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Disertaciones |
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1
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PEDRO PAULO MATOS BARRETO
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ANALYSIS OF DOORS AND LOGICAL CIRCUITS BASED ON PHOTONIC CRYSTALS
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Líder : VITALY FELIX RODRIGUEZ ESQUERRE
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MIEMBROS DE LA BANCA :
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ANA JÚLIA FERNANDES DE OLIVEIRA BARROS
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MAICON DEIVID PEREIRA
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VITALY FELIX RODRIGUEZ ESQUERRE
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Data: 28-ene-2020
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Resumen Espectáculo
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The present work deals with the analysis of error tolerance, which occurs in the manufacturing process of several logic gates, such as OR, XOR, XNOR, AND and NAND, which can be used to make logic circuits. The logic circuits mentioned were also analyzed, similarly to logic gates, with an analysis applied to possible failures, which occur in the logic gates manufacturing process, targeting the possible changes between the project and the final device developed, in aspects such as changes in the dimensions of the radius and the spacing between the rods. The devices analyzed in this dissertation are completely optical and, designed with the use of photonic crystals (PhC, Photonic Crystals), the method used in the simulations was the Finite Element Method (FEM, Finite Element Method) applied in the simulations, through the software WITH SUN. This work was carried out through several simulations, and the analysis was made by measuring the intensity of the electric field and then a general analysis of the results was performed. The MMI (Multi Mode Interference, or MIX or Mixer) is a device capable of adding or canceling the different modes present in the electromagnetic signal. Analyzes were made on the position and dimensions of the radius of the rods and even their proportions of the x and y axes were varied in isolation, so that the rods assume the shape of ellipses. Subsequently, another analysis was performed on the same device, in which the dimensions of the rods were reduced by up to 50%, in the wavelength intervals of 1,261 µm≤ λ ≤1,361 µm and 1.50 µm≤ λ ≤1.62 µm .The structure presented that has one or two pairs of resonant rings, optimization of its dimensions, which corresponded to a reduction in the number of rods. The structure that has a combination of MMIs was subjected to an error tolerance analysis present in the variables of its manufacturing process, such as the radius of the rods, in a proportion of ± 10% and, in the refractive index of the rods and the substrate , in an isolated and simultaneous way, with this, it was found that it is possible to vary the index of refraction of the rods, up to a certain range of this value, and it was found that changes in the substrate index, have a greater capacity to change the level logic previously presented.
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2
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MIRIELE CARVALHO PAIM
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Propagation Properties and Applications of Hypercrystals
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Líder : VITALY FELIX RODRIGUEZ ESQUERRE
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MIEMBROS DE LA BANCA :
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IGOR LEONARDO GOMES DE SOUZA
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JUAREZ CAETANO DA SILVA
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VITALY FELIX RODRIGUEZ ESQUERRE
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Data: 31-mar-2020
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Resumen Espectáculo
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The growing interest in new metamaterials and hypercrystals is justified by the need for materials that meet the constant evolution of market demand, brings new questions and answers that reflect on the best ways to use the characteristics of good absorption and / or reflection. This work evaluates the behavior of hypercrystals, analyzing their transmission, reflection and absorption, which are important for applications in technologies such as solar cells. As simulated structures in the region visible to the infrared from 400 to 1600 nm, they are composed of layers of metals and dielectrics with variation in their parameters, geometries and configurations that allow to obtain better results. The results were moderate in the Transversal Electric (TE) and Magnetic Transversal (TM) modes, where the applied measures show satisfactory results of absorption and reflection along the entire wavelength, demonstrating new possibilities of hypocrisy structures and the possibility of using or structure in manufacturing and testing photonic devices.d Applications of Hypercrystals
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3
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EDNALDO LUÍS DE JESUS SOUZA
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Transient study of a feedback measurement system based on thermoresistive sensors
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Líder : TITO LUIS MAIA SANTOS
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MIEMBROS DE LA BANCA :
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TITO LUIS MAIA SANTOS
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ACBAL RUCAS ANDRADE ACHY
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JOSE MARIO ARAUJO
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Data: 28-may-2020
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Resumen Espectáculo
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This work proposes two techniques aimed at improving feedback systems based on a sensor thermoresistive kept at constant temperature. In order to obtain better results regarding the effects of the temperature transients of the device in the measurement, control strategies by internal model with two degrees of freedom and control based on disturbance observer are presented. A temperature derivative compensation method called backward approximation is also proposed in order to minimize the effects of transients in the response of the measurement system based on NTC sensors and provide a faster process of estimating physical quantities. A study on the errors inherent to the discussed approaches is also presented. Simulations of measurements of ambient temperature, fluid velocity and thermal radiation absorbed by the sensor are carried out in the face of changes in temperature reference and disturbances at the sensor input, as well as bench tests of ambient temperature measurements.
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4
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DIEGO OLIVEIRA CARDOSO
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Three-phase inverter control connected to the grid with LCL filters.
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Líder : FABIANO FRAGOSO COSTA
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MIEMBROS DE LA BANCA :
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FABIANO FRAGOSO COSTA
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ANDRE PIRES NOBREGA TAHIM
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LUCIANA MARTINEZ
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DARLAN ALEXANDRIA FERNANDES
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Data: 29-may-2020
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Resumen Espectáculo
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This paper discusses control strategies for the connection of the three phase inverter to the grid through LCL filters. Three different methods are presented: conventional dq, multivariate and optimized PI. The first two proposals consider simplified modeling for the system plant and therefore neglect the resonance phenomenon caused by the use of high order filters. Closed-loop stability is guaranteed for this simplification through the use of extra cushioning strategies. The optimized method uses non-parametric models of the plant and the control is performed using fifth order controllers. The constants of these controllers are determined with the solution of a restricted optimization, which guarantees the decoupling and stability of the system. It was possible to verify that the conventional strategy guarantees the stability of the closed-loop plant, but the power decoupling is not achieved. This objective is achieved with the controls, multivariate and optimized PI, presenting stability and decoupling. Among these two techniques, only the optimized one was able to decouple the powers, even with variations of the plant parameters.
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5
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REGINEY AZEVEDO BARBOSA
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Voltage Control for dc Microgrids Using an Adaptative Fuzzy Controller
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Líder : ANDRE PIRES NOBREGA TAHIM
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MIEMBROS DE LA BANCA :
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ANDRE PIRES NOBREGA TAHIM
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FABIANO FRAGOSO COSTA
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DARLAN ALEXANDRIA FERNANDES
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DURVAL DE ALMEIDA SOUZA
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Data: 01-jun-2020
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Resumen Espectáculo
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The growth of renewable energy sources led to the rise of microgrids and, therefore, it is necessary to study and develop techniques that make them more efficient and stable. This work makes the study of a DC microgrid, composed of a photovoltaic generating unit, a DC-DC converter of the typeBoost, a DC bus connectedto the load and the bidirectional DC-AC converter responsible for making the interface with the concessionaire network. The DC-DC converter is responsible for tracking the maximum power of the photovoltaic panels while the bidirectional DC-AC converter has two functions: to keep the DC bus voltage constant and to inject/extract power from the grid. The control of the bidirectional converter consists of two loops: an internal one that controls the AC current and an external one responsible for controlling the DC bus voltage. The internal mesh uses a Resonant Proportional controller suitable for tracking sinusoidal current reference. The Intelligent Controller of the bus voltage is composed of a Proportional Integral compensator and a Fuzzy controller and are used together to reduce the transients caused by disturbances. The control signal of the PI compensatorin steady state is stored and processed by the Fuzzy controller, and from then on the microgrid adapts around this point of operation. The Fuzzy controller is able to control the microgrid more quickly and efficiently, mitigating the overrun and transitory time. Finally, the results of the microgrid control are presented from two simulation scenarios, highlighting the transient in each instant that the system disturbances occur,demonstrating the effectiveness of the proposed controller compared to the conventional PI compensator, most used in the literature.
