Sob o regime de metas de inflação cabe à autoridade monetária balisar seus instrumentos de política de forma a manter a estabilidade do nível geral de preços. Neste aspecto, pelo caráter volátil dos índices de inflação cheia os bancos centrais de todo o mundo utilizam o conceito de núcleo da inflação para tentar capturar com maior acurácia a tendência subjacente da taxa de inflação. Muitas vezes os índices de preços ao consumidor estão altamente sujeitos a volatilidades decorrentes de fatores temporários e muitas vezes localizados. E já que o objetivo da autoridade monetária está em zelar pela estabilidade \"real\" (ou de fato) do nível geral de preços, mudanças temporárias ou localizadas não afetam as taxas de inflação no longo prazo e, consequentemente, não cabe à autoridade monetária responder a tais mudanças, pois isso poderia gerar uma volatilidade desnecessária à política monetária com consequência sobre as flutuações da atividade econômica no período. Dessa forma, Bancos Centrais do mundo inteiro fazem uso de núcleos de inflação. Este trabalho aplica uma nova metodologia de cálculo de núcleo para a inflação brasileira, utilizando o modelo de fatores dinâmicos generalizados. Esta abordagem permite diferenciar fatores localizados (idiossincráticos) dos choques comuns (generalizados) em um grande conjunto de dados. Usamos o IPCA em seu nível mais desagregado e geramos o choque comum entre este conjunto. E a este choque chamamos de núcleo da inflação. Sua eficiência em termos de antecedência à inflação cheia no curto prazo foi testada por meio de uma cointegração, VEC, tais resultados foram comparados com o desempenho do núcleo por Exclusão, mostrando uma maior eficiência do núcleo aqui encontrado. / Under the inflation target system lies to the monetary authority the evaluation of the best tools to keep general price stability. In this context, due to the volatile character of the inflation, central banks around the world use the concept of the inflation core in attempt to capture in a more accurately way the prices trends. Several times, consumer prices indexes are subjected to very volatile prices, due to temporary or localized factors. As the vigilance of the monetary authority relies on the real stability of the general prices level, temporary or localized changes doesn\'t affect the inflation indexes in the long run and, therefore, it\'s not an issue to the central bank to respond to this variations, this could indeed create an unnecessary volatility to the monetary politics with consequences to the economic activity in the period. This way, central banks around the world calculate and use inflation core. This paper applies a new methodology to calculate the inflation core to the Brazilian inflation, using the generalized dynamic factor model. With this approach it\'s possible to differentiate the localized factors from the common (generalized) shocks in a great data set. We use IPCA on its more disaggregated level and create a common shock in the data set, and we name this shock the inflation core. We test the advance of this core to the inflation in the short run using a VEC, and compare with the results of the Exclusion core, we show that your core by using dynamic factor model is more effcient then Exclusion core.

Este trabalho apresenta um modelo de dinâmica de desenvolvimento distribuído de software, cujo objetivo é representar a realidade e os aspectos de ambientes de DDS (Desenvolvimento distribuído de software), a fim de torná-los observáveis e descritíveis qualitativa e quantitativamente. Um modelo preliminar foi elaborado a partir da revisão bibliográfica e de um caso de experimentação desenvolvido por LErario et al (2004). Para a construção e validação deste modelo, a metodologia de estudo de múltiplos casos foi aplicada em diversas organizações que desenvolvem software de maneira distribuída. Ao modelo preliminar foram adicionados estados e transições significantes para a dinâmica do desenvolvimento distribuído de software, originando então o M3DS (Modelo de Dinâmica de Desenvolvimento Distribuído de Software). Duas versões do M3DS são apresentadas. Uma versão construída sobre uma máquina de estados, cujo objetivo é representar apenas a transições entre os estados. Outra versão equivalente, porém mais formal, é apresentada no formato de redes de Petri, na qual é possível visualizar a dependência entre transições e mudanças de estado. Com este modelo, é possível compreender o funcionamento de um projeto distribuído e auxiliar na eficácia da gestão da rede de produção, além de auxiliar as demais entidades e pessoas envolvidas a obterem um posicionamento na rede mais preciso. O M3DS pode, também, auxiliar a detecção proativa de problemas originados a partir do desenvolvimento a distância. Os resultados apresentados neste trabalho respondem a questão de como as organizações desenvolvedoras de software produzem software de maneira distribuída. A riginalidade da pesquisa centra-se na construção de um modelo de dinâmica do desenvolvimento distribuído elaborado com os dados levantados a partir de seis estudos de casos. / This work presents a dynamic model of distributed development of software, whose objective is to represent the reality and the aspects of DDS environments, in order to turn them qualitatively and quantitatively observable. A preliminary model was elaborated from the bibliographical revision and an experimentation case developed by L\'Erario et al (2004). The construction and validation of this model used the methodology multiple cases study in several organizations that develop software in a distributed way. After this, states and transitions were added in the dynamics model of the distributed development of software creating the M3DS. (Dynamics Model of Distributed Development of Software). Two versions of M3DS are presented. A version built on a state machine whose objective is demonstrating the transitions among the states. Another version equivalent, however more formal, it is presented in the format of Petri nets. The second version makes possible to visualize the dependence between transitions and state changes. With this model it is possible to understand the operation of a distributed project, aiding in the effectiveness of the manager of the network production and people can obtain a precise positioning in network. Besides, M3DS can also aid the proactive detection of problems originated from the development at the distance. The results presented in this work answer the question: how the development software organizations produce software in a distributed way. The originality of the research is the construction of a model of dynamics of the distributed development elaborated from data of six cases studies.

