This dissertation presents a methodology for state estimation in islanded radial microgrids, incorporating steady-state frequency as a state variable. The focus is on dispatchable generators operating under droop control mode. The proposed estimator is framed as an optimization problem, utilizing the Maximum Correntropy Criterion (MCC) and considering nodal power injections as pseudo-measurements to ensure system observability. It integrates synchronized measurements from Phasor Measurement Units (PMUs) with generation data from dispatchable generators. Initially, an Optimal Power Flow (OPF) algorithm generates measurements and minimizes power losses. The performance of the proposed MCC-based approach is compared with a Weighted Least Squares-based estimator (WLS), demonstrating superior capability in rejecting bad data. This methodology is tested on a simulated 33-bus islanded microgrid, specifically focusing on scenarios with a single piece of bad data. When juxtaposed against the OPF results (assumed error-free), the MCC-based estimator exhibits a deviation of 2.43% compared to the 14.96% deviation noted with the WLS-based estimator.

The increasing demand for sustainable energy sources and the need to reduce dependence on fossil fuels have driven the development of solar photovoltaic systems. However, the efficiency of these systems largely depends on the ability to track the maximum power point, where the conversion of solar energy into electricity is maximized. Tracking the maximum power point is a challenging task as it involves searching for a specific point on a power characteristic curve. Traditionally, various techniques have been developed to optimize the performance of photovoltaic systems. However, one of the limitations faced by MPPT techniques is the lengthy tracking time required to find the maximum power point. Prolonged tracking time results in efficiency losses and inadequate utilization of available solar energy. In this context, this dissertation presents an innovative strategy to accelerate tracking techniques, aiming to reduce the time required to find the maximum power point. The development of this tracking acceleration strategy represents a significant advancement in the field of photovoltaic systems. The results obtained from implementing this methodology can contribute to improving the performance and efficiency of solar photovoltaic systems, facilitating their widespread adoption as a clean and renewable energy source.

This work presents a Probabilistic Three-Phase Power Flow based on the Unscented Transformation and the OpenDSS software's use, considering the uncertainty of loads and solar irradiance. The application of the Unscented Transformation allows for a reduction in the number of samples of uncertain variables. OpenDSS, a free software, provides greater flexibility in modeling the unbalanced distribution network. The developed tool is used to evaluate the effect of inverters Volt/Var control, which connects photovoltaic systems to distribution systems. The results obtained for a 13-bus system are compared with those provided by the Monte Carlo Simulation, allowing for a significant reduction in computational effort while maintaining the accuracy of the estimated statistical variables.

The multiphase induction machine offers several advantages over traditional three-phase motors, making it an attractive choice for industrial applications. These advantages include enhanced fault tolerance, the potential for torque improvement through harmonic current injection, and suitability for high-power drives. This project aims to assess the practicality of multiphase machines by conducting a comparative analysis between a nine-phase machine and a three-phase machine. It will encompass an examination of the sizing and selection of ferromagnetic and conductive materials used in the design of each machine. In addition, a comprehensive assessment will be conducted on the power supply circuits and semiconductor components utilized for driving these machines. Moreover, this project aims to deliver a comprehensive and in-depth analysis of the multiphase drive, comparing it to the conventional solutions typically utilized in high-power industrial applications.

The Quantile Graph (QG) method is a promising technique for mapping time series into

complex networks. The QG uses network statistics to characterize the time series and time se-
ries statistics to characterize networks. In addition, it presents low computational cost, and it is

simple to be implemented, as it has only one free parameter. The input time series are obtained
by measuring real systems or simulations. Thus, the time series data can be uncertain. However,

there are no known studies regarding the presence of incorporation of uncertainty into time se-
ries. Nonetheless, uncertainties can impact not only the parameters, but also the structure of the

model, and consequently changing the topology of the designed network. Therefore, it is rele-
vant to consider uncertainty in the QG. Based on this matter, the main objective of this work is

to investigate the consequences caused by uncertainties present in time series and investigate the
impact in the topology and behavior of the constructed network. Uncertainty is considered by
changing the threshold of the quantiles and using Monte Carlo simulation. The results express
the network’s metrics values for two time series with different uncertainty sources. In one case,
time-constant error from 5% to 20% are incorporated, while in the second case a growing error,
typical from chaotic computer simulation is investigated. Network’s metrics are compared with
no-uncertainty QG scenario. The main results found are that the proposed method is able to
express the changes in the constructed network caused by different types of uncertainties.

