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Item Desempenho de métodos clássicos e meta-heurísticas aplicadas à sintonia de controladores PID sob o aspecto do fator de incontrolabilidade(Universidade Federal de Goiás, 2023-03-30) Andrade Filho, Alfredo de Paulo; Cardoso, Alisson Assis; http://lattes.cnpq.br/8216536516894987; Cruz Júnior, Gelson da; http://lattes.cnpq.br/4370555454162131; Cruz Júnior, Gelson da; Avelar, Henrique José; Teixeira, Edilberto PereiraThe PID (Proportional Integral Derivative) is one of the most used in industry, and has been employed around the world for decades in industrial control systems. Its popularity can be attributed in part, to its robust performance, in a wide range of operating conditions, and their functional simplicity, which allows engineers to operate them in a simple and direct way. However, tuning such controllers effectively, represents a challenge to control engineers, since it directly affects the efficiency of the system. In the context of modern industry, the setback is even greater, due to the complexity of the processes involved, in which the presence of the Dead Time and the Time Constant of the system, have a great impact on its response. Tuning of PID controllers aims to satisfy some specifications imposed on the transient and steadystate characteristics of the response of the system being controlled. Generally, these specifications fall on the values of Rise Time (Tr), Settlement Time (Ts), Maximum Value overshoot (Mp) and a maximum acceptable Stationary Error (Ess) value. Within the scope of control problems that offer great complexity, either because of the impossibility of previously knowing the transfer function of the system, or due to its multivariable characteristics, several researches have been carried out within the scope of optimizing the tuning of PID controllers using meta-heuristics. In many situations, the system PID cannot be accurately modeled, and still malfunctions in the presence of noise or external disturbances due to the adjustment problem of its parameters that are challenging in practice, as they depend on characteristics of the environment. In this work, we sought to evaluate the performance of the PID controller under the aspect of Uncontrollability Factor when tuned by Genetic Algorithm heuristics (GA) and Particle Swarm (PSO), which have been shown to be more effective in compared to classical tuning methods. Six case studies were evaluated, with varied Uncontrollability Factors.Item Aplicação de técnicas SPWM na segmentação dos polos da máquina síncrona de ímãs permanentes para redução na ondulação do torque(Universidade Federal de Goiás, 2020-08-20) Andrade Júnior, Khristian Marques de; Paula, Geyverson Teixeira de; http://lattes.cnpq.br/0140145167826333; Paula, Geyverson Teixeira de; Alvarenga, Bernardo Pinheiro de; Silva, Wander Gonçalves daIn the present work, six methods are proposed considering the application of PWM techniques in the pole segmentation of permanent magnet synchronous machines in order to reduce the value of the torque ripple. Such methods reduce this ripple by eliminating the back-emf low-order harmonics and reducing the amplitude of the cogging torque. The PWM techniques considered here are the unipolar sinusoidal, bipolar, trapezoidal and sinusoidal with harmonic injection. A finite element analysis of the designed machines, under no load and under load conditions, is carried out in order to validate the presented methods. Method 1 presents the best results when the amplitude modulation index was kept constant and with unit value, guaranteeing a reduction in the cogging torque of 78.54%, however also reducing the electromagnetic torque by 17.87%. The major disadvantage of Methods 2, 5 and 6 is the presence of low order harmonics in their back-emf. The effect of using fractional-pitch winding is evaluated when these methods are considered to surpass the mentioned problem, however it is observed that, contrary to what is desired, the the torque ripple increases, while its average value reduces. Furthermore, the elimination of segments with width of less than 5◦ results, in general, in an increase of the back-emf harmonics and a behavior of the cogging torque without an apparent trivial pattern. Finally, an optimization process is carried out for Methods 1, 5 and 6, as these present the best results, to determine the optimal values of the amplitude and frequency modulation indices that guarantee a reduction in the cogging torque and mitigate the depreciation in the machine torque. In this scenario, Method 6 has the best results, reducing the torque ripple by about 88.02%, and increasing the fundamental density of the air gap flux by 4.55% in relation to that one of the reference machine.Item Potencialização do rendimento do gerador a relutância chaveado empregando técnica de rastreamento associada a controle de tensão otimizado(Universidade Federal de Goiás, 2020-12-16) Araújo, Wanderson Rainer Hilário de; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Coimbra, António Paulo Mendes Breda Dias; Ribeiro, Luiz Eduardo