In the face of the internationally tightened requirements and regulations for CO2 emissions from the transportation sector, waste heat recovery using a thermoelectric generator (TEG) has become the most significant research interest. A vehicular TEG, converting otherwise wasted thermal energy from engines to electricity directly for use in the vehicle systems, is a promising approach for vehicle original equipment manufacturers (OEMs) to reduce fuel consumption and lower CO2 emissions. This thesis aims to explore the main challenges to be faced in the commercialization of TEGs. Based on a review of the literature, four research gaps have been identified, which are respectively: * Translating the material improvements into TEG Performance, * Transient behaviors of vehicular TEGs under driving cycles, * Fuel saving percentage and cost-benefit estimation of TEG, * Bidirectional characteristic of TEM and bifunctional vehicular TEG. To directly address these research gaps, a quasi-static TEM model, a dynamic TEG model, a semi-empirical vehicular TEG model, and a dual-model TEM model have been respectively developed and validated through experiments on both TEM test rigs and TEG engine test benches. These developed models are used as tools to investigate the performance of TEG, parameters sensitivity, and integration effects. Model-based TEG control, TEG cost benefit ratio and feasibility of a bifunctional TEG are also explored based on the developed models. The simulation results show that TEG power generation is highly sensitive to the heat transfer coefficient of hot side heat exchanger and thermal contact resistance. The TEG installation position is identified as the most important integration effect. It has been found by the simulation result that the fuel saving with TEG installed upstream of the three-way catalyst (TWC) is 50% higher than the fuel saving with TEG installed downstream of the TWC. The fuel saving percentage for a skutterudite vehicular TEG, which can generate around 400-600W in constant speed 120km/h, is 0.5-3.6% depending on the integration position in the exhaust line. A 3-minute faster warm-up effect of engine oil can be obtained when the bifunctional TEG works in engine warm-up mode with electrical current applied.

Research in soft robot hardware has led to the development of platforms that allow for safer performance when working in uncertain or dynamic environments. The potential of these platforms is limited by the lack of proper dynamic models to describe or controllers to operate them. A common difficulty associated with these soft robots is a representation for torque, the common electromechanical relation seen in motors does not apply. In this thesis, several different torque models are presented and used to construct linear state-space models. The control limitations on soft robots are induced by natural compliance inherent to the hardware. This inherent compliance results in soft robots that are commonly underdamped and present significant oscillations when accelerated quickly. These oscillations can be mitigated through model-based controllers which can anticipate these oscillations. In this thesis, multiple model predictive controllers are implemented with the torque models produced and results are presented for an inflatable single-DoF pneumatically actuated soft robot. Larger, multi-DoF, soft robots present additional issues with control, where flexibility in one joint impacts control in others. In this thesis a preliminary method and results for controlling multiple joints on an inflatable multi-DoF pneumatically actuated soft robot are presented. While model predictive controllers are capable, their control commands are defined by solving an optimization constrained by model dynamics. This optimization relies on minimizing the cost of a user-defined objective function. This objective function contains a series of weights, which allow the user to tune the importance of each component in the objective function. As there are no calculations that can be performed to tune model predictive controllers to achieve superior control performance, they often need to be tuned tediously by a skilled operator. In this thesis, a method for automated discrete performance identification and model predictive controller weight tuning is presented. This thesis constructs multiple state-space models for single- and multi-DoF underdamped, antagonistic, pneumatically actuated soft robots and shows that these models can be used with model predictive control, tuned for performance, to achieve accurate joint position control.