The growing use of distributed generators (GDs) causes significant changes in the operation of electric power distribution systems (SDEE), mainly in the predominantly radial ones. In addition, battery energy storage systems (SAEBs) are being used to provide auxiliary services to the grid due to their flexibility to act by injecting or absorbing power, which can mitigate the impact of DG penetration. However, it is necessary to program the actuation of these devices. In this context, this work proposes two intelligent management strategies to plan (day-ahead) the hourly State of Charge (𝑆𝑜𝐶) of a battery connected to IEEE test feeders (34 and 123 bus) with photovoltaic distributed generation. In summary, in the first methodology, two optimization metaheuristics (NSGA-II and MOPSO) were implemented to attenuate load demand peaks, reduce voltage transgressions concerning normative limits and minimize tap changeovers in automatic regulators. In addition, physical and operational constraints are imposed on the mathematical model to bring it closer to reality. The second methodology consists of monitoring the active power of the substation using it as a trigger signal for the dispatch or loading of the SAEB. It is noteworthy that the software Matlab and OpenDSS were selected, respectively, to structure the metaheuristics and calculate the temporal power flow due to their communication capacity. The results show that the traditional actuation by triggering signals ignores several possibilities of actuation, mainly in systems with multiple load peaks of different dimensions. Finally, the metaheuristic approaches stood out among the analyzed objectives.

Dynamic Security Regions and Steady-State Security Regions are three-dimensional graphs that evaluate the system's security when divided into three generation groups as the generation transfer among them takes place. Steady-State Security Regions will consider different generation scenarios considering limits for static quantities (such as voltages, power generations, and power flows). In addition, dynamic Security Regions employ active power limits and dynamic indices (such as damping factors associated with oscillation modes). The construction process of Dynamic Security Regions requires a higher computational effort than the static ones due to the modal analysis that must be performed in addition to the power flow calculation. In this work, an efficient method for constructing security regions is presented through the Particle Swarm Optimization (PSO) method. The main focus relies on Dynamic Security Regions, and a series of considerations are made to improve the PSO performance. The PSO is also used to optimize the damping controllers, and the impact of these adjustments on the Dynamic Security Regions is also investigated. The tests were carried out using the New England test system, and promising results were obtained from the point of view of precision and reduced computational effort.

This work is dedicate to the study of diffraction losses from along the path electromagnetic wave assisting of the cover of radio signal propagation for communication systems 5G, for this, the Parabolic Equation (PE) method was used. The numerical solution of PE method occur, on here, through the algorithms SSPE (SplitStep Parabolic Equation) and the SSPE added the DMFT (Discrete Mixed Fourier Transform) method. The first consider the surfaces like perfect electric conductor (PEC) and the second consider the electrical characteristics the surfaces, for thus, to specify the losses due the surfaces. The simulations developed here are compare to those measurements performed at microwave frequencies, at CEFET-MG in Belo Horizonte. The RMSE is calculated for analyze the differences between the measurements and the two algorithms developed and between the both algorithms. The RMSE represent the quality of the model settings. The main contribution of this the dissertation is the characterization of diffraction effects, considering the terrain losses, in the frequency range of 1,0 a 8,5 GHz, that has potential to are using in future mobile wireless communication.