Bento; Sousa, Marcos Antônio de; Oliveira, Marco Antônio Assfalk de; Calixto, Wesley PachecoThis work presents the potentialization of the efficiency of the Switched Reluctance Generator (GRC) submitted to the control of the output voltage. The efficiency is enhanced by using tracking technique acting on the switching angles of the power converter. As it is a DC machine, the control of the output voltage is applied to adapt this value to DC-AC conversion systems and load controllers. The PID controller is used and, because it is a controller with only one output, other quantities are not contemplated by the performance of the controller. In this work, there is an interest in enhancing the performance of the GRC to make this type of machine more attractive for generating electricity in distributed systems and in installations without connection to the main distribution network. Therefore, in parallel to the PID controller, a tracking technique is applied to the GRC performance with a disturb and observe algorithm. Other procedures are presented, such as obtaining an inductance surface to improve the mathematical and computational modeling of the generator, in addition to the development of an indirect conjugate detection system. Simulation and experimental results are presented for validation and discussion of the proposed study.Item Processo de otimização aplicado no projeto térmico e luminoso de luminárias de Led de alta potência(Universidade Federal de Goiás, 2022-11-25) Barbosa, José Luiz Ferraz; Simon, Daniel John; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Magalhães, Alana da Silva; Reis, Márcio Rodrigues da Cunha; Cruz Junior, Gelson da; Marques, Leonardo GarciaThis work develops an optimization methodology for the design of high power LED luminaires – HP-LED. The objective is to design a luminaire with optimized geometry and LED quantity. The solution to the problem must have an illuminance uniformity factor in the illuminated area according to standards established by regulations and adequate thermal management that guarantees luminous flux and lifetime within the nominal standards established by the HP-LED manufacturer. A computational model of the geometry of the HP-LED luminaire is used, in which thermal and optical analyzes are performed through simulators. Simulation and experimental results are presented for validation of the proposed study and from the results of the simulations a multi-objective evaluation function is developed in order to categorize potentially viable solutions. The optimized solution obtained proposes the design of a rectangular luminaire with an arrangement of 2 × 2 HP-LED with a temperature that reaches a maximum value of 73.9oC in steady state and an illuminance uniformity factor of 0.228 for individual lighting. The illuminance uniformity factor found for two adjacent lighting points on pedestrian paths is 0.5413, with minimum illuminance of 36.95lx, maximum illuminance of 93.65lx and average illuminance of 68.27lx. It is concluded that the metric developed in this proposal is capable of evaluating lighting criteria and nominal criteria of thermal limitation, even managing to classify different types of luminaires.Item Avaliação de características e previsão de sucesso de canções populares brasileiras por meio de aprendizado de máquina(Universidade Federal de Goiás, 2021-04-13) Bertoni, André Augusto; Lemos, Rodrigo Pinto; http://lattes.cnpq.br/3333000136853156; Lemos, Rodrigo Pinto; Vieira, Flávio Henrique Teles; Calixto, Wesley Pacheco; Almeida, Anselmo Guerra deThis work aims to develop algorithms capable of predicting whether a Brazilian popular song can become a commercial success, using the help of Machine Learning techniques. To achieve this goal, a bank of popular Brazilian songs performed on the radio from 2014 to 2019 was created, applying the number of radio plays as the criterion for separating the songs into a successful group and another of non-successful. Several techniques of Data Analysis were studied and applied to optimize the databases and extract statistical characteristics of the songs. From the study of music theory, a set of musical semantic characteristics extracted from each song was also defined to support the Machine Learning algorithms, and then employ Data Science techniques to predict if a song can become a commercial success. Classification algorithms with supervised training were used, both by the classical approach and by means of Deep Neural Networks. For training and validation, cross-validation was used with ten subsets for the classical approach, and five subsets for convolutional networks. The performance of the algorithms was compared basically in terms of accuracy, precision, sensitivity and specificity. The discussion of the results of this work showed that statistical characteristics extracted from the songs brought satisfactory results in several metrics, such as: Accuracy (69.63%), Precision: (69.03%), Sensitivity (71.55%), Balanced Accuracy (69.75%) and ROC (69.75%), using classic techniques as: Naive Bayes, Decision Tree, Random Forest, kNN, Logistic