The research aims at modeling and analyzing the interactions among functional process variables (FPVs) for process control in semiconductor manufacturing. Interaction is a universal phenomenon and different interaction patterns among system components might characterize the system conditions. To monitor and control the system, process variables are normally collected for observation which could vary with time and present in a functional form. These FPVs interact with each other and contain rich information regarding the process conditions. As an example in one of the semiconductor manufacturing processes, changes of interactions among FPVs like temperature and coefficient of friction (COF) might characterize different process conditions. This dissertation systematically developed a methodology to study interaction among FPVs through statistical and physical modeling. Three main topics are discussed in this dissertation: (1) Interaction patterns of FPVs under varying process conditions are studied both through experiments and statistical approaches. A method based on functional canonical correlation analysis (FCCA) is employed to extract the interaction patterns between FPVs and experiments of wafer polishing processes are conducted to verify the patterns of FPVs under varying process conditions. (2) Interaction among FPVs is further studied based on physics for process condition diagnosis. A mathematical model based on nonlinear dynamics is developed to study the strength of interaction and their directionalities, and advanced statistical control charts followed by this nonlinear dynamics model are established for process monitoring. (3) Complex interaction structures among multiple FPVs are analyzed based on nonlinear dynamics for a better understanding of process mechanism. An approach with extended nonlinear dynamics model is proposed to characterize process conditions, and combined engineering knowledge, complex interaction structure patterns are concluded accordingly for interpretation of process mechanism. The main contribution of this dissertation is to propose a novel methodology based on nonlinear dynamics, which could investigate interactions between components of systems and provide physical understanding of process mechanism for process monitoring and diagnosis. Through studies on interaction among FPVs in semiconductor manufacturing, this research provides guidance for improvement of manufacturing processes. Not limited to manufacturing, the developed methodology can be applied to other areas such as healthcare delivery.

<p>This thesis presents improvements and extensions of a previously presented threat assessment algorithm. The algorithm uses Monte Carlo simulation to find threats in a road scene. It is shown that, by using a wider sample distribution and only apply the most likely samples from the Monte Carlo simulation, for the threat assessment, improved results are obtained. By using this method more realistic paths will be chosen by the simulated vehicles and more complex traffic situations will be adequately handled.</p><p>An improvement of the dynamic model is also suggested, which improves the realism of the Monte Carlo simulations. Using the new dynamic model less false positive and more valid threats are detected.</p><p>A systematic method to choose parameters in a stochastic space, using optimisation, is suggested. More realistic trajectories can be chosen, by applying this method on the parameters that represents the human behaviour, in the threat assessment algorithm.</p><p>A new definition of obstacles in a road scene is suggested, dividing them into two groups, Hard and Soft obstacles. A change to the resampling step, in the Monte Carlo simulation, using the soft and hard obstacles is also suggested.</p>

<p>Dynamic model driven architecture (DMDA) is a architecture made to aid in the</p><p>development of parallel computing code. This thesis is applied to an implementation of</p><p>DMDA known as DMDA3 that should convert graphs of computations into efficient</p><p>computation code, and it deals with the translation of Platform Specific Models (PSM)</p><p>into running systems. Currently DMDA3 can generate schedules of operations but not</p><p>finished code.</p><p>This thesis describes a DMDA3 module that turns a schedule of operations into a</p><p>runable program. Code was obtained from the DMDA3 schedules by reflection and a</p><p>framework was build that allowed generation of low level language code from</p><p>schedules. The module is written in Java and can currently generate C and Fortran code</p><p>for computational tasks. Based on runtime tests for matrix multiplication algorithms the</p><p>generated code is almost as fast as handwritten code.</p><p> </p>

This dissertation describes the development and results of a physiological rigid body forward solution mathematical model that can be used to predict normal knee and total knee arthroplasty (TKA) kinematics and kinetics. The simulated activities include active extension and weight-bearing deep knee bend. The model includes both the patellofemoral and tibiofemoral joints. Geometry of the normal or implanted knee is represented by multivariate polynomials and modeled by constraining the velocity of lateral and medial tibiofemoral and patellofemoral contact points in a direction normal to the geometry surface. Center of mass, ligament and muscle attachment points and normal knee geometry were found using computer aided design (CAD) models built from computer tomography (CT) scans of a single subject. Quadriceps forces were the input for this model and were adjusted using a unique controller to control the rate of flexion, embedded with a controller which stabilizes the patellofemoral joint. The model was developed first using normal knee parameters. Once the normal knee model was validated, different total knee arthroplasty (TKA) designs were virtually implanted. The model was validated using in vivo data obtained through fluoroscopic analysis. In vivo data of the extension and deep knee bend activities from five non-implanted knees were used to validate the normal model kinematics. In vivo kinematic and kinetic data from a telemetric TKA with a tibia component instrumented with strain gauges was used to validate the kinematic and kinetic results of the model implanted with the TKA geometry. The tibiofemoral contact movement matched the trend seen in the in vivo data from the one patient available with this implant. The maximum axial tibiofemoral force calculated with the model was in 3.1% error with the maximum force seen in the in vivo data, and the trend of the contact forces matched well. Several other TKA designs were virtually implanted and analyzed to determine kinematics and bearing surface kinetics. The comparison between the model results and those previously assessed under in vivo conditions validates the effectiveness of the model and proves that it can be used to predict the in vivo kinematic and kinetic behavior of a TKA.

