Engenharia Elétrica

This article uses a Kalman Filter as controller design method. It was done simulation using the Kalman Filter and another state observer controller, for comparing purposes. Both controllers were used for controlling the temperature
in a neonate unit care. For tuning the State Space Controller was used a Pole Placement method. According to measured
disturbances at plant, it was established the design  parameters for the Kalman Filter.

This article proposes a dead-time compensator using CDM (Coefficient Diagram Method) design method for controlling humidity in a neonate intensive care unit. It was used a Modified Smith Predictor (MSP) structure for deadtime
compensation. Also was done a stability and robustness analysis according to the CDM Diagram. It was done
simulations and experiments and is shown the results using the proposed controller. It was done still a simulation for
showing results of modelling errors.

This article proposes using a GPC control method, by adjustment of a control signal weighting factor (λ) changing in a band according a sigmoid function. This method was implemented by computational simulation and  experimentally in a neonatal incubator controlling temperature. The variable weighting factor allows the reduction on overshoot as the rising time, resulting in a faster response. A comparative study for system response with and without weighting factor was done to prove the
method efficiency.

O presente artigo propõe o uso do método de controle GPC com o ajuste do fator de ponderação do sinal de controle (λ) variando dentro de uma faixa segundo uma função do tipo sigmóide. O método foi implementado através de simulação computacional e experimentalmente em uma incubadora neonatal para o controle de temperatura. A variação no fator de ponderação permite que se possa reduzir o valor do sobressinal bem como o valor do tempo de subida, deixando a resposta mais rápida. É feito um estudo comparativo da resposta do sistema com um fator de ponderação fixo e variável de modo a se comprovar a eficácia do método. Foram realizados ensaios também com um controlador DMC (Dynamic Matrix Control) de modo a se fazerem comparações entre os resultados com as duas técnicas de controle.

This work proposes using a state observer structure and a Kalman filter for controlling a dead time system. The practical implementation for the proposed structure is done in a thermal system, corresponding to a temperature control of a neonate intensive care unit. The results obtained are compared to different controlers, as state space controller and a Smith predictor.

This article goal is to show a trajectory predictive control of a mobile robot using DMC method whose identification is done by neural network. This method was proposed due to changes on parameters occurring, being this a problem controlling the trajectories of this kind of robot.

This article goal is implementation of a mobile robot  trajectory system control using predictive control using neural
network. The trajectory is programmed and sent to mobile robot via radio link. The trajectory control is obtained on the speed control of motors, giving linear and angular movements, for this, the computer gets the running time for each motor. The complete system use two neural-networks: One of these is used for controlling the right and the other for left motor. Each individual controller is a neural network with three layers and the control horizon used was 5. The robot was implemented with three micro controllers
PIC 16F877A. The communication between these was did using an I2C network. The main controller is centralized
and was running on a PC, whose software was implemented in MATLAB. The software on micro controllers did the control
action and data collection. The micro controllers software was implemented in C language.

This work proposes using a state observer structure and a Kalman filter for controlling a dead time system. The practical implementation for the proposed structure is done in a thermal system, corresponding to a temperature control of a neonate intensive care unit. The results obtained are compared to different controlers, as state space controller and a Smith predictor.

The objective of this work is to create a system for separating types of pieces for didactic purposes. An artificial vision system applied to a manipulator was used to perform this task of classifying and separating the pieces, through the use of digital image processing. The vision system uses a camera attached to the robot's end-effector, whose objective is to identify the area, perimeter and position of the centroid of the pieces to be separated. The separation of objects is performed between two classes: with round and non-round shapes. The tests were carried out with objects such as screws and nuts. After obtaining the positions of the objects to be separated by the vision system, some characteristics of these related to the reference system of the robot base are determined. Some difficulties were observed in the recognition of objects related to the colours and lighting conditions of the separation environment. To reduce these problems, black colour objects were used in or...

This article proposes using a GPC control method, by adjustment of a control signal weighting factor (λ) changing in a band according a sigmoid function. This method was implemented by computational simulation and experimentally in a neo natal incubator controlling temperature. The variable weighting factor allows the reduction on overshoot as the rising time, resulting in a faster response. A comparative study for system response with and without weighting factor was done to prove the method efficiency. It was done experiments using a DMC (Dynamic Matrix Control) controller also to compare results obtained by two control techniques.

This article goal is implementation of a mobile robot trajectory system control using predictive control using neural network. The trajectory is programmed and sent to mobile robot via radio link. The trajectory control is obtained on the speed control of motors, giving linear and angular movements, for this, the computer gets the running time for each motor. The complete system use two neural-networks: One of these is used for controlling the right and the other for left motor. Each individual controller is a neural network with three layers and the control horizon used was 5. The robot was implemented with three microcontrollers PIC 16F877A. The communication between these was did using an I2C network. The main controller is centralized and was running on a PC, whose software was implemented in MATLAB. The software on microcontrollers did the control action and data collection. The microcontrollers software was implemented in C language.

This paper addresses the topic of distributed generation with a focus point of common coupling protection of a microgrid to the distribution system. It describes the regulatory and normative aspects of access to Brazilian distribution system, as well as effects caused by the connection of distributed generation on the network. It also proposes the necessary settings to the protection relay to the point of common coupling and performs tests using a testing equipment of protection relays.

SPECT scanning with TI-20I and Tc-99m offers a unique, inexpensive functional imaging modality to combine with CT stereotactic craniotomy for grading resection of necrosis and/or tumour in patients treated with escalated doses of radiation (> 6000cGy) by either brachytherapy or radiosurgery. Thirty-two cases were analyzed, with a detailed description of the imaging and operative techniques.