Regression, SVM and MLP - which represents an excellent result, when compared to several other works of literature. Deep Neural Networks of the Convolutional type did not bring good results, with little better accuracy than randomness. The best scenario was achieved by combining three distinct banks of characteristics: a) statistics; b) spectrographs extracted from the Main Voice Melody; c) Musical Melodic Semantic information. With the combination of these three distinct banks of characteristics, 74.54% Accuracy was obtained.Item Mineração de opinião em mídias sociais com aprendizado de máquina(Universidade Federal de Goiás, 2020-10-14) Brandão, Jhonathan de Godoi; Calixto, Wesley Pacheco; https://orcid.org/0000-0002-1928-4432; Calixto, Wesley Pacheco; Ribeiro, Luiz Eduardo Bento; Reis, Márcio Rodrigues da Cunha; Cruz Junior, Gelson da; Marques, Leonardo GarciaThe aim of this work is to develop a tool for that optimizes supervised machine learning models in order to classify polarity of opinions in tweets. Five different datasets are used, which are prepared, preprocessed and then used as input for the training and evaluation stage of machine learning models. The best accuracy results obtained in the training and evaluation of the models are 82.45% for the data without preprocessing × 78.83% with all the proposed preprocessing for the dataset using the Naive Bayes classifier. Finally, hyperparametric optimization of the classifiers and selection of the model that obtains the best accuracy is performed. The optimized model achieves an accuracy greater than 90% for some data sets. The supervised learning techniques depend on labeled data for training, the proposed method produces similar performances for datasets of varying sizes, which allows the development of optimized classification models with reduced amount of labeled data.Item Análise e otimização da rede de distribuição de energia utilizando conceitos de redes inteligentes(Universidade Federal de Goiás, 2021-10-21) Caetano Neto, João; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Reis, Márcio Rodrigues da Cunha; Lemos, Rodrigo Pinto; Marques, Leonardo Garcia; Magalhães, Alana da SilvaThe main objective of this work is to develop a methodology for analyzing the quality of the voltage level in the distribution power grid to identify and re-duce the violations of voltage limits through the proposition of optimal points for the allocation of photovoltaic distributed generation. The methodology uses the geographic location of the power grid and its consumers to perform the grouping and classification in spatial grids of 100×100 m using the average annual consumption profile. The generated profiles, including the grid infor-mation, are sent to the photovoltaic distributed generation allocation algo-rithm, which, using an optimization process, identifies the geographic location, the required installed capacity, and the minimum number of photovoltaic gen-eration units that must be inserted to minimize the violations of voltage limits, respecting the necessary restrictions. The entire proposal is applied in a real feeder with thousands of bars, whose model is validated with measurements carried out in the field. Different violations of voltage limits scenarios are used to validate the methodology, obtaining grids with better voltage quality after the optimized allocation of photovoltaic distributed generation. The proposal presents itself as a new tool in the work of adapting the voltage of the distri-bution power grid using photovoltaic distributed generation.Item Controle adaptativo de fluxos de tráfego de redes baseado em modelagem multifractal e sistemas fuzzy(Universidade Federal de Goiás, 2019-08-13) Cardoso, Alisson Assis; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Sousa, Marcos Antônio de; Lemos, Rodrigo Pinto; Vieira, Robson Domingos; Dantas, Maria José PereiraThe network traffic flows that arrive at the base station to be transmitted to the mobile users, in a 5G network system, enter the queuing process until transmission rates are provided. In order to minimize the delay, this work proposes the use of flow control algorithms based on the prediction of user queue behavior. Thus, the more accurate the data prediction, the greater the accuracy and control of flow control algorithms. To improve accuracy, models describing the behavior of network traffic are employed. In this work, two adaptive modeling algorithms based on the Lognormal Beta and BetaMWM models are proposed to model the network traffic and allow its use in real-time applications, such as the 5G network. Simulations are performed in comparisons to multifractal models found in the literature to validate the proposed algorithms, where results in terms of expected value, variance, moments of 2º to 4º order, mean squared errors of autocorrelation and distribution function prove the adaptively use of the algorithms. To perform the flow control, an equation is also proposed to obtain the optimal prediction-based control rate, where generalized ortonormal functions and fuzzy modeling are employed. Simulations