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In this work, a novel methodology for tuning fractional order controller, so-called fractional order pole placement (FOPP) is proposed. The proposed methodology extends classical (integer order) pole placement technique, using commensurable transfer functions for representing fractional order controllers and placing the fractional dominant poles within an extended stability region based on three terms fractional transfer functions. The designed fractional order controller can be digitally implemented by using the Oustaloup integer approximation of the fractional order dynamics with Hankel model reduction. The proposed FOPP is used to design fractional order controllers for a DC/DC buck converter. The experimental tests include comparisons between the proposed FOPP and other tuning methodologies for integer and fractional order controllers for the DC/DC buck converter that is subject to load, parametric, and load variations. Integral indices are computed to aid the assessment of the control strategies with respect to the robustness, performance specification compliance, and control effort. The results show that the proposed method outperforms the other approaches when occurs the variations.

Transmission lines’ monitoring systems are hybrid-dynamical structures produce a large amount of data that renders faults diagnosis difficult. Moreover, multiple faults of unknown nature can occur simultaneously impeding their discrimination. In addition, the feature extraction step constitutes an inherent limitation to the diagnosis of multiple faults. Indeed, a feature extraction algorithm avoiding any masking effect among between different multiple faults is hard to devise. This paper proposes a methodology dedicated to the diagnosis of multiples faults in transmission lines using both and experimental and calculated Leakage Current (LC) signals’ harmonics as residuals. Measured data from the real transmission line was used to modelling normal operating mode. Besides, different scenarios, including insulator chains contamination with different types and concentrations of pollutants were modeled by equivalents circuits to generate a multiple faults scenario. LCs from deteriorated insulators were inserted in the transmission line normal operating mode to implement a faulty operating conditions model. Qualitative trend analysis (QTA) was used to generate primitives and by exploiting the leakage current difference between normal and faulty operating conditions to define a features extraction algorithm for the diagnosis of specific fault modes. A Naive Bayes classifier was designed in order to identify the most prominent fault in a multiple faults scenario by means of LC data. The methodology manages to split multiple faults into single faults and reaches a classification accuracy for multiple faults of 95%.

This paper presents the development of an environmental measurement technology prototype based on Internet of Things (IoT) for intelligent monitoring of environmental variables called PLACOT2AM. The system performs all the functions of an Environmental Monitoring System and has the task of analyzing behavior in environments by an intelligent agent, which processes the patterns related to environmental variables of temperature and relative humidity. The sensor hardware is composed of a computational embedded unit with wireless communication interfaces with the Internet of Things. The analysis of thermal comfort is made in this study and the results are presented.

This paper shows the design and tests of an LPV power system stabilizer aimed at improving the damping of electromechanical oscillations in power systems. In order to capture the dynamic model for control design, LPV models were estimated from experimental data. The generator active and reactive powers were used as scheduling parameters. The control problem is formulated as a parameterized linear matrix inequality, which the positivity condition is relaxed through a sum-of-squares decomposition. The controller ensures stability and H ∞ performance for a set of operating conditions. Field tests were carried out on a 10-kVA machine and on a 350-MVA hydroelectric generator.