Systems identification is an area that seeks to represent systems according to their input and output data through mathematical models. The PieceWise affine AutoRegressive with eXogenous input (PWARX) model has gained increasing prominence for its ability to identify non-linear systems using local linear submodels. In this sense, this work defines methods for identification with this class of model mentioned when using procedures, such as the error reduction ratio, information criteria and machine learning algorithms. Thus, the defined strategies cover all the necessary steps, without requiring any information about the system. Algorithms that make use of the meta-heuristic technique to separate the regions of PWARX models are also presented. These methods are able to increase the representativeness of the switched model and, in addition, they manage to reduce the complexity of the model by reducing its number of regions for cases in which it is over-parameterized. Furthermore, it is shown that this collection of linear submodels is capable of competing in terms of representativeness even with polynomial Nonlinear AutoRegressive with eXogenous input (NARX) models. Subsequently, sufficient conditions to represent hysteresis with PWARX models are presented. It is shown that these conditions are directly related to the excitation function of the system and also to the equilibrium points of each linear submodel of the switched model. The hysteresis phenomenon is highly non-linear and encompasses memory effects between the output and the history of the process variables. Therefore, a model estimated from data produced by the Bouc-Wen model is identified.

The electricity sector has been experiencing a competitive and deregulated environment in recent decades. In this context, several activities for operation and expansion planning of electrical power systems have become the subject of important reassessments and new recommendations. Among these activities, there is the maintenance schedule for generating units, which faces philosophical changes mainly arising from the transition from the centralized to the decentralized market and the modification of the energy matrix with the significant presence of renewable sources. Maintenance scheduling seeks to identify the best time during the operation of an electrical system to remove electric power generation units for carrying out maintenance actions, thus resulting in better maintenance schedules. In this dissertation, a methodology is proposed to solve the problem of scheduling the maintenance of generating units for an electrical system considering the decentralized market and renewable sources. To this end, performance indicators are used based on the system's reliability levels and the electricity production costs. The Evolutionary Strategy metaheuristic is used to solve optimization problems. To assess the reliability of maintenance schedules during the problem solving process, the Non-Sequential Monte Carlo Simulation algorithm associated with Cross Entropy is used. The efficiency of the proposed methodology is illustrated through case studies involving the IEEE-RTS test system with some changes. The performance of the proposed methodology is assessed through the identification of good quality schedules (i.e., technically feasible and adherent to the operational reality from a systemic perspective), which guarantee adequate levels of reliability for the system's operation, without causing excessive increases in its operating cost

Electricity systems are often a target of undesired electromagnetic surges, the outcomes of which may be quite costly. There are overhead and buried conductors that are subject to the impulsive currents associated with such surges, whose resulting electromagnetic fields interact with each other, that is, overhead and buried conductive elements are mutually coupled. Thereafter, the air-ground interface has a decisive influence on the establishment of this coupling. Given that specific topic relevance, there are researches that addresses the modelling of the airground interface to determine its influence on the electromagnetic field. Some numerical techniques may be used, for example, the Finite Element Method or the Finite Difference Method in the Time Domain, which naturally includes the different electromagnetic material properties of the media parted by generic interfaces. Nevertheless, notwithstanding the existence of such numerical techniques, within the context of this work, it has been chosen to consider research that has the most elementary possible source of electromagnetic field, namely, the Hertz dipole. From this elementary source, a method for determining electromagnetic fields (in the air and on the ground), generated by Hertz dipoles, immersed in the air, placed at a height from a plane interface that separates the air from the ground, is presented. Decomposition of the spherical electromagnetic wave (from the current distribution in the dipole) in a sum of infinite plane waves is carried out. Finally, some analyzes, of the electromagnetic field concerning the frequency of the current signal in the dipole, the resistivity of typical soils and distances between source and field observation point is performed. From these analyzes, it is possible to extract important physical behaviours from the corresponding electromagnetic field, which, to the best author’s knowledge, are not explored deeply in the available scientific writings