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6
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ARY MONTENEGRO BATISTA
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Finite Horizon Robust Model Predictive Control for time-varying discrete systems with guaranteed stability
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Líder : HUMBERTO XAVIER DE ARAUJO
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MIEMBROS DE LA BANCA :
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HUMBERTO XAVIER DE ARAUJO
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TITO LUIS MAIA SANTOS
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PEDRO LUIS DIAS PERES
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VALTER JUNIOR DE SOUZA LEITE
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Data: 08-jun-2020
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Resumen Espectáculo
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This work proposes a new approach for the Finite Horizon Robust Model-Based Predictive Control (FH-RMPC) problem of linear discrete systems with time-varying polytopic uncertainties. The basic idea of this approach is to find, in each sampling time, the optimal state feedback control law based on Riccati difference equations (RDE) that minimizes an objective function with finite horizon and takes in account input and output constraints. The closed loop stability, known as one of the challenging themes of FH-RMPC strategy with constraints, is based on monotonic property of the RDE associated with finite horizon Linear Quadratic (LQ) control problem. In this proposed method it is not necessary that the usual terminal weighting matrix be fixed to achieve asymptotic stability. The stability analysis is done considering a finite set of Lyapunov functions and also considering parameter dependent Lyapunov functions. Finally, the efficiency of the proposed approach is illustrated by numerical examples and comparing to the IH-RMPC strategy through error-based performance indexes.
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7
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IAGO JOSÉ PATTAS BASTOS FRANCO
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A Novel Approach for Parameter Extraction of an NMPC-based Visual Follower Model
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Líder : ANDRE GUSTAVO SCOLARI CONCEICAO
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MIEMBROS DE LA BANCA :
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ANDRE GUSTAVO SCOLARI CONCEICAO
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ANDRE LUIS MARQUES MARCATO
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PAULO CESAR MACHADO DE ABREU FARIAS
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TIAGO TRINDADE RIBEIRO
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Data: 10-ago-2020
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Resumen Espectáculo
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The main goal of this work is to study and develop systems for path detection and pa- rameters extraction directly from the image plane, using computer vision techniques, to feed controllers to perform NMPC-based Visual Path Following. Detecting a path to perform image-based control requires efficient processing that can extract parameters pre- cisely even in the presence of inconveniences in the navigation environment, such as path failures, spots of lights or shadows, poor lighting conditions, noise in the image captu- red, and floors with non-homogeneous colors. Such problems compromise the controller’s effectiveness because they affect the way the parameters are extracted.
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8
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JOÃO MARCOS RAMOS DE ABREU
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Elastic Optical Networks Planning with Protection: Managementing Failures
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Líder : KARCIUS DAY ROSARIO ASSIS
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MIEMBROS DE LA BANCA :
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ANTONIO CEZAR DE CASTRO LIMA
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JOSÉ VALENTIM DOS SANTOS FILHO
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KARCIUS DAY ROSARIO ASSIS
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Data: 14-ago-2020
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Resumen Espectáculo
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In Elastic Optical Networks - EON, the bandwidth of an optical path is variable and the overlap of the virtual topology in a physical topology must be designed to optimize the use of the spectrum. EONs, under static traffic, are typically designed using Mixed Integer Linear Programming (MILP) in order to minimize spectrum usage.
In this dissertation, a formulation for protection in EONs is proposed, which, based on the concept of squeezing and fixing the bandwidth, including shared risk groups, returns with the minimization of the maximum number of slots used in any physical link in the network. The route for each demand in the physical topology is determined by equilibrium equations together with restrictions of the physical layer in the formulation, so that pre-calculated routes are not necessary and the modulation format of each established optical path can be chosen with transmission quality needed. The first results evaluate the effectiveness of the MILP formulation for a small network when the connections are under different requirements of the Service Level Agreement - SLA and are provided by an appropriate protection scheme and different modulation formats. Subsequently, simulations are carried out on slightly larger real networks, such as the Via Network and the National Education and Research Network (RNP). Case studies are carried out to analyze the basic properties of the proposed formulation.
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9
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VIVIANA MARIA VACAS MARQUEZ
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Optimal Passive Filter Placement in Electrical Radial Distribution System Using Any Colony Algorithm
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Líder : FERNANDO AUGUSTO MOREIRA
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MIEMBROS DE LA BANCA :
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NIRALDO ROBERTO FERREIRA
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FERNANDO AUGUSTO MOREIRA
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KLEBER FREIRE DA SILVA
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ALESSANDRA FREITAS PICANÇO
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Data: 28-ago-2020
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Resumen Espectáculo
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Harmonic currents originated by non-linear loads flow through the electrical distribution system, causing distortion of the bus voltages and excessive power losses in the system. One of the most conventional solutions to keep the electrical power quality indicators at acceptable levels, such as voltage amplitude and frequency, unbalanced voltage and harmonic distortion, is the installation of passive harmonic filters in distribution networks. However, the planning of multiple harmonic filters in distribution systems can be interpreted as a discrete and combinatorial nonlinear programming problem. The combinatorial explosion worsens when increases the number of busbars in the distribution system. Few optimization techniques have been used to solve this problem, but not all are attractive because they cause a lon g time in the computational processing of the algorithms. For this reason, optimization techniques based on heuristic and metaheuristic methods have been improved due to their appropriate structure to solve optimization problems efficiently and quickly. This work presents a methodology based on the Ant Colony Optimization (ACO) metaheuristic, which together with a harmonic power flow algorithm, determines the optimal allocation and sizing of passive harmonic filters in electrical radial distribution systems. The objective is to reduce the total annual cost of active power losses, the cost of passive filters installation and the total harmonic distortion (THD), considering the constraints of the bus voltages and THD. In order to evaluate the proposed methodology based on multilevel ACO (allocation and sizing of filters), it was compared with another technique found in the literature. Thus, tests were performed on theses radial distribution systems with 10, 11, 18 and 34-bus balanced, and 33-bus unbalanced, with linear and non-linear loads.