of the Downlink 5G link are also performed to validate the proposed flow control algorithms. For this, results in terms of Flow, Utilization, Loss Rate, Delay and Average Waiting Queue are presented, proving the efficiency in the use of multifractal models, orthonormal basis functions, and fuzzy modeling in flow control algorithms for Downlink 5G systems. Taking advantage of the proposed multifractal modeling, an equation is also proposed to estimate the delay limitation for the first recommendations of the 5G network using the network calculation theory. For this, it is proposed a stochastic envelope process for network traffic based on the Adaptive Beta Lognormal model where comparisons with envelope processes known in the literature are performed.Item Alocação de recursos em redes sem fio multiportadoras com ondas milimétricas utilizando aprendizado por reforço baseado em modelo Markoviano(Universidade Federal de Goiás, 2022-07-08) Carneiro, Daniel Porto Queiroz; Cardoso, Alisson Assis; http://lattes.cnpq.br/8216536516894987; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Soares, Anderson da Silva; Cardoso, Alisson Assis; Lemos, Rodrigo PintoIn this dissertation, we present reinforcement learning-based resource allocation algorithms for a multicarrier communication system considering multiple users and the effects of multipath and average path loss in a transmission assuming millimeter waves. To this end, it is proposed that the communication system can be described by a Markovian model represented by queue states in buffers and channel states. For the resource allocation algorithms of this work, we introduce reward functions to be used in the reinforcement learning algorithm Q-learning. The results obtained in the simulations show that the application of the proposed algorithms for resource scheduling provides, in general, an improvement in the performance parameters of the considered communication system, such as, for example, increased throughput and decreased packet loss. Comparisons with other algorithms presented in the literature are carried out, also showing that the use of the proposed reward function and considered Markovian model makes the scheduling of users and the sharing of resources more efficient. Furthermore, a solution for resource and power allocation using a Deep Q-Network is presented. The modeling of states proposed for the DQN network covers some limitations encountered with the matrix representation of states and extends the limits for the size of the buffer.Item Aplicação da inteligência artificial, ontologia e mineração de dados para classificação de sentenças judiciais(Universidade Federal de Goiás, 2021-12-20) Castro Junior, Antonio Pires de; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Peretta, Igor Santos; Araújo, Wanderson Rainer Hilário de; Soares, Fabrizzio Alphonsus Alves de Melo Nunes; Gomes, Viviane Margarida; Calixto, Wesley PachecoThe objective of this work is to apply together ontology with bag-of-words models, similarity learning, and document classification in texts with uttered decisions. The objective is to improve the results of data mining in a database of court decisions. An automatic method of searching sentences in judicial processes related to the one under judgment is developed using the frequency term-inverse of frequency in documents model together with the Jaccard similarity coefficient, establishing weights on the co-occurrence of terms in legal texts of the same category. A dataset with document vectorization is used for supervised training of machine learning algorithms, aiming to classify new justice processes. The proposed methodology provides flexibility to the Judiciary, simulating the role of legal advisors in preparing court decisions with less time and efficiency in the search for jurisprudential standards. The results obtained show that, through accuracy metrics, the proposed model is effective and efficient, and can be applied in the process of identification of court decisions. Thus, the application of artificial intelligence, ontology, and data mining is indicated for information retrieval in court decisions.Item Contribuições à modelagem, controle e integração de dispositivos fotovoltaicos a sistemas elétricos de potência(Universidade Federal de Goiás, 2023-11-03) Corrêa, Henrique Pires; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Palhares, Reinaldo Martinez; Kopcak, Igor; Negrete, Lina Paola Garcés; Belchior , Fernando NunesThe prominence attained by photovoltaic (PV) power generation among the various available renewable energy resources has led to the need of analyzing and engineering such technology at a wide range of implementation scales, beginning from the electrical characteristics of PV cells, passing through the local control of PV generation systems, up to the massive integration of PV resources to wider electrical power systems, such as the distribution grid. This thesis is divided into three parts, each of which presents novel contributions to the study of PV systems in the three aforementioned scales of analysis. In the