One of the modern society features is the presence of comfort and technology. These words have begun to make sense to human being since the electrical energy got available to population through distribution lines. This one constitutes the final link of a complex system for energy supply started inside generating plants and transported in high scale through transmission lines. It’s necessary expanding the electrical system for suppling the growing demand for power. As a result, the concessionaries are instigate to keep the going services on to customers located in urban or rural areas. The ANEEL, as regulation agency, periodically disseminates distribution quality indicators such as global DEC and TMAE. Therefore, great efforts are establish for fulfillment of goals specifically the first one. Off-goal continuity indicator translates in expressive penalties and possible administrative sanctions that are imposed through regulator agency toward electrical power distributor. This dissertation purposes one methodology that can to estimate the behavior of DEC indicator due TMP decreasing during emergency outages. In consequence, distribution system reliability evaluation based on analytical models are used. Aiming the proposal concepts authentication, real distribution line case studies are shown and discussed.

An extensive range of modern applications allows the use of non-isolated DC-DC converters with high gain, such as renewable energy conversion systems, uninterruptible power supplies (UPSs), among others. In this way, many topologies have been presented in the technical literature, making this subject relevant in the field of power electronics. Several dc-dc converters are only suitable for low-power applications. Therefore, the search for new topologies is motivated by the need to obtain higher conversion ratios for higher-power applications, while taking into account other important aspects, such as efficiency, number of components, and stresses on the semiconductors. In this context, this work presents a single-ended primary inductance converter (SEPIC) based on the three-state switching cell (3SSC) and voltage multiplier cells (VMCs), which is capable of providing a high voltage gain, with reduced stresses on the semicondutors. The operation principle, qualitative analysis and quantitative analysis of the proposed converter operating in continuous conduction mode are presented in detail. Simulation and experimental results are presented and discussed, in order to establish the advantages and disadvantages of this topology.

EFICIÊNCIA NA SIMULAÇÃO
COMPUTACIONAL PARA IDENTIFICAÇÃO E CONTROLE DE SISTEMAS NÃO LINEARES

The polynomial Nonlinear Autoregressive with eXogenous inputs (NARX) model family has been extensively studied over the last three decades, and several techniques have been proposed in this respect. The traditional work has mainly focused on methods based on a stepwise procedure known as Forward-Regression Orthogonal Least Squares (FROLS) algorithm. Extensions to model with multiples input and output have been stated as well as developing multi-objective approaches. Recently, the identification framework has been carried out in a probabilistic pattern, and contemporary techniques have been proposed consisting of evolutionary algorithms. These methods incorporate the knowledge about the probability distribution of possible model structures into the search process. An especially exciting class of new algorithm is the one based on metaheuristic. In this dissertation, a variant meta-heuristic method based on Hybrid Binary Particle Swarm Optimization and Gravitational Search Algorithm is presented for a single objective and multi-objective model structure selection. It takes into account the complexity of the model and the contribution of each term to build parsimonious models by proposing a new cost function formulation. In addition, the proposed method is adapted to obtain models in situations where the output is represented by a dichotomous variable, resulting in a classification model. The robustness of the new algorithm is tested on several simulated and experimental system with different nonlinear characteristics. The obtained results show that the proposed algorithm is capable of identifying the correct model, for cases where the model structure is known, and determine parsimonious models for experimental data even for those systems for which traditional and contemporary methods habitually fails. The new algorithm is validated over classical methods such as the FROLS and recent approaches based on meta-heuristic.

Three-phase induction motors are responsible for a large part of the conversion of electrical energy into mechanical energy in several types of applications. In the industrial sector, for example, the performance and operating conditions of these electric machines have a significant impact on the entire production process and, consequently, on profit margins. Given the important role played, it is highly relevant to seek ways to anticipate eventual failures, thus avoiding unexpected stopeges in the production line. Amoung the main techniques used in the diagnosis of electrical machine failures, the Motor Current Signature Analysis is quite widespread and consolidated. However, this has some limitations associated with the load and the constructive characteristics of the motor. In this context, it is desired alternatives that are able to word around the deficiencies in traditional methods and detect anomalies even in the early stages, ensuring more freedom and efficiency in maintenance planning. Stray flux monitoring for this purpose has been shown to be prominent due to the high sensitivity of the signals to small variations in operating conditions. In this work, the stages of design and implementation of a stray flux sensor are presented, as well as a methodology for processing the device signals, in order to assess the viability of these signals for fault diagnosis. From signals of electromotive force, induced in the sensor by the stray flux, orbits are built whose characteristics reflect the motor’s operating conditions. Five faulty conditions were analyzed and the results demonstrated the effectiveness of the proposed technique.