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10
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THIALE MOURA ALCÂNTARA DE OLIVEIRA
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Design of Elastic Optical Networks with the Max-RMSA approach
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Líder : KARCIUS DAY ROSARIO ASSIS
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MIEMBROS DE LA BANCA :
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KARCIUS DAY ROSARIO ASSIS
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LUCIANA MARTINEZ
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HELIO WALDMAN
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Data: 11-sep-2020
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Resumen Espectáculo
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Four formulations of Mixed Integer Linear Programming (MILP) will be presented to solve the problem of traffic maximization and spectrum routing, modulation and allocation (Max-RMSA) in elastic optical networks (EONs). The first two models are formulations without using the Grooming technique with and without predefined optical paths (NPSP - Non Predefined Shortest Paths) and (PSP - Predefined Shortest Paths), in which NPSP provides the global optimal solution, as it contains all the possibilities of network paths between each of the pairs of nodes, whereas the PSP provides, in general, a near-optimal solution, as it only has a set of predefined paths, thus reducing complexity and its search space. The last two models are also for solving Max-RMSA, however considering the use of the Grooming technique. Several simulations were carried out for each MILP and the results were analyzed in networks of small instances. For moderately large networks such as the National Science Foundation Network (NSFNET) only PSP formulations will be used, due to the complexity of NPSP formulations in networks with a higher number of instances, and a good solution can be found with a reasonable simulation time.
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11
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MARCIO FIGUEIREDO GARCIA
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AXEBOT II - A MODULAR PLATFORM FOR MULTI-ROBOT SYSTEMS
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Líder : JES DE JESUS FIAIS CERQUEIRA
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MIEMBROS DE LA BANCA :
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AUGUSTO CESAR PINTO LOUREIRO DA COSTA
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JES DE JESUS FIAIS CERQUEIRA
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TIAGO TRINDADE RIBEIRO
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VITOR LEAO FILARDI
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Data: 22-sep-2020
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Resumen Espectáculo
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Autonomous robots are provided to perform a certain activity with minimal human intervention. However, the performance of these activities would not be possible to be carried out if the capacity for autonomous movement was not included in these robots. Thus, for these studies to be possible, a reliable experimental environment is necessary, with the possibility of changes and adaptations in terms of software and hardware appropriate to the research needs. The platforms for practical development, present themselves as an essential alternative to experimentation with real robots, since they allow the realization of experiments in a perfectly organized environment. Based on this purpose, a modular robotic platform was developed in the present work, composed of a PCB provided with a reconfigurable hardware architecture. On this platform, composed by the omnidirectional robot, it was configured to execute an embedded cognitive autonomous agent model, using three platforms connected to the CAN bus ( textit Controller Area Network). The agent architecture consists of three levels, namely: the reactive level (perception-action) that will be executed by the PSoC platform r 5L consisting of behaviors created on a kinematic controller, the instinctive level (coordination) composed through the LTeK r IoT LPC546xx platform and the cognitive level (planning) composed by the RENESAS r GR-PEACH platform, which are executed concurrently. In addition, the architecture of the cognitive agent was configured and programmed to merge reactive behaviors at the instinctual level using fuzzy logic where an experiment was carried out that the robot was able to navigate without fail during the execution of the agent.
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12
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LUCAS DO ESPIRITO SANTO FERNANDES
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Analysis of the Energization Switching in Ultra-High-Voltage Transmission Lines
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Líder : FERNANDO AUGUSTO MOREIRA
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MIEMBROS DE LA BANCA :
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DAMASIO FERNANDES JR
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FERNANDO AUGUSTO MOREIRA
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MILTON ELVIS ZEVALLOS ALCAHUAMAN
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RENATO JOSE PINO DE ARAUJO
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Data: 02-oct-2020
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Resumen Espectáculo
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The challenge of transporting large blocks of energy over long distances with low cost and high efficiency has attracted several studies for the application of transmission lines above 1000 kV. In this work, an analysis of the energization switching in UHV (Ultra-High-Voltage) lines is performed for lines with voltage levels between 1000 kV and 1200 kV, long lines above 900 km and considering the variation of the reactive compensation. This analysis seeks to find the most severe overvoltage levels, looking for methods to mitigate such disturbances in the energization of the lines. Besides the overvoltage analysis, the work also compared different configurations for the line compensation, defining, therefore, the one that presented the best configuration among them. The overvoltages resulting from the simulated operations were obtained with the PSCAD (Power System Computer Aided Design) software, commonly used for the simulation of electromagnetic transients in power systems. In the end, a comparison for the suppression of these overvoltages was performed involving three possible methods: surge arresters, pre-insertion resistor, and the controlled switching of the lines.
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13
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GILVAN FARIAS DA SILVA
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CORROSION DETECTION USING PULSED EDDY CURRENTS AND NEURAL CLASSIFIERS WITH TRAINING CONSTRAINTS
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Líder : PAULO CESAR MACHADO DE ABREU FARIAS
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MIEMBROS DE LA BANCA :
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EDUARDO FURTADO DE SIMAS FILHO
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Nadia Nedjah
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PAULO CESAR MACHADO DE ABREU FARIAS
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Werner Spolidoro Freund
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Data: 30-oct-2020
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Resumen Espectáculo
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Corrosion of metal pipes is a common problem in the industry. If not detec- ted in time, it can cause pipe disruption, resulting in loss of production and serious accidents. At insulated industrial pipes the corrosion can remain hid- den under thermal insulation, or inside the pipe. To detect corrosion visually, it is necessary to temporarily remove the thermal insulation. However, this removal may be impractical with the industrial plant in operation. There- fore, in this work, a type of non-destructive test called pulsed eddy currents (PEC) was used to detect this hidden corrosion. The interpretation of the test depends on the experience and technical skill of the operator. At aplica- tions like this, each misclassification has different consequences. Classifying a corroded pipe as not having corrosion inhibits the execution of proper main- tenance, increasing the chances of the pipe breaking. In this work, it was proposed a neural classifier to assist the operator in decision making. This classifier was trained with particle swarm optimization with restrictions, in order to consider the different classification errors in different ways. It was considered errors that increase the risk of accidents are more undesirable than errors that cause only financial losses. To evaluate the proposed method, it was used PEC signals acquired from pipes of a petrochemical industry. The classifier trained by the proposed method did not present classification errors that compromise the safety of the industrial plant. Contrary to what was observed with classifiers trained by the different variations of the backpropa- gation method analyzed in this work.
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14
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CAIO DOS SANTOS MAGALHÃES
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OBUST H∞ CONTROL FOR PWM BOOST CONVERTERS SUBJECT TO AGING CAPACITOR CONDITIONS
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Líder : BERNARDO ORDONEZ
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MIEMBROS DE LA BANCA :
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BERNARDO ORDONEZ
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ANDRE PIRES NOBREGA TAHIM
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HUMBERTO XAVIER DE ARAUJO
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HUMBERTO PINHEIRO
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VALTER JÚNIOR DE SOUZA LEITE
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Data: 26-nov-2020
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Resumen Espectáculo
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Boost converters are a topology of DC-DC switch-mode converter that is used in several applications, including power supplies, powertrain interface for hybrid vehicles, photovoltaic systems and aerospace industry. These devices usually employ aluminum electrolytic capacitors due to its low cost and high power density. However, these components are heavily affected by aging owing to electrolyte evaporation, which leads to an increase on the ESR value and a decrease on capacitance. Although the capacitor is one the main causes of failure in power converters, the parameter uncertainty related to this device has not been properly investigated in the publications about robust control of power converters.