first part, analytical modeling of PV cell current-voltage (I-V) characteristics by means of explicit closed-form equations is addressed. A new piecewise quadratic model is proposed, which is shown to perform either better or comparably, for different solar cells, to state-of-the-art models in terms of accuracy. Two methods are established for computing the model parameters: the first one is analytical and only requires datasheet information, whereas the second one uses linear-complexity optimization with respect to I-V samples in order to further improve accuracy. In the second part, the problem of maximum power point tracking (MPPT) in two-stage PV systems is considered. First, a new hybrid MPPT method which uses direct duty cycle control for enhanced tracking efficiency is developed for grid-tied systems. Then, an analytical MPPT approach for single-phase off-grid variable-voltage systems is presented and subsequently generalized to consider current harmonics and three-phase loads. Both proposed MPPT methods are shown, by means of simulation, to perform better than existing methods with similar implementation complexities. In the third part, voltage control of distribution systems with photovoltaic penetration by means of PV inverter reactive power support is studied. Three novel decentralized methods for controlling the inverter reactive power setpoints are proposed. The first method considers voltage measurements are available at each PV inverter and consists in the heuristic specification of a cooperative decentralized Markov decision process (MDP), whose offline solution yields voltage control policies to be carried out by the grid zone controllers. On the other hand, the second method assumes voltage measurement and computational resources are scarce and establishes a decentralized strategy which only uses two voltage measurements per control zone and is directly compatible with droop-type controls usually found in PV inverters. At last, a third method is presented which combines cooperative MDP, droop control and a switching mechanism for achieving a compromise between voltage regulation and reduction of active power losses. All methods are compared to similar existing approaches, via simulations with real irradiance profiles in a large distribution grid, yielding favorable performances.Item Estudo empírico de avaliação inteligente computadorizada de questões abertas baseado em colaboração(Universidade Federal de Goiás, 2009-09-12) Corrêa, Kleber Pullig; Machado, Paulo César Miranda; http://lattes.cnpq.br/8831309316416795; Machado, Paulo César Miranda; Nalini, Lauro Eugênio Guimarães; Martins, Weber; Lemos, Rodrigo Pinto; Fleury, Claudio AfonsoThis research submits to experimental tests in real-world environment, the Conexionist Collaborative Intelligent Evaluation System idealized by Martins (2004) and tested with simulations by Guimarães (2004), who have noticed consistent and promising results when dealing with synthetic datas. The system explores the Learning Theory by Kolb (1984), Peer Collaboration Evaluation and Artificial Intelligence (multilayer perceptrons neural networks), which are capable to apply and correct tests with open (free) questions. To get a real-world data, some students from the course of Engineer registered at Universidade Federal de Goiás (UFG) on the period of june 2008 to july 2009 were taken in heterogeneous groups composed by men and women in age from 16 to 26 years old and at least 18 students per test. The software SAICOweb, developed specifically to this data collection, allows the computerized evaluations of open (free) questions, by using methods and stages described at Guimarães (2004) research. SAICOweb system were experimental validited in a satisfactory way by an unique group composed by 38 students (by using two tests with 08 open questions each). The analisys of the results with Pearson correlation shows strong association (0,81) between grades given by SAICOweb and the human grades (corrected by professors). Another important result is the satisfaction of professor and students when evaluating Software SAICOweb, evaluation method, pedagogical experience and anonymity. Specific itens were identified and suggested as future updates, when more experimental tests should be designed to validade other aspects of the System.Item Modelo de programação não-linear para a reconfiguração e alocação de geração distribuída em redes de distribuição de energia elétrica(Universidade Federal de Goiás, 2022-09-16) Costa, Frederico Marques da; Gallego Pareja, Luis Alfonso; http://lattes.cnpq.br/8018026566444794; Garcés Negrete, Lina Paola; http://lattes.cnpq.br/3707701912481754; Flórez, Hugo Andrés Ruiz; Kopcak, Igor; Garcés Negrete, Lina Paola; Gallego Pareja, Luis AlfonsoThe Reconfiguration of Electric Power Distribution Systems (REPDS) is a traditional problem and of high mathematical complexity, since the operating state of the disconnecting switches enables the reduction of total operating costs, as well as the reduction of technical losses, so that the minimum voltage limits necessary to meet the