The current master thesis presents the modeling of the laying head system focusing on the characterization of the forces acting inside the pipe and the movement dynamics considering the laying head pipe with three degrees of freedom, operating at the lamination speed of 110 textrm m/s. The forces coming from the contact and kinetic friction of the wire rod with the inner wall of the laying pipe are very important inputs for understanding and classifying the main loop formation problems: premature wear of laying pipe and non-uniformity of the turn radius. With the characterization of these forces, it became possible to evaluate the distribution profile of forces acting on the laying head pipe , which are very sensitive to movement kinematics and to the kinetic friction coefficient, the main parameter responsible for causing internal pipe wear. It was also possible to evaluate the correlated effects the lack of synchronism between the translation speed of the wire and the rotation speed of laying head pipe, a parameter that stands out as critical for a good uniformity. lightning. The dynamic modeling of the laying head pipe with three degrees of freedom made it possible to evaluate its movement dynamics by characterizing the movements of its center of mass. In this approach it is noteworthy that the pipe exit hole of the pipe can perform unwanted movements with rotations about the axis of the pipe support bearing, key parameter for a good turn formation at high speeds. Moreover, it is presented by the torque equations dynamic coupling between the torques acting on the three axes of rotation, a phenomenon that can be explored as a proposal to control the correction of such unwanted movements.

This dissertation addresses the study of the problem of damping low-frequency electromechanical oscillations in power systems through the use of High Voltage Direct Current (HVDC) transmission links. Initially, the HVDC link model was included in an optimal power flow (OPF) to obtain the power system steady-state aiming at minimizing the generation cost. In a second stage, the HVDC link was modelled by a nonlinear differential–algebraic system of equations. These equations, together with the ones that describe the operation of the system in alternating current, are numerically linearized at the initial operating condition provided by the OPF. Further, the modal analysis is carried out, with the main objective of evaluating whether the low-frequency electromechanical oscillations are adequately damped. To increase the damping of these oscillations, damping controllers are included at generators and the HVDC link. For generators, conventional power system stabilizers (PSS) are considered. For the HVDC link, either conventional or multiband stabilizers (PSS4B) are considered. The damping controllers have been simultaneously designed by an optimization approach for maximizing the minimum damping coefficient of the system. The proposed methodology has been applied to the two-area four-generator power system and the New England system. The results show that only HVDC link (even with damping controller) is not able to ensure the power system stability. However, when damper controllers for HVDC link and synchronous generators are designed together, the system has a significant damping gain, thus guaranteeing its small-signal stability.

With the emergence and advancement of technologies, wireless communication systems for connecting objects to the Internet (Internet of Things), where devices exchange information in real time has been the subject of many studies. These systems use frequencies below 1 GHz in order to increase coverage, have high performance and thus ensure high information rates. In this work is presented the study of a propagation channel for application in Internet of Things in the frequency fixed in 903 MHz. With this, it is made the characterization of the fast fading of the signal and the effect of the presence of people in this channel from measures captured in indoor and outdoor environments. Different cases are used for the study and when evaluating the effects on the small-scale variation of the received signal level, a greater variability of the channel with the presence of people can be observed, and some statistical probability models are the key for the study, behavior and results found.

