Algoritmo modificado de PSO matricial aplicado a identificação de sistemas com análise de convergência

Recentemente diversas técnicas de computação evolucionárias têm sido utilizadas em áreas como estimação de parâmetros de processos dinâmicos lineares e não lineares ou até sujeitos a incertezas. Isso motiva a utilização de algoritmos como o otimizador por nuvem de partículas (PSO) nas referidas áreas do conhecimento. Porém, pouco se sabe sobre a convergência desse algoritmo e, principalmente, as análises e estudos realizados têm se concentrado em resultados experimentais. Por isso, é objetivo deste trabalho propor uma nova estrutura para o PSO que permita analisar melhor a convergência do algoritmo de forma analítica. Para isso, o PSO é reestruturado para assumir uma forma matricial e reformulado como um sistema linear por partes. As partes serão analisadas de forma separada e será proposta a inserção de um fator de esquecimento que garante que a parte mais significativa deste sistema possua autovalores dentro do círculo de raio unitário. Também será realizada a análise da convergência do algoritmo como um todo, utilizando um critério de convergência quase certa, aplicável a sistemas chaveados. Na sequência, serão realizados testes experimentais de maneira a verificar o comportamento dos autovalores após a inserção do fator de esquecimento. Posteriormente, os algoritmos de identificação de parâmetros tradicionais serão combinados com o PSO matricial, de maneira a tornar os resultados da identificação tão bons ou melhores que a identificação apenas com o PSO ou, apenas com os algoritmos tradicionais. Os resultados mostram a convergência das partículas em uma região delimitada e que as funções obtidas após a combinação do algoritmo PSO matricial com os algoritmos convencionais, apresentam maior generalização para o sistema apresentado. As conclusões a que se chega é que a hibridização, apesar de limitar a busca por uma partícula mais apta do PSO, permite um desempenho mínimo para o algoritmo e ainda possibilita melhorar o resultado obtido com os algoritmos tradicionais, permitindo a representação do sistema aproximado em quantidades maiores de frequências.

Critério de correntropia no treinamento de redes fuzzy wavelet neural networks para identificação de sistemas dinâmicos não lineares

The great interest in nonlinear system identification is mainly due to the fact that a large amount of real systems are complex and need to have their nonlinearities considered so that their models can be successfully used in applications of control, prediction, inference, among others. This work evaluates the application of Fuzzy Wavelet Neural Networks (FWNN) to identify nonlinear dynamical systems subjected to noise and outliers. Generally, these elements cause negative effects on the identification procedure, resulting in erroneous interpretations regarding the dynamical behavior of the system. The FWNN combines in a single structure the ability to deal with uncertainties of fuzzy logic, the multiresolution characteristics of wavelet theory and learning and generalization abilities of the artificial neural networks. Usually, the learning procedure of these neural networks is realized by a gradient based method, which uses the mean squared error as its cost function. This work proposes the replacement of this traditional function by an Information Theoretic Learning similarity measure, called correntropy. With the use of this similarity measure, higher order statistics can be considered during the FWNN training process. For this reason, this measure is more suitable for non-Gaussian error distributions and makes the training less sensitive to the presence of outliers. In order to evaluate this replacement, FWNN models are obtained in two identification case studies: a real nonlinear system, consisting of a multisection tank, and a simulated system based on a model of the human knee joint. The results demonstrate that the application of correntropy as the error backpropagation algorithm cost function makes the identification procedure using FWNN models more robust to outliers. However, this is only achieved if the gaussian kernel width of correntropy is properly adjusted.

iSalud: uma arquitetura para publicação e distribuição de sistemas de informação para o SUS

The Brazil Telehealth Networks Program was established by the Ministry of Health in 2007. Its main objective is to support professionals in Primary Health Care (PHC) by offering educational qualification, resulting in more favorable conditions to fixate the professional in remote areas. The formulation and management of telehealth services are performed by scientific and technical centers that are operated by public institutions of higher education and responsible for providing tools and services in the context of the regions where they are. However, one of the problems generated by this decentralization is the development of various tools with different types of language, architecture and without any regulation and integration of information with the Ministry of Health. Aiming to solve the above problem, we propose the specification, implementation and validation of an architectural model in the development and distribution of the Unified Health System software tools. This proposed architecture enables tools developed in telehealth center to be shared among the other centers, thereby preventing the unnecessary use of resources.

Teleconsultoria Off-line: uma arquitetura distribuída e compartilhada para sistemas heterogêneos

The Telehealth Brazil Networks Program, created in 2007 with the aim of strengthening primary care and the unified health system (SUS - Sistema Único de Saúde), uses information and communication technologies for distance learning activities related to health. The use of technology enables the interaction between health professionals and / or their patients, furthering the ability of Family Health Teams (FHT). The program is grounded in law, which determines a number of technologies, protocols and processes which guide the work of Telehealth nucleus in the provision of services to the population. Among these services is teleconsulting, which is registered consultation and held between workers, professionals and managers of healthcare through bidirectional telecommunication instruments, in order to answer questions about clinical procedures, health actions and questions on the dossier of work. With the expansion of the program in 2011, was possible to detect problems and challenges that cover virtually all nucleus at different scales for each region. Among these problems can list the heterogeneity of platforms, especially teleconsulting, and low internet coverage in the municipalities, mainly in the interior cities of Brazil. From this perspective, the aim of this paper is to propose a distributed architecture, using mobile computing to enable the sending of teleconsultation. This architecture works offline, so that when internet connection data will be synchronized with the server. This data will travel on compressed to reduce the need for high transmission rates. Any Telehealth Nucleus can use this architecture, through an external service, which will be coupled through a communication interface.