Setting the building construction duration for vertical residential works is made still in the study phase of economic and financial feasibility of the project and, in most cases, in an empirical way, increasing the uncertainties and the risks to fulfill the set deadline. However, there are computational intelligence tools that can contribute to reduce the degree of uncertainty. This study aimed to investigate the use of a hybrid system to estimate the deadline for vertical residential building works from design and production characteristics using factorial analysis and Fuzzy Systems. To this end, we used information of a database from the SEURB and in some buildings construction companies in Belém, a city located in the State of Pará, northern of Brazil. For the training and construction of the Fuzzy Forecast Model, data from 71 projects were used and 16 others residential buildings were used for its validation. The results showed a significant level of assertiveness, with 75% accuracy considering a range, whose upper and lower limits were calculated from MAPE and MASE. The model presented a prediction performance superior to other models already consecrated in the literature. Resumo A definição do prazo de execução de obras residenciais verticais ocorre ainda na fase de estudo de viabilidade econômica e financeira do empreendimento e, na maioria das vezes, de forma empírica, aumentando as incertezas e os riscos para o cumprimento do prazo estabelecido. No entanto, existem ferramentas de inteligência computacional que podem contribuir para a redução do grau de incerteza. Este trabalho tem como objetivo investigar o uso de um sistema híbrido para estimar o prazo de construção de obras verticais residenciais, a partir de características do projeto e produção utilizando análise fatorial e Sistemas Fuzzy. Para isso, utilizou-se de informações de um banco de dados oriundos da SEURB de Belém, no estado do Pará e empresas construtoras no município de Belém, cidade localizada no norte do Brasil. Para a construção e treinamento do Modelo de Previsão Fuzzy foram utilizados dados de 71 empreendimentos, e para a fase de validação foram utilizados 16 outras obras de edificações. Os resultados obtidos apresentaram nível significativo de assertividade, com acurácia igual a 75% considerando um intervalo cujos limites (superior e inferior) foram calculados a partir do MAPE e MASE. O modelo apresentou desempenho de predição superior a outros modelos já consagrados na literatura.

Automatic routines for Fault Detection and Diagnosis (FDD) are very important in industrial monitoring systems. However, false alarms potentially occur. High false alarm rates may lead to outages and consequent losses in the production process. To address such problem, a new FDD strategy based on type-2 fuzzy systems is proposed herein to minimize the false alarm rate. By applying system identification techniques, parametric models are estimated in order to represent the operation of the system under several levels of fault severity. The test system is a detailed dynamic nonlinear model of induction motor drive. The faults considered were partial short-circuit in stator winding coils. A performance comparison was made by implementing the monitoring system with both a type-2 fuzzy system interval and a type-1 fuzzy system. The results obtained thereby showed the improved performance and robustness of type-2 fuzzy system-based monitoring system, which outdoes the performance obtained by a type-1 fuzzy system. Furthermore, the performance of the proposed type-2 fuzzy system-based monitoring system may be further improved by using a Genetic Algorithm for tuning the parameters of the fuzzy type-2 system.

In this paper, a Fractional Order Power System controller (FOPSS) is designed, and its performance and robustness are experimentally evaluated by tests in a 10 kVA laboratory scale power system. The FOPSS design methodology is based on the tuning of an additional design variable, namely the fractional order of the controller transfer function. This design variable is tuned aiming to obtain a tradeoff between satisfactory damping of dominant oscillating mode and improved closed-loop system robustness. For controller synthesis, transfer function models were estimated from data collected at selected operating points and subsequently applied for the controller design and for obtaining upper bounds estimates on the operating-point depends on plant uncertainties. The experimental results show that the FOPPS was able to obtain a robust performance for the considered set of the power system operating conditions.

In this paper, we present a low-cost, stand-alone sensory platform developed for in situ monitoring of environmental parameters, for use in the Amazon region in the north of Brazil. The mission of the platform is to perform monitoring and identification of overirradiance (solar irradiance > 1000 W/m2) and extreme overirradiance events (solar irradiance > 1300 W/m2) using a photovoltaic based irradiance sensor. The sensory platform was built using the ESP8266 microcontroller, an open embedded computer capable of Wi-Fi communication using the IEEE 802.11 standard, and small photovoltaic modules, air temperature, atmospheric pressure, voltage, and current sensors, enabling the development of a low-cost system (€70/R$350.00 BRL). Calibration and tests were conducted at the Federal University of Pará (UFPA), Belém campus, Pará, where the platform measured an extreme overirradiance of 1321 W/m2 at a low-latitude (1 °S) and low altitude (7 m above sea level).

Smart grids raised a great demand for special services and automatic control, particularly to load balance on low-voltage consumers grid, which stands out for ensuring stable states between phases in the secondary grid. This paper presents a new system design approach in order to automate the phase load balancing process, as an alternative system control to urban microgrids. The control system is based on combined algorithms that process the load unbalances identification in the phases of the grid, the load consumption classification and forecast of the consumer units, and the optimization of the selection consumption units to be switched in feeders. The system design validation is performed used a Timed Hierarchical Petri net. The result produces an efficient automated workflow of tasks to the phase load balancing, based on automatic load switching and ensure the load stability in the grid and minimize the load average unbalance.