This dissertation addresses the problem of linear robust control of the boost converter, operating in CCM, with the purpose of output voltage regulation. A more comprehensive model is developed, including the uncertainties in the capacitor ESR and its capacitance. The usual consideration of uncertainty in the duty cycle and load resistance is kept in the model. Moreover, output load and input voltage are considered as sources of disturbance in the converter circuit.
A convex modeling is accomplished by the construction of a polytope that comprises all possible linearized models of the converter. In order to minimize the polytope volume and, consequently, reduce the conservatism of the proposed solution, the polytope vertices are determined by the polytopic covering of the projections of the uncertainty region. The synthesis of a robust H∞ state feedback controller is performed by a convex optimization problem based on LMIs. The algorithm includes pole placement restrictions in closed-loop.
One of the states of the system is an unmeasurable tension related to the capacitor, therefore it must be estimated for implementing the state feedback control. Hence, the proposed solution consists in measuring the capacitor current, so that it can be used alongside the output voltage to identify the capacitor ESR and determine the unmeasurable state. Albeit it increases the system complexity, the ESR identification circuit can be used not only for control purposes, but also for monitoring the operational conditions of the converter. The proposed solution is validated by the results of PSIM simulations, considering an specific study of case.
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15
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Lauê Rami Souza Costa de Jesus
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IMPLEMENTATION OF A REAL-TIME PROCESSING SYSTEM FOR OBJECT DETECTION IN DIGITAL VIDEOS USING FPGA
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Líder : WAGNER LUIZ ALVES DE OLIVEIRA
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MIEMBROS DE LA BANCA :
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WAGNER LUIZ ALVES DE OLIVEIRA
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EDSON PINTO SANTANA
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PAULO CESAR MACHADO DE ABREU FARIAS
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ACBAL RUCAS ANDRADE ACHY
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Data: 27-nov-2020
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Resumen Espectáculo
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Digital video and image processing is an area that has many applications that need real-time performance, for example, Video Surveillance and Automotive Safety. A real-time image processing application aims to manipulate, analyze and process a large amount of data related to the pixels of an image in a stipulated time. These applications include image processing techniques like image analysis, image enhancement, image segmentation, object detection and others. Extracting the resources of an image is an intensive task with high computational cost and through the use of an FPGA device it is possible to achieve a more suitable implementation.
This work discusses the implementation of a Real-Time Processing System for Object Detection in Digital Videos using FPGA. All the steps of the FPGA design flow were developed. In this approach the steps of project specification, system modeling, microarchitecture, RTL coding, functional verification, logic synthesis, gate level simulation (logic post-synthesis), time analysis and FPGA device programming were included.
The proposed hardware architecture was designed and synthesized for Altera DE2-115 FPGA kit. The results are verified in real time with an input video from TRDB-D5M Terasic CMOS sensor, DE2-115 FPGA kit and VGA monitor for displaying images.
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16
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TIAGO TARGINO SEPULVEDA
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Application of neural networks for tracking maximum power in photovoltaic panels with shadowing
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Líder : LUCIANA MARTINEZ
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MIEMBROS DE LA BANCA :
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DURVAL DE ALMEIDA SOUZA
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FABIANO FRAGOSO COSTA
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LUCIANA MARTINEZ
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Data: 03-dic-2020
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Resumen Espectáculo
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This work presents a Maximum Power Point Tracking (MPPT) method in photovoltaic systems combining an Articial Neural Network (ANN) with a classic tracking technique known as Incremental Conductance (InC). Despite being widely applied, the InC technique generally fails to track the Maximum Power Point (MPP) under partial shading conditions due to the existence of local maximum points on the P-V characteristic curve. For this reason, an ANN has been trained in order to provide an initial reference voltage to the system that ensures that the InC tracking starts in a region which will converge to the MPP. To help in simulations, a solar cell is modeled and, based on parameters from a commercial solar module, the model of a photovoltaic panel is built using MATLAB software. The main methods of MPPT are described, pointing out the positive and negative sides as well as the respective implementation algorithms. The average small signal model is applied to the Boost converter, which considers small variations around an operating point, to obtain a linear model. With the delevoped model, it is possible to calculate the transfer function which re ects the in uence of the switching duty cycle of the DC-DC converter on the bus voltage that a photovoltaic arrangement is connected and thus insert a compensator to improve the efciency of the system. The main concepts of an ANN are presented and neural network training is performed using the backpropagation algorithm, which is based on the error calculated in the output layer to adapt the synaptic weights of the neuron layers. Then, the Constant Voltage, Perturb and Observe and Incremental Conductance methods are simulated. The results are discussed and compared taking into account the efciency of the search under variation of radiation and temperature and also under the efect of partial shading. The results of the proposed technique are presented considering dierent cases of arrangements and partial shading in order to demonstrate the efciency of the technique.
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17
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ARTHUR LÚCIDE COTTA WEYLL
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SHORT TERM LOAD FORECASTING USING ARTIFICIAL NEURAL NETWORKS
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Líder : EDUARDO FURTADO DE SIMAS FILHO
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MIEMBROS DE LA BANCA :
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EDUARDO FURTADO DE SIMAS FILHO
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ANTONIO CARLOS LOPES FERNANDES JUNIOR
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KIM NAKAMURA SAMEJIMA
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DANTON DIEGO FERREIRA
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Data: 03-dic-2020
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Resumen Espectáculo
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Industrial, residential and commercial buildings depend primarily on an uninterrupted and low cost energy supply. Brazil is a country rich in natural resources and renewable energy, but energy prices across the country are high. Despite the excellent levels of solar irradiation, the prevailing wind characteristics (constant and unidirectional) and also the generation of energy through sugarcane (biomass), the Brazilian energy matrix is predominantly dependent on hydroelectric plants. Due to high energy costs in the country, many companies are looking for alternative sources and systems that manage the demand and consumption of electricity. In this context, one of the most important prerequisites for power management is the power forecast required by the facility. The demand curves of a given location are greatly influenced by factors such as weather, human activities, and installed load. In this way, the appearance of load curves may vary greatly on a given day, making the forecasting task difficult. A proper forecast combined with a management system leads to the efficient use of energy by the consumer at the lowest possible cost. In this work, statistical and Artificial Intelligence methods were used to forecast short-term power in the interval of 15 and 30 minutes ahead using data from the power demanded by the electrical installation of the State University of Santa Cruz (Ilhéus, Bahia, Brazil) from March 2014 to March 2015. Only active power data was used to predict the active power demanded by the electrical system and three case studies were proposed to establish how to handle with time information available in the series to make the forecasts with the smallest possible error.