loads are respected. The REPDS problem seeks to find the optimal combination of the states of the existing intercon-nection switches, so that, simultaneously, it meets the operational constraints, minimizes the objective function in focus and maintains the radiality, whereas the study of the allocation of the Distributed Generation (DG) it seeks the best connection location for the generators dis-tributed in the system in such a way that it can also minimize operating costs and total active power losses, complying with the voltage levels established by current national regulations. In this way, this work presents a methodology to solve the REPDS problem in the presence of DG through a Mixed Integer Nonlinear Programming (MINLP) model,developed in the AMPL - A Mathematical Programming Language - programming environment and solved by the commercial solver knitro. Several tests were performed on electrical systems commonly found in the technical literature, to verify the convergence of the proposed model to solve the REPDS problem together with the DG allocation. To guarantee success in the implementa-tions, initially, both problems were solved independently and after finding consistent results, both problems were solved simultaneously. From the results obtained, it was found that the adopted unified model (REPDS with DG allocation) has high reliability and presents optimal solutions that significantly reduce active power losses when compared to the system in its original configuration. However, despite its reliability, the solution of the nonlinear model requires a high computational cost when dealing with a system of 69 buses or higher.Item Análise de viabilidade técnica, econômica e ambiental de um projeto de eficiência energética associado com geração distribuída(Universidade Federal de Goiás, 2022-04-25) Faria, Adriano Ferreira de; Marra, Enes Gonçalves; http://lattes.cnpq.br/8463332056679918; Alvarenga, Bernardo Pinheiro de; http://lattes.cnpq.br/9850449311607643; Alvarenga, Bernardo Pinheiro de; Marra, Enes Gonçalves; Belchior, Fernando Nunes; Viajante, Ghunter Paulo; Domingos, José LuisThis study focused on developing a sustainability project carried out in 11 Federal Institute of Education, Science, and Technology of Goiás (IFG) campuses, combining energy efficiency and distributed generation actions to optimize energy consumption by through the retrofit of the lighting system, installation of a photovoltaic generation system, energy monitoring, and qualification and training of teachers, students and employees, in compliance with the guidelines established by the National Electric Energy Agency (ANEEL) within the scope of the Public Call for Priority Projects for EE and Strategic R&D nº 01/2016 – “Energy Efficiency and Mini Generation in Public Institutions of Higher Education”. In the lighting system, 18,377 inefficient lamps were replaced by lamps with more efficient technology, with an energy saving of 867.9 MWh/year and a peak demand reduction of 309.6 kW. The proposed generation system aimed to install 3076 PV modules on the rooftops of selected campus buildings, totaling 1 MWp of installed power with an average annual power generation of 1736.9 MWh/year. The total project investment was USD 1,348,768.50 and the global cost–benefit ratio of the project was 0.68, which will result in annual savings of approximately USD 197,321.85. This corresponded to a 58% reduction in energy bills. The project proposed in this work was considered technically and economically viable within the scope of the Brazilian Energy. The estimate of avoided carbon emissions is also carried out, considering the methodologies used by the United Nations Framework Climate Change Convention (UNFCCC) for Clean Development Mechanism (CDM) projects that include energy efficiency activities and grid-connected renewable energy generation, resulting in an avoided emission of 983.36 tCO2 eq.Item Sistema de comunicação alternativa para pessoas com distúrbios neuromotores severos usando redes neurais artificiais(Universidade Federal de Goiás, 2023-12-15) Floriano, Carolina Souza; Silva, Adson Rocha; http://lattes.cnpq.br/4116708456419800; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Brito, Leonardo da Cunha; Gomide, Renato de Sousa; Rocha, Adson SilvaCommunication difficulties are frequent for many people with severe motor disabilities, making it difficult for them to interact with their families, caregivers and society in general. Augmentative and Alternative Communication (AAC) then aims to compensate for the communication deficit of these people, providing the individual with a better quality of life. However, these individuals with severe neuromotor disorders who have severe movement restrictions find great challenges in the use of several current assistive technologies. In this context, the objective of this research is to present an Alternative Communication System based on Artificial Neural Networks with a user-centered approach and their needs, for use by this public. The input and signal processing are carried out by reading facial landmark