the current trend of the drive system. It is designed to maintain tight control of speed and torque for high-performance applications. The performances of the two controllers are validated through a series of simulation and experimental tests using a 2HP 3-phase induction motor with an ADMC21992 160-MHz DSP microprocessor. / Power Engineering and Power Electronics

<p>Modern industrial, government, and academic organizations are collecting massive amounts of data ("Big Data") at an unprecedented scale and pace. The ability to perform timely and cost-effective analytical processing of such large datasets in order to extract deep insights is now a key ingredient for success. These insights can drive automated processes for advertisement placement, improve customer relationship management, and lead to major scientific breakthroughs.</p><p>Existing database systems are adapting to the new status quo while large-scale dataflow systems (like Dryad and MapReduce) are becoming popular for executing analytical workloads on Big Data. Ensuring good and robust performance automatically on such systems poses several challenges. First, workloads often analyze a hybrid mix of structured and unstructured datasets stored in nontraditional data layouts. The structure and properties of the data may not be known upfront, and will evolve over time. Complex analysis techniques and rapid development needs necessitate the use of both declarative and procedural programming languages for workload specification. Finally, the space of workload tuning choices is very large and high-dimensional, spanning configuration parameter settings, cluster resource provisioning (spurred by recent innovations in cloud computing), and data layouts.</p><p>We have developed a novel dynamic optimization approach that can form the basis for tuning workload performance automatically across different tuning scenarios and systems. Our solution is based on (i) collecting monitoring information in order to learn the run-time behavior of workloads, (ii) deploying appropriate models to predict the impact of hypothetical tuning choices on workload behavior, and (iii) using efficient search strategies to find tuning choices that give good workload performance. The dynamic nature enables our solution to overcome the new challenges posed by Big Data, and also makes our solution applicable to both MapReduce and Database systems. We have developed the first cost-based optimization framework for MapReduce systems for determining the cluster resources and configuration parameter settings to meet desired requirements on execution time and cost for a given analytic workload. We have also developed a novel tuning-based optimizer in Database systems to collect targeted run-time information, perform optimization, and repeat as needed to perform fine-grained tuning of SQL queries.</p> / Dissertation