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18
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FRANKLIN LIMA SANTOS
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Application of the Hilbert-Huang Transform in Ultrasound Inspection Signals for Defect Classification using Neural Networks
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Líder : PAULO CESAR MACHADO DE ABREU FARIAS
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MIEMBROS DE LA BANCA :
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ANTONIO CARLOS LOPES FERNANDES JUNIOR
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CARMELO JOSE ALBANEZ BASTOS FILHO
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EDUARDO FURTADO DE SIMAS FILHO
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PAULO CESAR MACHADO DE ABREU FARIAS
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Data: 07-dic-2020
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Resumen Espectáculo
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The use of digital signal processing as an aid for diagnosing failures in manufac- turing processes has been very promising, as it allows to increase the efficiency of such processes and ensures product quality and the safety of installations. This work proposes the use of Hilbert-Huang transform (HHT) as a tool for feature extraction of ultrasound signals obtained in an experimental procedure on welded joints using the TOFD techni- que. HHT is a time-frequency decomposition that uses base functions for transformation that are estimated from the signals of interest. Such base functions are obtained from decomposition algorithms such as EMD, EEMD and CEEMDAN. Once the experimental signals were obtained and the HHT applied for feature extraction, a classifier based on multilayer perceptron neural network was used and showed a satisfactory performance, reaching efficiency product above 90% in all considered cases. When EEMD and CE- EMED were used as decomposition algorithms, the efficiency product achieved 98.5% and 97.4%, respectively, whereas the EMD algorithm was used, the value reached 95.3%. When HHT was associated with PCA, the classifier was able to discriminate the different defect classes with 91.0% for HHT-EMD, 93.0% for HHT-EEMD and 92.7% for HHT- CEEMDAN. These results are comparable to those found in the literature in which use other pre-processing techniques, whose highest values obtained for a similar dataset were 94.8% using the DFT and 97.5% for DFT with PCA.
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19
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ELMO ALBERTO TEIXEIRA BORGES JUNIOR
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CONTRIBUTION TO THE DEVELOPMENT OF AN AUDITORY MODULE FOR ASSISTIVE ROBOTICS
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Líder : JES DE JESUS FIAIS CERQUEIRA
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MIEMBROS DE LA BANCA :
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JES DE JESUS FIAIS CERQUEIRA
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EDUARDO FURTADO DE SIMAS FILHO
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TIAGO TRINDADE RIBEIRO
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JUGURTA MONTALVÃO
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Data: 08-dic-2020
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Resumen Espectáculo
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This work proposes an automatic system of recognition of speaker and emotions through the voice signal with the application of statistical signal processing techniques such as the principal components analysis and the independent components analysis and artificial neural classifiers. Initially, characteristic descriptors of audio and voice signals such as Mel frequency cepstral coefficients are extracted from the audio files available in the used dataset. After this step, principal component analysis and independent component analysis techniques are applied to reduce dimensionality and remove redundant information between the parameters that will be presented at the input of the shallow neural network. In order to compare the results, also, pre-trained convolutional neural networks and recurrent neural networks with memory cell LSTM and BLSTM are used and that pre-trained convolutional neural classifiers, in an image database, can be used for the automatic recognition of emotions and speakers task achieving good discrimination efficiency.
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20
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RAFAEL FURQUIM JUNIOR
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Employment of the Clifford Geometric Algebra for the Analysis of Non-Linear Circuits
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Líder : FERNANDO AUGUSTO MOREIRA
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MIEMBROS DE LA BANCA :
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NIRALDO ROBERTO FERREIRA
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FERNANDO AUGUSTO MOREIRA
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KLEBER FREIRE DA SILVA
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ALESSANDRA FREITAS PICANÇO
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Data: 09-dic-2020
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Resumen Espectáculo
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The first theory created for the analysis of power in electric circuits under nonsinusoidal steady-state conditions
was proposed by Budeanu in 1927. It is based on an extrapolation of the classical method used for sinusoidal
steady-state conditions.
Since it does not explain adequately some aspects of the behavior of non-active
power flow, it has allowed the proposition of several other theories for almost the last
100 years.
Among the most recent propositions is the one by Castro-Nuñez, which uses, in
order to model the non-active power and the multivector aspect of the electric power, a
mathematical tool called Clifford Algebra or Geometric Algebra. However, this proposal
still does not reach its goal since its results diverge in the time-domain.
In this work, a new approach for the transformation between the time and
Clifford domains is presented, which is capable of reproducing the results from the
analysis of the instantaneous power in the time-domain. Also, it is proposed, for the first
time, a rotating operator, different for each frequency present in the circuit. Therefore,
the time-domain is perfectly reproduced in the Clifford-domain, a characteristic that is
not present in the proposal of other authors.
In order to validate the proposed method, four single-phase circuits in nonsinusoidal steady-state conditions
were solved in the time-domain and in the Clifford domain. These circuits contain fundamental frequency and
third harmonic voltage sources together with RLC loads. Also, a circuit containing a fundamental frequency
voltage source, a linear load, and a non-linear load consisting of a single-phase fullwave rectifier, was solved.
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21
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ADSON ALVES FERNANDES
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LOW SATURATION ONSET TRANSISTOR EQUIVALENT NETWORK
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Líder : ANA ISABELA ARAUJO CUNHA
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MIEMBROS DE LA BANCA :
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ANA ISABELA ARAUJO CUNHA
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EDSON PINTO SANTANA
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ROBSON NUNES DE LIMA
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MAICON DEIVID PEREIRA
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PAULO MÁRCIO MOREIRA E SILVA
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Data: 15-dic-2020
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Resumen Espectáculo
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This work presents a network of four MOS transistors, which is approximately equivalent to one of its devices, but which presents a lower saturation onset voltage. DC current-voltage characteristics of six network examples and the respective transistors to be replaced, either with n-channel or p-channel devices, are analyzed through simulation in SMASH software using BSIM model for a CMOS 130 nm technology, with 1.2 V power supply. For most cases, the simulation results reveal saturation onset voltage reduction in the order of a few hundreds of millivolts. An assembly with discrete prototypes allows also observing the network operation through the measurement of DC current-voltage characteristics, for conceptual validation. The proposed network is adequate to replace output transistors in cascode current mirrors, so that a low output conductance is achieved, with increased output voltage swing. This assertion is based on results obtained from the simulation of Widlar and cascode mirrors, as well as casdode mirrors with a transistor replaced by the proposed network. These results demonstrate that the modified cascode mirror may preserve other characteristics of the traditional cascode mirror, such as the DC mismatching error and the bandwidth, without a significant increase in dissipated power and at the cost of active area augmentation not above twice.
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22
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RICARDO SUTANA DE MELLO
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MAPPING THREE-DIMENSIONAL ENVIRONMENTS USING RGB-D and LiDAR SENSORS APPLIED TO MOBILE ROBOTICS
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Líder : ANDRE GUSTAVO SCOLARI CONCEICAO
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MIEMBROS DE LA BANCA :
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ANDRE GUSTAVO SCOLARI CONCEICAO
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LEONARDO DE MELLO HONÓRIO
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PAULO CESAR MACHADO DE ABREU FARIAS
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TIAGO TRINDADE RIBEIRO
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Data: 16-dic-2020
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Resumen Espectáculo
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The autonomous action of a robot is directly related to the way it perceives the environment around it. One of the main tasks of an autonomous robot is to be able to understand the complexity of the environment in which it is inserted. This complexity is due to the shape of the objects that are present in the environment, such as tables, chairs, boxes, walls, among others. For this, sensors such as: LiDAR, RGB and RGB-D cameras are used to perceive the world outside the robot. The method that perceives the external environment is known as SLAM - Simultaneous Localization and Mapping. In SLAM, the environment is modeled using sensors and an environment map is created iteratively as the robot moves. This work addresses the mapping of three-dimensional environments on a two-dimensional map using LiDAR and RGB-D sensors. For this, the LiDAR SICK LMS111 sensor and the Microsoft Kinect RGB-D sensor coupled to the mobile terrestrial robot HUSKY A200 were used. Using GAZEBO, a 3D model from the Robotics Laboratory of the Federal University of Bahia, the 3D model of the HUSKY robot and the SICK and Kinect sensors, the SLAM algorithms were used: HECTOR SLAM and RTAB-Map to produce an occupation map two-dimensional over a fixed path. The methods were able to represent the objects contained in the environment, which for trajectory planning activity is essential to have a consistent and true to reality map.
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23
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UBIRATAN DE MELO PINTO JÚNIOR
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ANTICOLLISION SYSTEM APPLIED TO ROBOTIC MANIPULATORS BASED ONARTIFICIAL POTENTIAL FIELDS
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Líder : ANDRE GUSTAVO SCOLARI CONCEICAO
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MIEMBROS DE LA BANCA :
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ANDRE GUSTAVO SCOLARI CONCEICAO
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AUGUSTO CESAR PINTO LOUREIRO DA COSTA
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RODRIGO ANTONIO MARQUES BRAGA
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Data: 16-dic-2020
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Resumen Espectáculo
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This Master’s thesis proposes the integration of an Adaptive Artificial Potential Fields algorithm with a new end effector orientation control technique for real-time robot path planning. The development of autonomous robotic systems has undergone several ad- vances in path planning algorithms. These systems generate object collision-free paths in the robot’s workspace. In this context, the Artificial Potential Fields technique has been the focus of improvements in recent years due to its simplicity of application and efficiency in real-time systems, since it does not require a global mapping of the robot’s workspace. In spite of its efficiency, this technique is susceptible to local minimum prob- lems of different natures, such as Goals Non-Reachable with Obstacles Nearby (GNRON). To solve this problem, we suggest the use of an improvement called Adaptive Artificial Potential Fields used in conjunction with the proposed end effector orientation control technique, which allows reaching a desired orientation of the end effector. The resulting force, generated from the Adaptive Artificial Potential Field, guides the robot end effec- tor to the goal. The Robot Operating System (ROS) framework and a collaborative robot manipulator UR5 are used to validate the proposed method on an approaching task for an object on a 3D printer tray.
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24
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ELIANA SILVA DOS SANTOS
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IMPROVEMENTS IN THE DESIGN OF THE LOW SATURATION ONSET TRANSISTOR
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Líder : ANA ISABELA ARAUJO CUNHA
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MIEMBROS DE LA BANCA :
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ANA ISABELA ARAUJO CUNHA
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EDSON PINTO SANTANA
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ROBSON NUNES DE LIMA
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MAICON DEIVID PEREIRA
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PAULO MÁRCIO MOREIRA E SILVA
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Data: 17-dic-2020
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Resumen Espectáculo
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This work presents a methodology for properly sizing the LSOT (Low Saturation Onset Transistor). The LSOT is a four-transistor network that emulates a MOS device with much lower saturation onset voltage by compensating the reverse saturation component of the main transistor drain current. The main transistor must have the same dimensions of the device to be replaced and, theoretically, the compensation device should be equal. However, the mobility degradation due to the transversal electrical field as well as other second order effects lead to current overcompensation in the structure, so that the DC output characteristic of the equivalent device presents an undesirable hump. A systematic procedure to dimension the compensation transistor is thus proposed, in order to smooth the LSOT current-voltage characteristic. A few guidelines are also suggested to dimension the other two transistors and slight modifications in the LSOT topology are tested, aiming to optimize circuit power and area. At last, we analyze the applicability of the LSOT as a succedaneum of one of the output transistors of a regulated cascode mirror. All circuits have been tested through a simulation tool.
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Tesis |
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1
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GABRIELE COSTA GONÇALVES
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DISTORTION IN MULTIPLIERS ANALOGS: COMPARATIVE ANALYSIS OF AC AND DC METHODS
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Líder : ANA ISABELA ARAUJO CUNHA
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MIEMBROS DE LA BANCA :
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ANA ISABELA ARAUJO CUNHA
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CARLOS EDUARDO VIANA NUNES
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RAIMUNDO CARLOS SILVÉRIO FREIRE
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SEBASTIAN YURI CAVALCANTI CATUNDA
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TITO LUIS MAIA SANTOS
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Data: 17-feb-2020
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Resumen Espectáculo
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This paper presents a theoretical comparison between three different criteria for the evaluation of harmonic distortion in analog multipliers: the two-dimensional integral non-linear function and the total harmonic distortion of two inputs, both proposed by our research group at the Integrated Circuits Design Laboratory (LCCI) of the Federal University of Bahia, and conventional simple total harmonic distortion. Methodologies are proposed to determine these figures of merit using DC characterization. In addition to the direct determination of the integral non-linear function of two dimensions, the distortion coefficients calculated to adjust the DC transfer surface are used to estimate the total harmonic distortions for single or double input. Simulation and experimental results obtained for four different topologies of analog multipliers in CMOS technology demonstrate that figures of merit determined either by AC analysis or by DC analysis can be consistent. We also illustrate how to take advantage of the distortion analysis of analog multipliers through DC characterization to establish circuit design and implementation guidelines to minimize distortion. For this purpose, two analog multipliers in voltage mode CMOS technology are analyzed theoretically to relate the distortion coefficients of their DC transfer surfaces to the technological parameters and the geometry of the transistors.
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2
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ANTONIO JOSE SOBRINHO DE SOUSA
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CMOS Analog Multiplier Architectures for the Application as CNN Synapse
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Líder : ANA ISABELA ARAUJO CUNHA
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MIEMBROS DE LA BANCA :
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ANA ISABELA ARAUJO CUNHA
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EDSON PINTO SANTANA
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JOAQUIM JÚNIOR ISÍDIO DE LIMA
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KLEYMILSON DO NASCIMENTO SOUZA
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MAICON DEIVID PEREIRA
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Data: 24-abr-2020
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Resumen Espectáculo
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This work presents new architectures of analog multipliers in CMOS technology, for the application as synaptic elements in cellular neural networks (CNN). The proposed networks adopt two voltage-mode inputs and current-mode output, and are based on the principle according which the MOSFET acts as a gate-source voltage squarer in strong inversion and saturation. Although such principle is employed by numerous CMOS multipliers with voltage-mode inputs, the here described circuits are innovative concerning the signal application methods. One of these methods avoids the use of reference voltage generators. The circuit performance is analyzed in several aspects through simulation in 130 nm CMOS technology using symmetric power-supply of +0.6 V. In all designs a special care has been taken to reduce the area with respect to prior works of the same research group.