Lightning strikes pose a risk to people and equipment. For safety, electrical grounding systems are projected. However, it is necessary to be able to make a quantitative analysis of the project and the quantities of interest, such as step voltage. This often requires computer simulations. A mathematical model that can be used for such simulations is the Hybrid Electromagnetic Model (HEM). This work presents the HEM deducted from both T and Π equivalent circuits, using both a Global Immitance and Nodal Admittance formulation. There are also a number of simplifications that are presented that can be used with HEM, such as modified HEM (mHEM) or power series (sHEM). The main objective is to develop a high performance and open source computer program that implements HEM and its variants for use by industry and academia. To this end, good programming practices are followed. The program was created with the C programming language, with interfaces for Julia and MATLAB for easy use by the end user. The user must understand the algorithmic model t wants to implement, as the program is a numeric library (set of functions). The impedance matrices depend only on the medium and the geometry of the conductors. Taking advantage of geometric symmetry avoids redoing unnecessary calculations. An algorithm that uses the symmetry of uniform rectangular grids has been developed. The computational gain it offers is less pronounced the greater the number of segments in the system. For testing the program, simulations of a buried horizontal conductor and a rectangular grid are made, both results compared with those that have been published. Ground potential rise (GPR), electric field and step voltage are calculated. The step voltage is obtained both by the difference in scalar electric potential and by the line integral of the electric field. The results show that step voltage is not equal to potential difference.

Preliminary techniques for estimating muscle fiber conduction velocity was consolidated in the early 80s, but due to recent technological progress in electronics and computing, only in the last few decades studies have been published demonstrating more accessible and more practicable applications. This project aims to provide information about muscle fatigue through muscle fiber conduction velocity (MFCV) estimation upon the use of surface electromyography (sEMG), studying and improving bitstream modulation techniques and cross-correlation. The modulation technique discussed in this study presents an assessment based on a set of data generated by gain variation, providing an average of MFCV. The estimated results reveal a decrease in the MFCV correlated with the fatigue condition of the observed muscle. The main contribution of this work is the use of bitstream modulation for MFCV estimation, allowing distinguishing the decrease of MFCV statistically in different modulation representations on sEMG signals. The method was evaluated upon experimental study and supplied estimates of MFCV similar to those obtained by the literature, providing more conservative values when taking in account the average of a set of velocities every second.

This work investigates new convex conditions to design robust and Linear Parameter Varying (LPV) gains for continuous time-varying systems subject to saturating actuator and energy bounded disturbances. The input-to-state stability conditions are used to design controllers ensuring the minimization of the L2-gain between the disturbance input and the controlled output. Furthermore, optimization procedures to maximize the estimate of the region of attraction, and the bound to the control signal as well, are formulated. By means of sum of squares (SOS) decomposition, this work is also concerned with the design of state-feedback controllers for LPV polynomial continuous-time systems. The vector field presents polynomial dependence on states. For both cases, the state-feedback gains designed depend on the filtered time-varying parameter. When designing time-varying controllers for time-varying systems in practical situations, the noise on the parameter measures may induce abrupt changes in the gain values and, consequently, in the control signal. Therefore, one may expect early damages on the actuator due to wear and fatigue. Hence, filtering the time-varying parameter and guaranteeing that the closed-loop filtered system is stable may produce state-feedback gains with smaller variance over time. The methods proposed consider the filtered parameter on the stabilization problems and, as an advantage over the existing literature, there is no need to know the bounds of the time-derivative of the parameter and such function does not need to be continuous. Convex conditions are also developed for the case when LPV polynomial continuous-time systems present input constraints. Hence, this work deals singly with three kinds of systems: • input-to-state stabilization for continuous-time varying systems with saturating actuators; • design of state-feedback controllers for continuous-time varying systems with state polynomial dependency. • design of state-feedback controllers for continuous-time varying systems with state polynomial dependency and input constraints. For all cases, the efficacy of the proposed methods is illustrated with numerical examples. Key-words: Saturating actuators. Filtered parameter. Input-to-state. Region of attraction. Sum of squares. Polynomial continuous-time varying systems.