Efficient and reliable public transport systems are fundamental in promoting green growth developments in metropolitan areas. A large range of Advanced Public Transport Systems (APTS) facilitates the design of real-time operations and demand management. The analysis of transit performance requires a dynamic tool that will enable to emulate the dynamic loading of travelers and their interaction with the transit system. BusMezzo, a dynamic transit operations and assignment model was developed to enable the analysis and evaluation of transit performance and level of service under various system conditions and APTS. The model represents the interactions between traffic dynamics, transit operations and traveler decisions. The model was implemented within a mesoscopic traffic simulation model. The different sources of transit operations uncertainty including traffic conditions, vehicle capacities, dwell times, vehicle schedules and service disruptions are modeled explicitly. The dynamic path choice model in BusMezzo considers each traveler as an adaptive decision maker. Travelers’ progress in the transit system consists of successive decisions that are defined by the need to choose the next path element. The evaluations are based on the respective path alternatives and their anticipated downstream attributes. Travel decisions are modeled within the framework of discrete random utility models. A non-compensatory choice-set generation model and the path utility function were estimated based on a web-based survey. BusMezzo enables the analysis and evaluation of proactive control strategies and the impacts of real-time information provision. Several experiments were conducted to analyze transit performance from travelers, operator and drivers perspectives under various holding strategies. This analysis has facilitated the design of a field trial of the most promising strategy. Furthermore, a case study on real-time traveler information systems regarding the next vehicle arrival time investigated the impacts of various levels of coverage and comprehensiveness. As passengers are more informed, passenger loads are subject to more fluctuation due to the traveler adaptations. / QC 20111201

In this thesis, a grid-connected wind-energy converter system including a matrix converter is proposed. The matrix converter, as a power electronic converter, is used to interface the induction generator with the grid and control the wind turbine shaft speed. At a given wind velocity, the mechanical power available from a wind turbine is a function of its shaft speed. Through the matrix converter, the terminal voltage and frequency of the induction generator is controlled, based on a constant V/f strategy, to adjust the turbine shaft speed and accordingly, control the active power injected into the grid to track maximum power for all wind velocities. The power factor at the interface with the grid is also controlled by the matrix converter to either ensure purely active power injection into the grid for optimal utilization of the installed wind turbine capacity or assist in regulation of voltage at the point of connection. Furthermore, the reactive power requirements of the induction generator are satisfied by the matrix converter to avoid use of self-excitation capacitors. The thesis addresses two dynamic models: a comprehensive dynamic model for a matrix converter and an overall dynamical model for the proposed wind turbine system. The developed matrix converter dynamic model is valid for both steady-state and transient analyses, and includes all required functions, i.e., control of the output voltage, output frequency, and input displacement power factor. The model is in the qdo reference frame for the matrix converter input and output voltage and current fundamental components. The validity of this model is confirmed by comparing the results obtained from the developed model and a simplified fundamental-frequency equivalent circuit-based model. In developing the overall dynamic model of the proposed wind turbine system, individual models of the mechanical aerodynamic conversion, drive train, matrix converter, and squirrel-cage induction generator are developed and combined to enable steady-state and transient simulations of the overall system. In addition, the constraint constant V/f strategy is included in the final dynamic model. The model is intended to be useful for controller design purposes. The dynamic behavior of the model is investigated by simulating the response of the overall model to step changes in selected input variables. Moreover, a linearized model of the system is developed at a typical operating point, and stability, controllability, and observability of the system are investigated. Two control design methods are adopted for the design of the closed-loop controller: a state-feedback controller and an output feedback controller. The state-feedback controller is designed based on the Linear Quadratic method. An observer block is used to estimate the states in the state-feedback controller. Two other controllers based on transfer-function techniques and output feedback are developed for the wind turbine system. Finally, a maximum power point tracking method, referred to as mechanical speed-sensorless power signal feedback, is developed for the wind turbine system under study to control the matrix converter control variables in order to capture the maximum wind energy without measuring the wind velocity or the turbine shaft speed.