points, using the MediaPipe FaceMesh library. The development of the gesture/facial expression classifier is performed through the implementation and comparison of two different models: a Convolutional Neural Network (CNN) model and a Recurrent Neural Network model using Long Short-Term Memory (LSTM) units and dense layers. Dynamic challenges were implemented to conduct a more in-depth analysis of the models’ performance in various contexts, varying parameters such as the quantity of samples and the inclusion of similar gestures. Real-time overall results indicate a consistent performance of the proposed system, suggesting that, in both approaches, the Convolutional Neural Network (CNN) stands out significantly compared to the Long Short-Term Memory Recurrent Neural Network (LSTM) in gesture recognition.Item Modelos de simulação e controle preditivo generalizado de sistemas fotovoltaicos conectados à rede(Universidade Federal de Goiás, 2019-11-28) Franco, Ricardo Augusto Pereira; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Negrete, Lina Paola Garces; Castro, Marcelo Stehling de; Soares, Telma Worle Lima; Belchior, Fernando NunesAfter the Second Industrial Revolution, the electric energy became an essential item for the world population. Beyond the environmental impacts caused by polluting energy sources, the awareness of clean energy generation has been growing worldwide. In this way, renewable and clean energy sources gain prominence in relation to traditional dirty energy sources. Photovoltaic systems can help to reduce the energy consumption at the consumer units in which they are deployed and it can contribute to reducing the energy demand provided by the utility power grid. Thus, the objective of this work is to provide modeling, simulation and control methods for photovoltaic systems in order to assist the photovoltaic systems projects, to analyze the quality of the energy produced, the impacts that these systems cause on the distribution network and to perform the control of power generation of photovoltaic systems. It is proposed to develop optimization and analytical methods for the estimation of the parameters of the single diode model. The estimation of the parameters is performed to improve the modeling of a photovoltaic module and, consequently, its performance in the generation of energy. Then, simulations of grid-connected photovoltaic systems are proposed with the purpose of analyzing the impacts that the photovoltaic energy generation implies on the consumer loads and on the distribution network. Finally, it is proposed a method of energy flow control in a system consisting of photovoltaic system and energy storage system, in order to reduce the energy consumed from the utility grid. The energy flows in this electric system with energy storage system (hybrid system) can be combined to provide power for a load or inject power into the distribution network. The results presented show the benefits of the estimation of parameters of a photovoltaic module in terms of power generation. The results of the simulations show the impacts of photovoltaic systems for the consumer who installed the system and for the utility to design its energy distribution networks in medium and long-term. The results of the controller present the optimization achieved through the control of hybrid energy systems, reducing the costs of the energy consumption of a load and making the most efficient use of the energy storage system.Item Acústica aplicada no desenvolvimento de equipamentos para agricultura de precisão(Universidade Federal de Goiás, 2022-07-08) Furriel, Geovanne Pereira; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Silva, José Geraldo da; Araújo, Wanderson Rainer Hilário de; Jakelaitis, Adriano; Cruz Junior, Gelson daThis work presents methodology for development of precision agriculture equipment based on acoustic and vibration techniques. The proposed methodology uses the scale reduction method to simulate the induced vibration and the direction of sound pressure fields. After analyzing the scale-down model, the prototype is built in real dimensions to validate the proposed system. Two acoustic induction systems are designed and evaluated, one for applying phytosanitary products and the other for selective fruit harvesting. When applying the phytosanitary product, there is a reduction in drift and an increase in leaf coverage by approximately 45%. In the selective harvest, the proposed method is analyzed, and approximately 40% of the fruits were harvested at the appropriate maturation stage. The acoustic techniques presented applied to agriculture are promising for developing equipment for handling and harvesting in precision coffee farming. The results indicate that using acoustic techniques promotes the reduction of the inherent wear of the harvest in the plants.Item Estudo, implementação e otimização de técnicas de controle avançado(Universidade Federal de Goiás, 2022-10-06) Ganzaroli, Cleber Asmar; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Magalhães, Alana da Silva; Calixto, Wesley Pacheco; Gomide, Renato de Sousa; Lemos, Rodrigo Pinto; Araújo, Wanderson Rainer Hilário deThis work proposes the tuning, implementation, analysis and comparison of different control strategies applied to the same system. The controllers studied are: Proportional, Integral and Derivative, Nonlinear Predictive, Fuzzy Control and Sliding Mode Control. These techniques are applied to the speed control of an independently excited DC motor driven by a fully controlled three-phase rectifier. The methodology proposes the bench design, the modeling of the real system by the system identification method, the sensitivity analysis and the adjustments of the controllers parameters using an optimization process. Comparisons are made between the techniques, highlighting their characteristics and performance considering similar conditions of execution. The robustness of each control when acting on a non-linear system is investigated. All control techniques are applied in three different tests: i) step-type reference signal, without load application, ii) reference signal with amplitude variation, without load application and iii) step-type reference signal, with load application. The techniques present satisfactory performance in the execution of the proposed control, depending, therefore, on the analysis of the system to be implemented to determine the appropriate method.Item Complexidade natural de sistemas com base em análise de sensibilidade(Universidade Federal de Goiás, 2020-09-30) Gomes, Viviane Margarida; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Wainer, Gabriel Andres; Peretta, Igor Santos; Pinheiro Neto, Daywes; Martins, WeberThis work proposes a methodology for analyzing systems based on a particular measure of complexity, called the natural complexity of the system. This measure corresponds to the proper level of complexity of each system, characterized by the region of optimized configurations. Given the optimal or optimized solution, the sensitivity analysis is performed to define the impact generated at the output of the system due to variations in the input parameters. The proposed methodology comprises: i) sensitivity analysis metrics, ii) system complexity metrics based on weighted connections, iii) analysis of the system using natural complexity as a reference and iv) development of models for application of the methodology. The complexity metric uses the sensitivity indices of the parameters to define the relevance values of the connections, in order to establish a relationship between the parties and the whole. The results point to the complexity metric as a mechanism for synthesizing the configuration, arrangement, performance and workload of the system in a single measure. Regarding the measure of natural complexity, it may be used as a reference of the desired level of complexity, since it was significantly different from the measures obtained under overload or idle conditions. Thus the natural complexity may correspond to the minimum complexity value of the system in regular activity. The proposed complexity metric strengthened the assertion that every system exhibits some level of complexity. Thus, it may be said that complexity is the totality of the system in interaction, with its own internal dynamics and its own environmental flows.Item Otimização da força contra eletromotriz e do torque eletromagnético mediante a modificações nos parâmetros estruturais de uma máquina síncrona de ímãs permanentes(Universidade Federal de Goiás, 2021-08-02) Jesus, Luiz Henrique Reis de; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Paula, Geyverson Teixeira de; http://lattes.cnpq.br/0140145167826333; Paula, Geyverson Teixeira de; Pereira, William César de Andrade; Almeida, Thales Eugenio Portes de; Suetake, Marcelo; Brito, Leonardo da CunhaThis work aims to present an approach to the optimization process of a surface mounted permanent magnet synchronous machine (SM-PMSM) using the Tensors method, as well as methods and techniques for parametric optimization and topological optimization. It evaluates the behavior of the Back-Electromotive Force (Back-EMF) operating at no load and under load, as well as the behavior of the electromagnetic torque. The optimized parameters directly relate to the saturation of the machine as the electromagnetic load is increased (nominal load). The optimization process allows a reduction in the electromagnetic torque ripple, keeping the back-electromotive force unchanged. The results for the optimization of the Back-Electromotive Force presented variations lower than 0,5% when compared to its behavior operating at no load, with its behavior operating under load. For the electromagnetic torque optimization process, the results achieved provided to the SM-PMSM project a reduction in the electromagnetic torque ripple of approximately 37% and a reduction in the structural volume of 38,23%. Finally, optimization techniques and methodologies were compared regarding the results and objectives proposed for the optimization of the permanent magnet synchronous machine under study.
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