Due to the increasing use of automation in industrial processes, critical load equipment, personal computers and electronically controlled devices in residential installations, there is currently a greater interest in relation to Power Quality (QEE) problems. An important aspect related to QEE is the voltage compliance of power system. That is, the product delivered within the limits specified by Organs regulatory agencies. Due to the problems caused by voltage disturbances, which can be mentioned, disconnection of sensitive equipment, damage from voltage swell, increased losses in transformers and low efficiency operations of electrical equipment, there is this concern with voltage compliance. This work aims to contribute to the studies of voltage sags and swells (VTCD), seeking to demonstrate the real impact they cause on industrial consumers, even with full compliance with the standards determined in norms and resolutions. Initially, the main national and international standards applicable to VTCD are presented, characterization of events and verification of impact on loads, analyzing their similarities and peculiarities. The study on the implantation of a semiconductor factory in Brazil, aims to evaluate the impacts of low power quality from the phase of studies of the electrical system to the final operation / production. Finally, a proposal for a more detailed assessment of VTCD impacts is presented, within the normative scope

Diffraction analysis of multiple obstacles.

MODELAGEM DO NERVO AUDITIVO HUMANO APLICADO AO DESENVOLVIMENTO DE DETECTORES DE RESPOSTAS EVOCADAS AUDITIVAS EM REGIME PERMANENTE

Nowadays, Microstrip Antennas are used a lot in radio and wireless communications, even at high frequencies, due to their small size, ease of integration with another elements, among other factors. However, they have small bandwidth and small gain and therefore their application is restricted. To these structures are applied radomes that aim to improve these limitations. Radomes are structures placed above antennas for protection purposes, however, several applications include the improvement of antenna characteristics, mainly with the use of periodic structures with metamaterial characteristics. Metamaterials are structures made with conductor materials that has dimensions and spacing much smaller than wavelength, behaving macroscopically as an equivalent medium as long as they are geometrically arranged periodically. Thus, modifications in the structures of metamaterials can modify the constitutive characteristics of these media and thus provide positive or negative electrical permittivity, magnetic permeability and refractive index values. In this work, square Split Ring Resonators (SRR) and Thin Wires (TW) are used to behave as metamaterial cells and are used on radomes of microstrip antennas. There are used several layers of radomes designed with these cells above the antenna. The distance between cells and between each layer are two principal points on the radome design. The obtained results for positive permittivity and permeability, both negative and only permeability negative are compared. In this way, reviews are presented on microstrip antennas, metamaterials. The effects of radome with metamaterial characteristics on antenna gain and bandwidth are shown. The proposed structure reach a gain of 11,27 dBi and 1 GHz of bandwidth and were simulated by means of CST Microwave Studio software.

This work addresses the problem of stability analysis and state feedback control for discretetime uncertain periodic systems. The proposed synthesis and analysis conditions are developed using techniques derived from Lyapunov theory in conjunction with Linear Matrix Inequalities. First, the conditions for robust stability analysis and robust H2 analysis are presented using two distinct types of structured Lyapunov functions - higher order shifted state Lyapunov function and Lyapunov function considering non-monotonic terms. The efficiency of the proposed methods, whose goal is to reduce the conservatism of the solutions is explored through numerical examples taken from the literature. Secondly, techniques are developed regarding observer design for estimated state feedback control. These conditions are formulated considering the H2 performance criterion. Numerical examples illustrate the effectiveness of the proposed method.

APLICAÇÃO DE TÉCNICAS METAHEURÍSTICAS NO BALANCEAMENTO DE BANCO DE CAPACITORES

System identification consists on mathematically modeling a system in order to reproduce its most important features. In this work, a bi-objective estimator was used for process identification. The bi-objective estimator adds useful information to the estimation process. This estimation process implementation occurs in a four steps procedure: representation choice, framework detection, parameters estimation and model validation. The bi-objective estimation solution achievement involves high computational cost, what motivates this cost optimization interest. The objective of this work is to develop a technique that can reduce the estimation solution time. Two estimations technique came out as a result of this study: parallel bi-objective and accelerated biobjective techniques; both estimate parameters in shorter time than the conventional way. For both, simulations using real systems were performed to verify the efficiency