Estudo dos harmônicos entre diferentes sistemas de excitação de máquinas síncronas

Dissertação (Mestrado)

Utilização da transformada de wavelet para detecção de variações anormais de tensão em sistemas elétricos com geração distribuída

The increasing demand in electricity and decrease forecast, increasingly, of fossil fuel reserves, as well as increasing environmental concern in the use of these have generated a concern about the quality of electricity generation, making it well welcome new investments in generation through alternative, clean and renewable sources. Distributed generation is one of the main solutions for the independent and selfsufficient generating systems, such as the sugarcane industry. This sector has grown considerably, contributing expressively in the production of electricity to the distribution networks. Faced with this situation, one of the main objectives of this study is to propose the implementation of an algorithm to detect islanding disturbances in the electrical system, characterized by situations of under- or overvoltage. The algorithm should also commonly quantize the time that the system was operating in these conditions, to check the possible consequences that will be caused in the electric power system. In order to achieve this it used the technique of wavelet multiresolution analysis (AMR) for detecting the generated disorders. The data obtained can be processed so as to be used for a possible predictive maintenance in the protection equipment of electrical network, since they are prone to damage on prolonged operation under abnormal conditions of frequency and voltage.

Estudo comparativo de dois conversores Boost quadrático com comutação suave monochaveados para aplicação de rastreamento de máxima potência em sistemas fotovoltaicos

This paper makes a comparative study of two Soft Single Switched Quadratic Boost Converters (SSS1 and SSS2) focused on Maximum Power Point Tracking (MPPT) of a PV array using Perturb and Observe (P&O) algorithm. The proposed converters maintain the static gain characteristics and dynamics of the original converter with the advantage of considerably reducing the switching losses and Electromagnetic Interference (EMI). It is displayed the input voltage Quadratic Boost converter modeling; qualitative and quantitative analysis of soft switching converters, defining the operation principles, main waveforms, time intervals and the state variables in each operation steps, phase planes of resonant elements, static voltage gain expressions, analysis of voltage and current efforts in semiconductors and the operational curves at 200 W to 800 W. There are presented project of PI, PID and PID + Notch compensators for MPPT closed-loop system and resonant elements design. In order to analyze the operation of a complete photovoltaic system connected to the grid, it was chosen to simulate a three-phase inverter using the P-Q control theory of three-phase instantaneous power. Finally, the simulation results and experimental with the necessary comparative analysis of the proposed converters will be presented.

Projeto, implementação e análise de um conversor CC-CC de alto ganho e alto rendimento para aplicações fotovoltaicas

In recent years the photovoltaic generation has had greater insertion in the energy mix of the most developed countries, growing at annual rates of over 30%. The pressure for the reduction of pollutant emissions, diversification of the energy mix and the drop in prices are the main factors driving this growth. Grid tied systems plays an important role in alleviating the energy crisis and diversification of energy sources. Among the grid tied systems, building integrated photovoltaic systems suffers from partial shading of the photovoltaic modules and consequently the energy yield is reduced. In such cases, classical forms of modules connection do not produce good results and new techniques have been developed to increase the amount of energy produced by a set of modules. In the parallel connection technique of photovoltaic modules, a high voltage gain DC-DC converter is required, which is relatively complex to build with high efficiency. The current-fed isolated converters explored in this work have some desirable characteristics for this type of application, such as: low input current ripple and input voltage ripple, high voltage gain, galvanic isolation, feature high power capacity and it achieve soft switching in a wide operating range. This study presents contributions to the study of a high gain and high efficiency DC-DC converter for use in a parallel system of photovoltaic generation, being possible the use in a microinverter or with central inverter. The main contributions of this work are: analysis of the active clamping circuit operation proposing that the clamp capacitor connection must be done on the negative node of the power supply to reduce the input current ripple and thus reduce the filter requirements; use of a voltage doubler in the output rectifier to reduce the number of components and to extend the gain of the converter; detailed study of the converter components in order to raise the efficiency; obtaining the AC equivalent model and control system design. As a result, a DC-DC converter with high gain, high efficiency and without electrolytic capacitors in the power stage was developed. In the final part of this work the DC-DC converter operation connected to an inverter is presented. Besides, the DC bus controller is designed and are implemented two maximum power point tracking algorithms. Experimental results of full system operation connected to an emulator and subsequently to a real photovoltaic module are also given.