This research presents an IN SITU sensory platform developed through the integration of air temperature and relative humidity sensors on an ecosystem in order to obtain some thermal characteristic of the rural environments. This sensory platform contains an expert system to detect the behaviors of environmental variables that result in risk or without risk alert to the thermal comfort for human and animal health. For this, the expert system analyses the environmental thermal conditions of the UFRA University, through temperature and humidity index (THI). The THI values estimated (processed) from data of temperature and relative humidity during the year 2012. Four intervals of THI were used to classify human health performance (THI 84: extremely hot), and two intervals to classify animal production (79 ⩽ THI ⩽ 84: dangerous and THI > 84: emergency). The Amazon is located in the equatorial region and has a warm and humid climate that the prevailing mode reveals an alternation of two seasons throughout the year, hot and humid summer and rainy winter. The results that the most critical period occurs between May and October, although it was observed in every day of every year, the THI values during the hottest hours of the day (15:00 pm) range between 75.9 and 86.3, where humans and animals can suffer some degree of thermal stress, affecting negatively both. Therefore, we consider this platform as a good solution for thermal monitoring, which is based on IN SITU measurement technologies for rural environments.

Segundo a literatura tecnica pertinente, a logica fuzzy (nebulosa) surgiu como necessidade de controlar sistemas que, no mundo real, sao complexos demais para se obter boa modelagem matematica. Alem disso, ao adentrarmos cada vez mais na era da informacao, o conhecimento humano torna-se muito importante. Neste sentido, precisa-se de uma logica de controle que imite o conhecimento humano de uma maneira sistematica e seja de facil aplicacao em sistemas reais. Pretende-se, neste artigo, fazer um projeto de controlador difuso (ou fuzzy) para garantir constância na frequencia de saida de um gerador (60Hz), acionado por uma turbina a vapor.

Este artigo apresenta um estudo experimental de técnicas de identificação paramétrica aplicadas à modelagem dinâmica de um servidor web Apache. Foi desenvolvido um arranjo experimental para simular variações de carga no servidor. O arranjo é composto por dois computadores PC, sendo um deles utilizado para executar o servidor Apache e o outro utilizado como um gerador de carga, solicitando requisições de serviço ao servidor Apache. Foram estimados modelos paramétricos auto-regressivos (AR) para diferentes pontos de operação e de condição de carga. Cada ponto de operação foi definido em termos dos valores médios para o parâmetro de entrada MaxClients (parâmetro utilizado para definir o número máximo de processos ativos) e a saída percentual de consumo de CPU (Central Processing Unit) do servidor Apache. Para cada ponto de operação foram coletadas 600 amostras, com um intervalo de amostragem de 5 segundos. Metade do conjunto de amostras coletadas em cada ponto de operação foi utilizada para estimação do modelo, enquanto que a outra metade foi utilizada para validação. Um estudo da ordem mais adequada do modelo mostrou que, para um ponto de operação com valor reduzido de MaxClients, um modelo AR de 7ª ordem pode ser satisfatório. Para valores mais elevados de MaxClients, os resultados mostraram que são necessários modelos de ordem mais elevada, devido às não-linearidades inerentes ao sistema.

Understanding the uncertainty inherent in the analysis of diesel fuel consumption and its impact on the generation of electricity is an important topic for planning the expansion of isolated thermoelectric systems in the state of Amazonas. In light of this, a decision support system has been developed to forecast the cost of electricity production using non-stationary data by integrating the methodology of time series models with fuzzy systems and optimization tools. The method presented herein combines the potential of the Autoregressive Integrated Moving Average (ARIMA) and the Seasonal ARIMA (SARIMA) models, such as the forecasting tool, with the advantages of fuzzy set theory to compensate for the uncertainties and errors encountered in the observed data, which would degrade the validity of forecasted values. The results show that incorporation of the α-cut concept facilitated the evaluation of risks while allowing simultaneous consideration of intervals for the unitary cost of energy production. This provides the analyst with the ability to make decisions using various predicted intervals with different membership values instead of the common practice of simply using the specific costs.

This paper examines some problems encountered in the expansion of isolated electrical systems (IES) in the Amazon region, more precisely, the thermoelectric systems used in that region. Supposing a certain degree of uncertainty in energy consumption, we evaluate the expansion of thermoelectric power from firewood and diesel fuel, together with variations for costs, CO2 emissions, and number of direct jobs (NDJ) generated with the use of these technologies. The analysis is accomplished by using fuzzy multi-objective mathematical programming, and interpreting each objective function both by itself and in combination with the others, through a fuzzy multi-objective parametrization. The scenarios are defined by the energy consumption percentage increase, limited to be below some admissible maximum value, while still considering variations in the installed power. The costs, CO2 emission, and the NDJ generated are analyzed and compared with the largest values obtained with the model of crisp mathematical programming, used for the original configuration. Finally, in Section 4, we present the results and respective analyses for the finished simulation.

Este trabalho propõe uma estratégia fuzzy, do tipo Rede de Controladores Locais, aplicável à melhoria da estabilidade dinâmica em sistemas elétricos de potência, visando compensar possíveis perdas de sintonia devido à ocorrência de variações nas condições operacionais da planta. A adaptação dos ganhos do controlador fuzzy é efetuada on-line, interpolando-se os ganhos de um conjunto finito de controladores locais fixos. Ao ocorrer variações nas condições operacionais da planta, os ganhos da lei de controle são ajustados automaticamente de modo a manter satisfatório o desempenho do sistema de controle. O desempenho do controle foi avaliado através de estudos de simulação, utilizando-se um modelo dinâmico não-linear, do tipo máquina barra infinita. Os resultados mostram que o emprego da estratégia proposta permite obter melhorias no desempenho dinâmico do sistema.

INTRODUCTION: Electromagnetic interference caused by electric power lines adversely affects the signals of electronic instruments, especially those with low amplitude levels. This type of interference is known as common-mode interference. There are many methods and architectures used to minimize the influence of this kind of interference on electronic instruments, the most common of which is the use of band-reject filters. This paper presents the analysis, development, prototype and test of a new reconfigurable filter architecture for biomedical instruments, aiming to reduce the common-mode interference and preserve the useful signal components in the same frequency range as that of the noise, using the technique of dynamic impedance balancing. METHODS: The circuit blocks were mathematically modeled and the overall closed-loop transfer function was derived. Then the project was described and simulated in the VHDL_AMS language and also in an electronics simulation software, using discrete component blocks, with and without feedback. After theoretical analysis and simulation results, a prototype circuit was built and tested using as input a signal obtained from ECG electrodes. RESULTS: The results from the experimental circuit matched those from simulation: a 97.6% noise reduction was obtained in simulations using a sinusoidal signal, and an 86.66% reduction was achieved using ECG electrodes in experimental tests. In both cases, the useful signal was preserved. CONCLUSION: The method and its architecture can be applied to attenuate interferences which occur in the same frequency band as that of the useful signal components, while preserving these signals.

© 2013 Gonzalez Nogueira et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Design and Field Tests of a Digital Control System to Damping Electromechanical Oscillations Between Large Diesel Generators

Este trabalho apresenta o desenvolvimento e resultados de testes de campo de um estabilizador de sistemas de potência (ESP) digital, destinado ao amortecimento de oscilações eletromecânicas em sistemas interligados. Os testes experimentais foram efetuados em uma das unidades hidrogeradoras, de 350 MVA, da UHE de Tucuruí. A lei de controle amortecedor do ESP digital foi embarcada em um sistema de hardware baseado em um controlador digital de sinais (DSPIC 30f5011). A estrutura da lei de controle é na forma canónica RST, de tempo discreto, sendo os parâmetros do controlador calculados através da técnica de deslocamento radial de pólos. Para fins de projeto, a dinâmica da planta, no ponto de operação considerado, foi representada por um modelo paramétrico, o qual foi estimado a partir de dados medidos em campo. Os resultados experimentais mostraram um excelente desempenho do ESP digital no amortecimento de um dos modos eletromecânicos observável na UHE de Tucuruí. This paper presents the development and results of field tests of a digital power system stabilizer (PSS), designed for the damping of electromechanical oscillations in interconnected systems. Experimental tests were performed in a 350 MVA hydrogenerator unit, of the Tucurui Power Plant. The PSS damper control law was embedded in a digital hardware system based on a digital signal controller (DSPIC 30f5011). The structure of the control law is in discrete time RST canonical form, and the controller parameters were calculated using the pole shifting technique. For purposes of the controller design, the dynamics of the plant, in the considered operating point, was represented by a parametric model, which was estimated from data measured in the field. The experimental results showed an excellent performance of the damping of electromechanical modes observable UHE Tucurui by digital PSS.

Electromagnetic interference, caused by the electric power line, affects the signals of electronic instruments, specifically those with low levels of amplitude. This type of signal is known as Common Mode Interference. There are many methods and architectures used to minimize or eliminate the influence of these interferences in electronic instrumentation, the most common is the use of band reject filters to eliminate them. With this objective, we present the analysis, prototyping, developing and testing of a new architecture reconfigurable filter with application in biomedical instrumentation, applied to the reduction of interference in common mode and conservation of components of the useful signal in the same range of noise, by the principle of balancing impedance dynamic using the hardware description software and simulation electronics software. The methodology was tested using a sinusoidal signal in the same standard frequency of an electrocardiogram signal in the same frequency interference (50/60 Hz). Excellent results were obtained in simulation with noise reduction of approximately 97%, while the results of experimental tests showed around 50% reduction. In both cases, the useful signal was preserved, confirming the efficiency of the proposed architecture. The method can be applied to eliminate the interference, which are in the same band the of the useful signal components.

O design de sistemas modernos de energia aumentou em complexidade devido às suas novas características: sustentável, distribuído, heterogêneo, escalável, colaborativo, sempre preservando o alto desempenho. Novas abordagens, métodos, conceitos e ferramentas surgiram para caracterizar, compreender e especificar sistemas híbridos de produção/consumo de energia totalmente adaptados ao ambiente de entorno onde deveriam funcionar. Este trabalho apresenta uma proposta de método sistêmico para o desenvolvimento de requisitos aplicado a Smart Grid (SG), baseado em uma abordagem de serviço. Portanto, privilegia o acoplamento entre o sistema, o usuário e o domínio. A proposta enfatiza formalização, já na especificação de requisitos para redes distribuídas Smart Grid usando análise de workflow baseadas em Redes de Petri. A rede é sintetizada de um processo de Engenharia de Requisitos Orientada a Objetivos (GORE), baseada em diagramas semi-formais KAOS (Aquisição de Conhecimento de Especificações Objetivas), capaz de superar o dilema da abordagem funcional/ não-funcional, pelo menos na fase preliminar. O ciclo de requisitos consiste em eliciação, modelagem, análise, modelagem formal e verificação e pode ser iterado por refinamentos. O método foi aplicado a um estudo de caso real, baseado na evolução de uma microgrid instalada em uma comunidade isolada na floresta amazônica. The modern design of energy systems grew in complexity due to emerging characteristics as sustainability, distribution, heterogeneity, scalability, collaboration while preserving high performance. New approaches, methods, concepts, and tools appeared to characterize, understand and specify hybrid production/consumption grids wholly adapted to the application environment. This work presents a proposal for a service-oriented systemic method to develop requirements that could be applied to Smart Grids (SG). Therefore, the method prioritizes the coupling between system, users, and domain. The proposal also emphasizes a formal approach, used in the early phase and applied to a distributed network of SGs, based on workflow analysis and Petri Nets (PN). A PN schema is synthesized after a Requirements Engineering process that is also goal-oriented (GORE), using semi-formal KAOS (Knowledge Acquisition on Objective Specifications). The schema can obliviate the dilemma functional/non-functional, at least in the first steps. The requirements cycle proposed comprised the steps: elicitation, modeling, analysis, formal modeling, and verification and was applied to a case study of an SG in an isolated community in the Amazon forest.