41 resultados para Automatic Control


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The power system stability analysis is approached taking into explicit account the dynamic performance of generators internal voltages and control devices. The proposed method is not a direct method in the usual sense since conclusion for stability or instability is not exclusively based on energy function considerations but it is automatic since the conclusion is achieved without an analyst intervention. The stability test accounts for the nonconservative nature of the system with control devices such as the automatic voltage regulator (AVR) and automatic generation control (AGC) in contrast with the well-known direct methods. An energy function is derived for the system with machines forth-order model, AVR and AGC and it is used to start the analysis procedure and to point out criticalities. The conclusive analysis itself is made by means of a method based on the definition of a region surrounding the equilibrium point where the system net torque is equilibrium restorative. This region is named positive synchronization region (PSR). Since the definition of the PSR boundaries have no dependence on modelling approximation, the PSR test conduces to reliable results. (C) 2008 Elsevier Ltd. All rights reserved.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This work presents a simplified architecture of a neurofuzzy controller for general purpose applications that tries to minimize the processing used in the several stages of hazy modeling of systems. The basic procedures of fuzzification and defuzzification are simplified to the maximum while the inference procedures are computed in a private way. The simplified architecture allows a fast and easy configuration of the neurofuzzy controller and the structuring rules that define the control actions is automatic. Th controller's Limits and performance are standardized and the control actions are previously calculated. For application, the industrial systems of fluid flow control will be considered.

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The identification of ground control on photographs or images is usually carried out by a human operator, who uses his natural skills to make interpretations. In Digital Photogrammetry, which uses techniques of digital image processing extraction of ground control can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features of object space and its homologous in the image space. A build-in self-diagnosis is also used in this method. It is based on implementation of data snooping statistic test in the process of spatial resection using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

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An overview is given on the possibility of controlling the status of circuit breakers (CB) in a substations with the use of a knowledge base that relates some of the operation magnitudes, mixing status variables with time variables and fuzzy sets. It is shown that even when all the magnitudes to be controlled cannot be included in the analysis, it is possible to control the desired status while supervising some important magnitudes as the voltage, power factor, and harmonic distortion, as well as the present status.

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This paper introduces a method for the supervision and control of devices in electric substations using fuzzy logic and artificial neural networks. An automatic knowledge acquisition process is included which allows the on-line processing of operator actions and the extraction of control rules to replace gradually the human operator. Some experimental results obtained by the application of the implemented software in a simulated environment with random signal generators are presented.

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This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here. Copyright © 2006 by ABCM.

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This paper deals with the subject-matter of teaching immaterial issues like power system dynamics where the phenomena and events are not sense-perceptible. The dynamics of the power system are recognized as analogous to the dynamics of a simple mechanical pendulum taken into account the well-known classical model for the synchronous machine. It is shown that even for more sophisticated models including flux decay and Automatic Voltage Regulator the mechanical device can be taken as an analogous, since provided some considerations about variation and control of the pendulum length using certain control laws. The resulting mathematical model represents a mechanical system that can be built for use in laboratory teaching of power system dynamics. © 2010 Praise Worthy Prize S.r.l. - All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)