Estabilidade e robustez de um controlador adaptativo indireto por um modelo de referência e estrutura variável

In this thesis, it is developed the robustness and stability analysis of a variable structure model reference adaptive controller considering the presence of disturbances and unmodeled dynamics. The controller is applied to uncertain, monovariable, linear time-invariant plants with relative degree one, and its development is based on the indirect adaptive control. In the direct approach, well known in the literature, the switching laws are designed for the controller parameters. In the indirect one, they are designed for the plant parameters and, thus, the selection of the relays upper bounds becomes more intuitive, whereas they are related to physical parameters, which present uncertainties that can be known easier, such as resistances, capacitances, inertia moments and friction coefficients. Two versions for the controller algorithm with the stability analysis are presented. The global asymptotic stability with respect to a compact set is guaranteed for both cases. Simulation results under adverse operation conditions in order to verify the theoretical results and to show the performance and robustness of the proposed controller are showed. Moreover, for practical purposes, some simplifications on the original algorithm are developed

Mapeamento de ambientes estruturados com extração de informações geométricas através de dados sensoriais

The objective of this thesis is proposes a method for a mobile robot to build a hybrid map of an indoor, semi-structured environment. The topological part of this map deals with spatial relationships among rooms and corridors. It is a topology-based map, where the edges of the graph are rooms or corridors, and each link between two distinct edges represents a door. The metric part of the map consists in a set of parameters. These parameters describe a geometric figure which adapts to the free space of the local environment. This figure is calculated by a set of points which sample the boundaries of the local free space. These points are obtained with range sensors and with knowledge about the robot s pose. A method based on generalized Hough transform is applied to this set of points in order to obtain the geomtric figure. The building of the hybrid map is an incremental procedure. It is accomplished while the robot explores the environment. Each room is associated with a metric local map and, consequently, with an edge of the topo-logical map. During the mapping procedure, the robot may use recent metric information of the environment to improve its global or relative pose

Controle vetorial de velocidade de uma máquina de indução sem mancais trifásica com bobinado dividido utilizando estimação neural de fluxo

This work describes the study and the implementation of the vector speed control for a three-phase Bearingless induction machine with divided winding of 4 poles and 1,1 kW using the neural rotor flux estimation. The vector speed control operates together with the radial positioning controllers and with the winding currents controllers of the stator phases. For the radial positioning, the forces controlled by the internal machine magnetic fields are used. For the radial forces optimization , a special rotor winding with independent circuits which allows a low rotational torque influence was used. The neural flux estimation applied to the vector speed controls has the objective of compensating the parameter dependences of the conventional estimators in relation to the parameter machine s variations due to the temperature increases or due to the rotor magnetic saturation. The implemented control system allows a direct comparison between the respective responses of the speed and radial positioning controllers to the machine oriented by the neural rotor flux estimator in relation to the conventional flux estimator. All the system control is executed by a program developed in the ANSI C language. The DSP resources used by the system are: the Analog/Digital channels converters, the PWM outputs and the parallel and RS-232 serial interfaces, which are responsible, respectively, by the DSP programming and the data capture through the supervisory system

Estudo de estratégias de otimização para poços de petróleo com elevação por bombeio de cavidades progressivas

The progressing cavity pump artificial lift system, PCP, is a main lift system used in oil production industry. As this artificial lift application grows the knowledge of it s dynamics behavior, the application of automatic control and the developing of equipment selection design specialist systems are more useful. This work presents tools for dynamic analysis, control technics and a specialist system for selecting lift equipments for this artificial lift technology. The PCP artificial lift system consists of a progressing cavity pump installed downhole in the production tubing edge. The pump consists of two parts, a stator and a rotor, and is set in motion by the rotation of the rotor transmitted through a rod string installed in the tubing. The surface equipment generates and transmits the rotation to the rod string. First, is presented the developing of a complete mathematical dynamic model of PCP system. This model is simplified for use in several conditions, including steady state for sizing PCP equipments, like pump, rod string and drive head. This model is used to implement a computer simulator able to help in system analysis and to operates as a well with a controller and allows testing and developing of control algorithms. The next developing applies control technics to PCP system to optimize pumping velocity to achieve productivity and durability of downhole components. The mathematical model is linearized to apply conventional control technics including observability and controllability of the system and develop design rules for PI controller. Stability conditions are stated for operation point of the system. A fuzzy rule-based control system are developed from a PI controller using a inference machine based on Mandami operators. The fuzzy logic is applied to develop a specialist system that selects PCP equipments too. The developed technics to simulate and the linearized model was used in an actual well where a control system is installed. This control system consists of a pump intake pressure sensor, an industrial controller and a variable speed drive. The PI control was applied and fuzzy controller was applied to optimize simulated and actual well operation and the results was compared. The simulated and actual open loop response was compared to validate simulation. A case study was accomplished to validate equipment selection specialist system

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

Classificação de distúrbios na rede elétrica usando redes neurais e wavelets

Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbance s occurrences in the network. This work presents a methodology based on the Discrete Wavelet Transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks