Estimação de Fasores para Proteção de Sistemas Elétricos Baseada em Mínimos Quadrados e Morfologia Matemática

This work proposes a new technique for phasor estimation applied in microprocessor numerical relays for distance protection of transmission lines, based on the recursive least squares method and called least squares modified random walking. The phasor estimation methods have compromised their performance, mainly due to the DC exponential decaying component present in fault currents. In order to reduce the influence of the DC component, a Morphological Filter (FM) was added to the method of least squares and previously applied to the process of phasor estimation. The presented method is implemented in MATLABr and its performance is compared to one-cycle Fourier technique and conventional phasor estimation, which was also based on least squares algorithm. The methods based on least squares technique used for comparison with the proposed method were: forgetting factor recursive, covariance resetting and random walking. The techniques performance analysis were carried out by means of signals synthetic and signals provided of simulations on the Alternative Transient Program (ATP). When compared to other phasor estimation methods, the proposed method showed satisfactory results, when it comes to the estimation speed, the steady state oscillation and the overshoot. Then, the presented method performance was analyzed by means of variations in the fault parameters (resistance, distance, angle of incidence and type of fault). Through this study, the results did not showed significant variations in method performance. Besides, the apparent impedance trajectory and estimated distance of the fault were analysed, and the presented method showed better results in comparison to one-cycle Fourier algorithm

Análise comparativa e teste empírico da validade dos modelos CAPM tradicional e condicional: o caso das ações da Petrobrás

ALVES, Janaína da Silva. Análise comparativa e teste empírico da validade dos modelos CAPM tradicional e condicional: o caso das ações da Petrobrás. Revista Ciências Administrativas, Fotaleza, v. 13, n. 1, p.147-157, ago. 2007.

Determinantes da Estrutura de Capital de Companhias Abertas Brasileiras Não-Financeiras: Um Estudo Empírico com Dados em Painel

When a company desires to invest in a project, it must obtain resources needed to make the investment. The alternatives are using firm s internal resources or obtain external resources through contracts of debt and issuance of shares. Decisions involving the composition of internal resources, debt and shares in the total resources used to finance the activities of a company related to the choice of its capital structure. Although there are studies in the area of finance on the debt determinants of firms, the issue of capital structure is still controversial. This work sought to identify the predominant factors that determine the capital structure of Brazilian share capital, non-financial firms. This work was used a quantitative approach, with application of the statistical technique of multiple linear regression on data in panel. Estimates were made by the method of ordinary least squares with model of fixed effects. About 116 companies were selected to participate in this research. The period considered is from 2003 to 2007. The variables and hypotheses tested in this study were built based on theories of capital structure and in empirical researches. Results indicate that the variables, such as risk, size, and composition of assets and firms growth influence their indebtedness. The profitability variable was not relevant to the composition of indebtedness of the companies analyzed. However, analyzing only the long-term debt, comes to the conclusion that the relevant variables are the size of firms and, especially, the composition of its assets (tangibility).This sense, the smaller the size of the undertaking or the greater the representation of fixed assets in total assets, the greater its propensity to long-term debt. Furthermore, this research could not identify a predominant theory to explain the capital structure of Brazilian

Crenças normativas e comportamentais e suas influências na intenção de adoção de um sistema de informação: um estudo na área de compras da UFPA

The study aims to identify the factors that influence the behavior intention to adopt an academic Information System (SIE), in an environment of mandatory use, applied in the procurement process at the Federal University of Pará (UFPA). For this, it was used a model of innovation adoption and technology acceptance (TAM), focused in attitudes and intentions regarding the behavior intention. The research was conducted a quantitative survey, through survey in a sample of 96 administrative staff of the researched institution. For data analysis, it was used structural equation modeling (SEM), using the partial least squares method (Partial Least Square PLS-PM). As to results, the constructs attitude and subjective norms were confirmed as strong predictors of behavioral intention in a pre-adoption stage. Despite the use of SIE is required, the perceived voluntariness also predicts the behavior intention. Regarding attitude, classical variables of TAM, like as ease of use and perceived usefulness, appear as the main influence of attitude towards the system. It is hoped that the results of this study may provide subsidies for more efficient management of the process of implementing systems and information technologies, particularly in public universities

Aceitação e uso de ambiente virtual de aprendizagem no contexto de um curso de capacitação para servidores públicos