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3
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MARCOS YUZURU DE OLIVEIRA CAMADA
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A Performance Analysis of Machine Learning Algorithms for Affective State Recognition: An Application for Autistic Behaviors
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Líder : JES DE JESUS FIAIS CERQUEIRA
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MIEMBROS DE LA BANCA :
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JES DE JESUS FIAIS CERQUEIRA
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AUGUSTO CESAR PINTO LOUREIRO DA COSTA
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EDUARDO FURTADO DE SIMAS FILHO
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ANTONIO MARCUS NOGUEIRA LIMA
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IVAN NUNES DA SILVA
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PABLO JAVIER ALSINA
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Data: 05-jun-2020
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Resumen Espectáculo
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Stereotyped Behaviors (SBs) are atypical and repetitive movements of the body, which can be related to low mental health condition. These behaviors can lead the patients to increase their activation levels. The development of systems able to both recognize SBs and inferring activation level automatically can aid some therapeutic approaches. In this paper, a system is proposed to infer activation levels from recognized SBs, where different Machine Learning Algorithms (MLAs) are used for identifying the SBs and for determining the related activation levels. A performance metric, called Temporal Performance Index (TPI), is also proposed to evaluate the performance of MLAs that consider the time for classification of SBs by relating it to accuracy and precision. For classifying the SB, the Hidden Markov Models and Multilayer Perceptron presented the best performance than Support Vector Machine and Convolutional Neural Network. The Adaptive Neuro-Fuzzy technique based on the Fuzzy C-Means Clustering algorithm allowed one to determine and differentiate the activation levels of the three stereotyped behaviors considered in the present study.
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4
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LUCAS CRUZ DA SILVA
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Decision support system for ultrasound non-destructive evaluation based on extreme learning machines embedded in microcontrollers.
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Líder : EDUARDO FURTADO DE SIMAS FILHO
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MIEMBROS DE LA BANCA :
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EDUARDO FURTADO DE SIMAS FILHO
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PAULO CESAR MACHADO DE ABREU FARIAS
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ANTONIO CARLOS LOPES FERNANDES JUNIOR
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LUCIANO MANHÃES DE ANDRADE FILHO
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ROMIS RIBEIRO DE FAISSOL ATTUX
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Data: 08-jul-2020
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Resumen Espectáculo
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This work aims to establish a technological basis for an ultrasound non-destructive evaluation decision support system, that may be portable to a microcontrolled platform. Extreme learning machines, a fast training class of artificial neural network, are used as pattern classifier. The purpose is to obtain a dedicated system capable of recording the input data, training and operating the classifier system, and finally producing an integrity status indication for supporting the operator decision. A case study on integrity evaluation of weld beads in steel plates was considered. The basics of ultrasonic non-destructive testing and artificial neural networks are introduced. Further aspects are considered in order to accomplish the referred objective, such as: a comparison between a fast-training neural network and traditional ones; a method to reduce the feature set dimensionality and the proposed approach for system realization in microcontrollers. The results indicate that the system realizes the training step of a classifier in the microcontroller to carry out the classification of weld defects in similar accuracy performance as reported works in the literature.
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5
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ERICK BALEEIRO DA SILVA
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Damping of electromechanical oscillations in electric power systems: an approach using partial eigenstructure assignment
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Líder : JOSE MARIO ARAUJO
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MIEMBROS DE LA BANCA :
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JOSE MARIO ARAUJO
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FERNANDO AUGUSTO MOREIRA
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TITO LUIS MAIA SANTOS
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BETÂNIA GOMES DA SILVA FILHA
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CAROLINA DE MATTOS AFFONSO
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Data: 27-ago-2020
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Resumen Espectáculo
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In this thesis, a partial eigenstructure assignment methodology is applied to dampen electromechanical oscillations in electrical power systems. The approach is anchored in allocating a small number of undesirable eigenvalues, for example, which are poorly damped, preserving the stable region of the spectrum - the so-called no spillover allocation. The ideal design is carried out using genetic algorithm techniques, and, considering that the order of the system may be higher for a general case, state observers are employed to estimate the states of the system, thus offering a viable implementation in practice. Simulation examples using a system with a synchronous machine connected to an infinite bus and multi-machine systems showed that the presented methodology is efficient in dampening the local and inter-area oscillation modes, quickly stabilizing the system in the event of a small disturbance when compared to the stabilizer of classic power systems. In addition to the traditional design using frequency techniques, genetic algorithms made it possible to obtain the stabilizer parameters and define a region for the partial eigenstructure assignment in order to employ state observers without requiring a great effort from the controller, enabling its implementation for larger systems.
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6
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TANIEL SILVA FRANKLIN
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CONTRIBUTIONS FOR THE CONTROL OF SYSTEMS WITH TIME VARYING DEADTIME: FREQUENCY APPROACH BASED ON PREDICTORS
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Líder : TITO LUIS MAIA SANTOS
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MIEMBROS DE LA BANCA :
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ANTONO DA SILVA SILVEIRA
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BISMARK CLAURE TORRICO
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CARLOS EDUARDO TRABUCO DOREA
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HUMBERTO XAVIER DE ARAUJO
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TITO LUIS MAIA SANTOS
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Data: 04-dic-2020
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Resumen Espectáculo
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Introduction: Time-delay systems are presents in several industrial sectors and they has also beeing affected by 4.0 connectivity trends whose changes impose relevant control challenges in order to achieve robust performance due time varying deadtime effect included in control loops. Objective: propose simple and robust stability criteria to systems affected by time varying delay and controlled by predictors using a frequency approach based on small gain theorem. Methods: based on small gain theorem some criteria are proposed using predictors in order to compensate a constant portion of time varying deadtime and the others criteria are obtained directly on second order systems described by receptances. Unstructured uncertainty descriptions are used as a way to simplify robust analysis and the results are illustrated through simulations and an experimental case. Results: the criteria obtained provide limited values to maximum deadtime based on model information and uncertainties bounds. The robust stability can be recovered through the robustness filter during operation by adjusting the filter tuning. The criteria are simple to apply and can be verified using computational mathematical tools. Besides that, there is no needs to assume any information about time delay change rate. Conclusion: simulation and experimental results illustrate the usefulness of this approach as an alternative to traditional methods, which usually disregard the use of predictors and their impact on robustness margins and time varying deadtime.
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7
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FELIPE MENDES DE VASCONCELLOS
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Development of a Time-Frequency Hybrid Model for the Evaluation of the Lightning Performance of Transmission Lines Using EMTP-Type Platforms
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Líder : FERNANDO AUGUSTO MOREIRA
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MIEMBROS DE LA BANCA :
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ANTÔNIO CARLOS SIQUEIRA DE LIMA
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FABIANO FRAGOSO COSTA
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FERNANDO AUGUSTO MOREIRA
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KLEBER FREIRE DA SILVA
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MARCO AURELIO DE OLIVEIRA SCHROEDER
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RAFAEL SILVA ALÍPIO
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Data: 16-dic-2020
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Resumen Espectáculo
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This thesis is dedicated to the study of the lightning performance of transmission lines. It proposes to include both frequency-dependent and non-linear time-dependent characteristics of the elements typically involved in this type of study, to establish consistent protection strategies and reduce the outage rates. A new model for the grounding system is proposed, based on transmission line theory, but not disregarding the electromagnetic coupling between the counterpoise cables arranged in parallel, as most works do. The model is validated comparing the results with those of the Hybrid Electromagnetic Model (HEM), based directly on Maxwell's Equations, widely used and recognized for its accuracy. The results obtained accuracy in the order of 100% to 96.1%, in concern to HEM, for typical configurations of transmission line grounding. From the systematic realization of hybrid time-frequency simulations using the proposed model, it is also characterized, in a general way, the influence of the dependence of the frequency of the soil electrical parameters in the performance of transmission lines against atmospheric discharges. It is concluded that disregarding this effect would lead to rough estimates of the actual performance of the line, which, when taken as true, would cause consequent errors in the protections applied to these electrical systems. Finally, it is proposed to evaluate the efficiency of the technique of partial protection of transmission lines by lightning devices through an innovative approach, by calculating the number of disconnections per line length per year with consideration or not of the variation of the electrical parameters of the ground with the frequency. Based on the results found, the efficiency of the technique of partial protection of transmission lines in maintaining the performance of these lines within the minimum requirements established by the regulatory agencies is proven, and again the importance of considering the frequency-dependent effect of the soil parameters in evaluating the lightning performance of transmission lines, with the risk of incurring technically inefficient and economically costly solutions.