Foi avaliada a composição da pele, do corpo sem extremidades, das extremidades corporais e a composição corporal total e estimadas as exigências líquidas de energia e proteína para ganho de peso da espécie Chinchilla lanigera. Foram utilizados 18 animais, tendo sido abatidos seis animais juvenis com 40 dias de idade e 12 animais adultos (seis machos e seis fêmeas) com 750 dias de idade. Foi feito um teste de comparação de médias para as composições das diferentes frações do corpo nas diferentes categorias animal. Foram ajustadas equações logarítmicas da quantidade corporal de proteína, gordura e energia, em função do logaritmo do peso corporal vazio. As exigências líquidas em proteína e energia para ganho de peso foram obtidas por derivação das equações de predição da composição corporal em proteína e energia. Foi verificada uma maior proporção (P<0,05) de extremidades corporais por parte dos animais juvenis em relação aos adultos. Entretanto, as proporções de pele e de corpo sem extremidades não diferiram (P>0,05) entre as categorias. As quantidades de matéria seca, proteína e gordura corporal, alteraram-se com o avanço da idade. Os animais juvenis apresentaram menor (P<0,05) percentual de matéria seca e extrato etéreo quando comparados com os adultos. As exigências líquidas de proteína decresceram, enquanto que as exigências energéticas se elevaram com o aumento da idade e peso dos animais.

Peptide sequence matching algorithms used for peptide identification by tandem mass spectrometry (MS/MS) enumerate theoretical peptides from the database, predict their fragment ions, and match them to the experimental MS/MS spectra. Here, we present an approach for scoring MS/MS identifications based on the high mass accuracy matching of precursor ions, the identification of a high intensity b1 fragment ion, and partial sequence tags from phenylthiocarbamoyl-derivatized peptides. This derivatization process boosts the b1 fragment ion signal, which turns it into a powerful feature for peptide identification. We demonstrate the effectiveness of our scoring system by implementing it on a computational tool called "HI-bone" and by identifying mass spectra of an Escherichia coli sample acquired on an Orbitrap Velos instrument using Higher-energy C-trap dissociation. Following this strategy, we identified 1614 peptide spectrum matches with a peptide false discovery rate (FDR) below 1%. These results were significantly higher than those from Mascot and SEQUEST using a similar FDR.

The ability to authenticate the feed given to animals from the animal products has become a major challenge for scientists, monitoring bodies and commercial entities alike. This study compared two methods based on the use of the visible reflectance spectrum of the fat to discriminate pasture-fed (P) from stall concentrate-fed (S) lamb carcasses. A total of 307 (143 P and 164 S) Limousine lambs were used over 2 years. Pasture-fed lambs grazed a permanent pasture that was maintained at a leafy, green vegetative stage, and offered ad libitum; they received no supplementation at pasture. Body weight of P lambs when turning out to pasture and at slaughter averaged 9.2 (standard deviation (s.d.) 2.21) kg and 33.2 (s.d. 2.89) kg, respectively. S lambs were fed indoors on an ad libitum diet of commercial concentrate and hay until slaughter at a mean body weight of 33.7 (s.d. 3.62) kg. The reflectance spectrum of perirenal and subcutaneous caudal fat was measured at slaughter and at 24 h post mortem. Plasma carotenoid concentration was measured at slaughter. In method 1, the fat reflectance spectrum data were used at wavelengths between 450 and 510 nm to calculate an index quantifying light absorption by carotenoid pigments. In method 2, a multivariate analysis was performed over the full set of fat reflectance data at wavelengths between 400 and 700 nm. Method 2 yielded a higher proportion of correctly classified lambs compared with method 1 (P , 0.05 to 0.001), except for measurements made at 24 h post mortem on perirenal fat for S lambs. The proportion of lambs correctly classified using method 2 was 87.4% and 92.9% for measurements made on perirenal and caudal fat at slaughter, and 93.9% and 91.0% for measurements made on perirenal and caudal fat 24 h post mortem. Plasma carotenoid concentrations were higher in P lambs than in S lambs (P , 0.001), which led to correct classification of 90.7% of the lambs.

Transient identification in nuclear power plants (NPP) is often a computational very hard task and may involve a great amount of human cognition. The early identification of unexpected departures from steady state behavior is an essential step for the operation, control and accident management in NPPs. The bases for the transient identification relay on the evidence that different system faults and anomalies lead to different pattern evolution in the involved process variables. During an abnormal event, the operator must monitor a great amount of information from the instruments that represents a specific type of event. Recently, several works have been developed for transient identification. These works frequently present a non reliable response, using the ''doń t know'' as the system output. In this work, we investigate the possibility of using a Neuro-Fuzzy modeling tool for efficient transient identification, aiming to helping the operator crew to take decisions relative to the procedure to be followed in situations of accidents/ transients at NPPs. The proposed system uses artificial neural networks (ANN) as first level transient diagnostic. After the ANN has done the preliminary transient type identification, a fuzzy-logic system analyzes the results emitting reliability degree of it. A validation of this identification system was made at the three loops Pressurized Water Reactor (PWR) simulator of the Human-System Interface Laboratory (LABIHS) of the Nuclear Engineering Institute (IEN/CNEN/Brazil). The obtained results show the potential of this new transient identification system to be used in an operational NPP in order to assist the operators to take decisions during transients/accidents.