This study aimed to examine how students perceives the factors that may influence them to attend a training course offered in the distance virtual learning environment (VLE) of the National School of Public Administration (ENAP). Thus, as theoretical basis it was used the Unified Theory of Acceptance and Use of Technology (UTAUT), the result of an integration of eight previous models which aimed to explain the same phenomenon (acceptance/use of information technology). The research approach was a quantitative and qualitative. To achieve the study objectives were made five semi-structured interviews and an online questionnaire (websurvey) in a valid sample of 101 public employees scattered throughout the country. The technique used to the analysis of quantitative data was the structural equation modeling (SEM), by the method of Partial Least Square Path Modeling (PLS-PM). To qualitative data was the thematic content analysis. Among the results, it was found that, in the context of public service, the degree whose the individual believes that the use of an AVA will help its performance at work (performance expectancy) is a factor to its intended use and also influence its use. Among the results, it was found that the belief which the public employee has in the use of a VLE as a way to improve the performance of his work (performance expectation) was determinant for its intended use that, in turn, influenced their use. It was confirmed that, under the voluntary use of technology, the general opinion of the student s social circle (social influence) has no effect on their intention to use the VLE. The effort expectancy and facilitating conditions were not directly related to the intended use and use, respectively. However, emerged from the students speeches that the opinions of their coworkers, the ease of manipulate the VLE, the flexibility of time and place of the distance learning program and the presence of a tutor are important to their intentions to do a distance learning program. With the results, it is expected that the managers of the distance learning program of ENAP turn their efforts to reduce the impact of the causes of non-use by those unwilling to adopt voluntarily the e-learning, and enhance the potentialities of distance learning for those who are already users

O argumento de inclusão enquanto política de acesso à universidade pública

There are a great number of evidences showing that education is extremely important in many economic and social dimensions. In Brazil, education is a right guaranteed by the Federal Constitution; however, in the Brazilian legislation the right to the three stages of basic education: Kindergarten, Elementary and High School is better promoted and supported than the right to education at College level. According to educational census data (INEP, 2009), 78% of all enrolments in College education are in private schools, while the reverse is found in High School: 84% of all matriculations are in public schools, which shows a contradiction in the admission into the universities. The Brazilian scenario presents that public universities receive mostly students who performed better and were prepared in elementary and high school education in private schools, while private universities attend students who received their basic education in public schools, which are characterized as low quality. These facts have led researchers to raise the possible determinants of student performance on standardized tests, such as the Brazilian Vestibular exam, to guide the development of policies aimed at equal access to College education. Seeking inspiration in North American models of affirmative action policies, some Brazilian public universities have suggested rate policies to enable and facilitate the entry of "minorities" (blacks, pardos1, natives, people of low income and public school students) to free College education. At the Federal University of the state Rio Grande do Norte (UFRN), the first incentives for candidates from public schools emerged in 2006, being improved and widespread during the last 7 years. This study aimed to analyse and discuss the Argument of Inclution (AI) - the affirmative action policy that provides additional scoring for students from public schools. From an extensive database, the Ordinary Least Squares (OLS) technique was used as well as a Quantile Regression considering as control the variables of personal, socioeconomic and educational characteristics of the candidates from the Brazilian Vestibular exam 2010 of the Federal University of the state Rio Grande do Norte (UFRN). The results demonstrate the importance of this incentive system, besides the magnitude of other variables

Identificação fuzzy-multimodelos para sistemas não lineares

This paper presents a new multi-model technique of dentification in ANFIS for nonlinear systems. In this technique, the structure used is of the fuzzy Takagi-Sugeno of which the consequences are local linear models that represent the system of different points of operation and the precursors are membership functions whose adjustments are realized by the learning phase of the neuro-fuzzy ANFIS technique. The models that represent the system at different points of the operation can be found with linearization techniques like, for example, the Least Squares method that is robust against sounds and of simple application. The fuzzy system is responsible for informing the proportion of each model that should be utilized, using the membership functions. The membership functions can be adjusted by ANFIS with the use of neural network algorithms, like the back propagation error type, in such a way that the models found for each area are correctly interpolated and define an action of each model for possible entries into the system. In multi-models, the definition of action of models is known as metrics and, since this paper is based on ANFIS, it shall be denominated in ANFIS metrics. This way, ANFIS metrics is utilized to interpolate various models, composing a system to be identified. Differing from the traditional ANFIS, the created technique necessarily represents the system in various well defined regions by unaltered models whose pondered activation as per the membership functions. The selection of regions for the application of the Least Squares method is realized manually from the graphic analysis of the system behavior or from the physical characteristics of the plant. This selection serves as a base to initiate the linear model defining technique and generating the initial configuration of the membership functions. The experiments are conducted in a teaching tank, with multiple sections, designed and created to show the characteristics of the technique. The results from this tank illustrate the performance reached by the technique in task of identifying, utilizing configurations of ANFIS, comparing the developed technique with various models of simple metrics and comparing with the NNARX technique, also adapted to identification

Um algoritmo para estimação de estado em alimentadores de distribuição de energia elétrica com base no método da soma de potências