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8
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ADEMIR DE JESUS COSTA
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Improvements on the Advanced Compact MOSFET Model and its Application to the Design by Hand of Analog Circuits
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Líder : ANA ISABELA ARAUJO CUNHA
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MIEMBROS DE LA BANCA :
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ANA ISABELA ARAUJO CUNHA
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EDSON PINTO SANTANA
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MAICON DEIVID PEREIRA
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MARCIO FONTANA
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MÁRCIO BENDER MACHADO
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OSCAR DA COSTA GOUVEIA FILHO
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Data: 18-dic-2020
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Resumen Espectáculo
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This Thesis presents an improved version of the Advanced Compact MOSFET model (ACM model) for application in hand calculations, required in the design of CMOS analog integrated circuits. The here accomplished research gave rise to semiempirical sub-models to be introduced into the basic model of the MOSFET drain current. These sub-models take into account second order effects, thus increasing the accuracy of the ACM model in the design stage of preliminary device dimensioning, which precedes the simulation stage. Methodologies have also been developed for the extraction of modeling parameters and have been applied to simulated DC characteristics from a CMOS 130 nm technology. The chief aim of this remodeling approach is to minimize the time spent in analog circuit design, by allowing reducing the number of iterations between the stages of hand calculation and simulation. Systematic methodologies have been proposed to the design of some basic CMOS analog cells, using the improved and original versions of the ACM model. The application of these methodologies to several design examples made it possible to compare simulation results, using the dimensions obtained from design by hand, with the specifications and hence to verify the reliability of the improved ACM model.
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9
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RICARDO MENEZES PRATES
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DEFECTS DETECTION AND INSULATOR CLASSIFICATION FOR POWER DISTRIBUTION NETWORKS USING DEEP LEARNING
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Líder : EDUARDO FURTADO DE SIMAS FILHO
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MIEMBROS DE LA BANCA :
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EDUARDO FURTADO DE SIMAS FILHO
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ANTONIO CARLOS LOPES FERNANDES JUNIOR
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JOSÉ MANOEL DE SEIXAS
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MARCELO ZANCHETTA DO NASCIMENTO
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RODRIGO PEREIRA RAMOS
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Data: 18-dic-2020
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Resumen Espectáculo
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Overhead Power Distribution Lines (OPDL) correspond to a large percentage of the medium-voltage electrical systems available worldwide. In these networks, Visual Inspection activities (VI) are usually performed without resorting to automated systems, requiring a significant investment of time and human resources. VI are also vulnerable to subjective evaluation and human error, which can lead to incorrect and/or inaccurate inspection results. In this perspective, the present PhD study proposes to introduce a set of intelligent techniques aimed at vision-based automatic inspection of medium voltage OPDL, aiming at the components identification as well as the diagnosis of defects visible to the naked eye. For this purpose, different computational models were developed based on Digital Image Processing (DIP) and Artificial Intelligence (AI) techniques. As an additional part of this research, it was created an image database of OPDL components collected in a photographic studio and from a realistic OPDL created outdoors. To optimize the computational models performance, different types of intelligent algorithms and deep learning techniques were evaluated, with emphasis on Convolutional Neural Networks (CNNs), hybrid configurations and frameworks of Generative Adversarial Networks (GANs). In addition, other approaches were implemented, such as: data augmentation; transfer learning and Multi-Task Learning (MTL); background invariance and Image Generators (IG). The preliminary results indicate satisfactory performance of the proposed techniques in class identification and defect detection of distribution insulators, providing a series of innovations in relation to other available solutions.
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10
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FABIAN SOUZA DE ANDRADE
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APPLICATIONS OF A CMOS ANALOG CNN TO FILTERING OPERATIONS FOR VISUAL PROCESSING
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Líder : ANA ISABELA ARAUJO CUNHA
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MIEMBROS DE LA BANCA :
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ANA ISABELA ARAUJO CUNHA
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EDSON PINTO SANTANA
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EDUARDO FURTADO DE SIMAS FILHO
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JES DE JESUS FIAIS CERQUEIRA
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DELMAR BROGLIO CARVALHO
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EDUARDO TELMO FONSECA SANTOS
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Data: 22-dic-2020
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Resumen Espectáculo
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This work is a contribution to the realization in CMOS technology of an analog circuit, belonging to the biomorphic class of cellular neural networks, for image processing. Aiming at the reproduction of more complex operations than usual, a compact cell architecture was employed in the implementation of a network featuring two layers and mutual coupling, originated from an extension of the traditional CNN. To obtain the parameters that configure the network to perform the desired functions, a training methodology was developed, taking inspiration from some existing techniques addressed to this category of neuronal network and including modifications either to improve its performance in general or to adapt the process to some relevant characteristics of the various types of image operations considered. For verification purposes, the circuit is applied in simulations involving bipolar functions and image filtering, exhibiting similar results to the ones generated from an ideal model.
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11
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PRISCILA SILVA MARTINS
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I2E: A Cognitive Architecture Based on Emotions for Assistive Robotics Applications
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Líder : JES DE JESUS FIAIS CERQUEIRA
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MIEMBROS DE LA BANCA :
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JES DE JESUS FIAIS CERQUEIRA
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EDUARDO FURTADO DE SIMAS FILHO
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ANTONIO CARLOS LOPES FERNANDES JUNIOR
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IVAN NUNES DA SILVA
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LUCIENE CRISTINA ALVES RINALDI
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Data: 23-dic-2020
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Resumen Espectáculo
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Emotions and personality play an essential role in human behavior, their considerations, and decision-making. Humans infer emotions from several modals, merging them all. They are an interface between a subject's internal and external means. This paper presents the design, implementation, and tests of the Inference of an Emotional State (I2E): a cognitive architecture based on emotions for assistive robotics applications, which uses, as inputs, emotions recognized previously by four afective modals who inferred the emotional state to an assistive robot. Unlike solutions that classify emotions, with a single sign, the architecture proposed in this article will merge four sources of information about emotions into one. For this inference to be closer to a human being, a Fuzzy System Mamdani was used to infer the user's personalities, and a MultiLayer Perceptron (MLP) was used to infer the robot's personality. The hypothesis tested in this work was based on the Mehrabian studies and in addition to three experts in psychologists. The I2E architecture proved to be quite ecient for identifying an emotion with various types of input.
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