Most algorithms for state estimation based on the classical model are just adequate for use in transmission networks. Few algorithms were developed specifically for distribution systems, probably because of the little amount of data available in real time. Most overhead feeders possess just current and voltage measurements at the middle voltage bus-bar at the substation. In this way, classical algorithms are of difficult implementation, even considering off-line acquired data as pseudo-measurements. However, the necessity of automating the operation of distribution networks, mainly in regard to the selectivity of protection systems, as well to implement possibilities of load transfer maneuvers, is changing the network planning policy. In this way, some equipments incorporating telemetry and command modules have been installed in order to improve operational features, and so increasing the amount of measurement data available in real-time in the System Operation Center (SOC). This encourages the development of a state estimator model, involving real-time information and pseudo-measurements of loads, that are built from typical power factors and utilization factors (demand factors) of distribution transformers. This work reports about the development of a new state estimation method, specific for radial distribution systems. The main algorithm of the method is based on the power summation load flow. The estimation is carried out piecewise, section by section of the feeder, going from the substation to the terminal nodes. For each section, a measurement model is built, resulting in a nonlinear overdetermined equations set, whose solution is achieved by the Gaussian normal equation. The estimated variables of a section are used as pseudo-measurements for the next section. In general, a measurement set for a generic section consists of pseudo-measurements of power flows and nodal voltages obtained from the previous section or measurements in real-time, if they exist -, besides pseudomeasurements of injected powers for the power summations, whose functions are the load flow equations, assuming that the network can be represented by its single-phase equivalent. The great advantage of the algorithm is its simplicity and low computational effort. Moreover, the algorithm is very efficient, in regard to the accuracy of the estimated values. Besides the power summation state estimator, this work shows how other algorithms could be adapted to provide state estimation of middle voltage substations and networks, namely Schweppes method and an algorithm based on current proportionality, that is usually adopted for network planning tasks. Both estimators were implemented not only as alternatives for the proposed method, but also looking for getting results that give support for its validation. Once in most cases no power measurement is performed at beginning of the feeder and this is required for implementing the power summation estimations method, a new algorithm for estimating the network variables at the middle voltage bus-bar was also developed

Um estimador de estado trifásico para sistemas de distribuição de energia elétrica com base no método da soma de potências

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Identificação em tempo real de modelo dinâmico de robô móvel com acionamento diferencial e zona morta

Several mobile robots show non-linear behavior, mainly due friction phenomena between the mechanical parts of the robot or between the robot and the ground. Linear models are efficient in some cases, but it is necessary take the robot non-linearity in consideration when precise displacement and positioning are desired. In this work a parametric model identification procedure for a mobile robot with differential drive that considers the dead-zone in the robot actuators is proposed. The method consists in dividing the system into Hammerstein systems and then uses the key-term separation principle to present the input-output relations which shows the parameters from both linear and non-linear blocks. The parameters are then simultaneously estimated through a recursive least squares algorithm. The results shows that is possible to identify the dead-zone thresholds together with the linear parameters

Metodologia para re-sintonia de controladores PID industriais

The present work has as objective to present a method of project and implementation of controllers PID, based on industrial instrumentation. An automatic system of auto-tunning of controllers PID will be presented, for systems of first and second order. The software presented in this work is applied in controlled plants by PID controllers implemented in a CLP. Software is applied to make the auto-tunning of the parameters of controller PID of plants that need this tunning. Software presents two stages, the first one is the stage of identification of the system using the least square recursive algorithm and the second is the stage of project of the parameters of controller PID using the root locus algorithm. An important fact of this work is the use of industrial instrumentation for the accomplishment of the experiments. The experiments had been carried through in controlled real plants for controllers PID implemented in the CLP. Thus has not only one resulted obtained with theoreticians experiments made with computational programs, and yes resulted obtained of real systems. The experiments had shown good results gotten with developed software

Uma proposta de um controlador adaptativo por posicionamento de pólos e estrutura variável

There are two main approaches for using in adaptive controllers. One is the so-called model reference adaptive control (MRAC), and the other is the so-called adaptive pole placement control (APPC). In MRAC, a reference model is chosen to generate the desired trajectory that the plant output has to follow, and it can require cancellation of the plant zeros. Due to its flexibility in choosing the controller design methodology (state feedback, compensator design, linear quadratic, etc.) and the adaptive law (least squares, gradient, etc.), the APPC is the most general type of adaptive control. Traditionally, it has been developed in an indirect approach and, as an advantage, it may be applied to non-minimum phase plants, because do not involve plant zero-pole cancellations. The integration to variable structure systems allows to aggregate fast transient and robustness to parametric uncertainties and disturbances, as well. In this work, a variable structure adaptive pole placement control (VS-APPC) is proposed. Therefore, new switching laws are proposed, instead of using the traditional integral adaptive laws. Additionally, simulation results for an unstable first order system and simulation and practical results for a three-phase induction motor are shown

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Modelagem e controle adaptativo de uma planta didática de nível com instrumentação industrial

The control, automation and optimization areas help to improve the processes used by industry. They contribute to a fast production line, improving the products quality and reducing the manufacturing costs. Didatic plants are good tools for research in these areas, providing a direct contact with some industrial equipaments. Given these capabilities, the main goal of this work is to model and control a didactic plant, which is a level and flow process control system with an industrial instrumentation. With a model it is possible to build a simulator for the plant that allows studies about its behaviour, without any of the real processes operational costs, like experiments with controllers. They can be tested several times before its application in a real process. Among the several types of controllers, it was used adaptive controllers, mainly the Direct Self-Tuning Regulators (DSTR) with Integral Action and the Gain Scheduling (GS). The DSTR was based on Pole-Placement design and use the Recursive Least Square to calculate the controller parameters. The characteristics of an adaptive system was very worth to guarantee a good performance when the controller was applied to the plant

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers