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International Conference on Electrical and Electronics engineering, ELECO

作者： Abdullah Türkmen M. Yusuf Korkut Mustafa Erdem Ömer Gönül Volkan Sezer Mechatronics Graduate Program Istanbul Technical University Istanbul TURKEY Energy Institute Istanbul Technical University Istanbul TURKEY Dept. of Control and Automation Engineering Istanbul Technical University Istanbul TURKEY

Inverted pendulum systems have an important place in practice for control problems due to their nonlinear structures. It is a very difficult task to control the orientation and speed of objects and robots which are free in three dimensions. These systems constitute the substructure of many advanced systems. Conventional actuators may not be used in such applications due to various limitations. Under these circumstances usage of reaction wheels come into prominence. Reaction wheel based systems are used for orienting, coordinating and balancing of spacecraft, transport systems, and other such systems. In this study, dual axis self-balancing reaction wheel based inverted pendulum system which is a basis for many complex systems has been designed, manufactured and controlled.

关键词： Wheels Mathematical model DC motors Gravity State feedback Torque Aluminum

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Design of an Autonomous Aerator

Design of an Autonomous Aerator

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IEEE International Conference on Emerging Technologies and Factory automation

作者： Rilene Carolina Goelzer Letieri ávila Deliel Oliveira Vinícius M. de Oliveira Control and Automation Engineering Federal University of Rio Grande Rio Grande RS Brasil Graduate Program in Computer Engineering Federal University of Rio Grande Rio Grande RS Brasil Universidade Federal do Rio Grande Rio Grande RS BR

Aquaculture has resorted to the use of technology to make control of important variables and improve production. There were two problems observed in the Marine Aquaculture Station - EMA of the Federal University of Rio Grande, more specifically related to the aeration of the culture tanks to pisciculture and carniciculture. Firstly, the high energy consumption of the paddle aerators was identified, due to the continuous need to oxygenate the water. Subsequently, it was noted that static aerators do not aerate the water evenly and they require that their placement be done manually by technicians or assistants. Thus, the article proposes a design of an autonomous aerator with electric power coming from a photovoltaic solar energy system. In the sequence, a navigation system for the aerator is proposed along the tank, based on a differential performance of the motors connected to the paddle.

关键词： Solar Energy Aquaculture Aerator control

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Charcoal and bio-oil production by using a microwave-assisted pyrolysis process

Charcoal and bio-oil production by using a microwave-assiste...

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AISTech 2016 Iron and Steel Technology Conference

作者： Oliveira, Tiago Luís Assis, Paulo Santos Leal, Elisângela Martins Dos Santos Morais, Anderson Ribeiro, Kelly Lopez REDEMAT-Graduate Program in Material Engineering School of Mining Federal University of Ouro Preto MG Brazil Department of Control Automation and Mechanical Engineering School of Mining Federal University of Ouro Preto MG Brazil ONDATEC S.A. Clean Charcoal Technology Innovare Technological Research Av. Cel. Cacildo Arantes 377 Uberaba MG Brazil

ISBN: (纸本)9781935117551

Bio-energy from biomass can be used as renewable energy to reduce CO2 emission in some industrial processes. Fast pyrolysis has emerged as the most promising technology to convert organic materials into liquid fuels at a short time but it still faces some technical challenges in improving product yield, its quality and process energy efficiency. Microwave assisted pyrolysis (MAP) of biomass provides distinctive environment to solve these challenges. In this paper, the pyrolysis of Lemon Eucalyptus was investigated using microwave energy as the heat source, and the yield and characteristics of the pyrolysis oils (i.e. elemental analysis, hydrocarbon composition, and potential fuel properties) and gases are presented and discussed. Here, a pilot unit with 150 kg per hour capacity using MAP technique was built in order to evaluate the energy potential of gases (non-condensable gases-NCG) and liquid (condensable gases-CG) of a biomass pyrolysis plant. The pyrolysis process was in continuous mode and in two stages, biomass drying and pyrolysis, with charcoal production, pyrolysis gas and bio-oil. The results showed that about 63% of the raw material was converted to charcoal and 37% to pyrolysis gas and bio-oil. In the pyrolysis gas fraction, 46% corresponds to the nitrogen from the air. There was a 1638 kg of air entering in the system, which was verified by mass balance. This air inlet implies several drawbacks, mainly explosion risks. The bio-oil fraction was analyzed showing that there was a 45% of pyroligneous gas followed by about 33% of water. It can be seen that the lower calorific value of condensable gases can be increased with the removal of water from its composition. The study of energy availability showed an averaged value of 5.60 MWh of thermal energy per ton of charcoal produced in the prototype.

关键词： Biomass

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Radio frequency safety device applied to chair children in cars 28

Radio frequency safety device applied to chair children in c...

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28th European Modeling and Simulation Symposium, EMSS 2016

作者： Da Cunha Santos, Robson De Oliveira, Karina Barros Moreira, Marcos Antônio Cruz Neto, Severino Joaquim Correia Cunha, Gerson Gomes Fluminense Federal Institute Campus Macaé Engineering and Automation Control 164 km Amaral Peixoto Road Brazil Estácio de Sá University General Alfredo Bruno Gomes Martins Highway s/n Braga-Cabo Frio/RJ Brazil Federal University of Rio de Janeiro Alberto Luiz Coimbra Institute Graduate Engineering and Research Civil Engineering Program COPPE UFRJ Brazil

ISBN: (纸本)9788897999683

The article aims to present a prototype device able to identify and warn those responsible when there is a possibility of forgetting of a child inside the car, thus avoiding an injury to the health of the child or even death. To this effect electronic sensors able to detecting the presence of the child on the chair have been used, microcontrollers (Arduino Uno, Arduino Nano) programmed to perform the data processing, wireless communication module (XBee) to perform the transfer of data between the chair, and a specific key chain, and ultimately actuators responsible for a possible warning against forgetting a child inside the car. Generally speaking, this article comprises concepts involving instrumentation and programming. This paper has the effect of academic results, nowadays there are not many studies concerning the proposed theme and its application is highly viable because of the relatively low cost, making it accessible to all social classes.

关键词： Microcontrollers

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Fuzzy inference about wind resources in urban environment 3

Fuzzy inference about wind resources in urban environment

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3rd International Workshop on Simulation for Energy, Sustainable Development and Environment, SESDE 2015

作者： Moreira, Marcos Antonio Cruz Rosenhaim, Roberto Santos, Robson Da Cunha Cunha, Gerson Gomes De Araújo Holanda, Thaiane Fagundes Fluminense Federal Institute Automation and Control Engineering Environmental Engineering Program Macaé Brazil Fluminense Federal Institute Automation and Control Engineering Macaécio Brazil Control Engineering Department Federal Institute and Estacio de Sá University Cabo Frio Brazil Alberto Luiz Coimbra Institute Graduate Engineering and Research Civil Engineering Program/COPPE/UFRJ Federal University of Rio de Janeiro Brazil Fluminense Federal University Macaécio Brazil

ISBN: (纸本)9788897999522

The advancement of renewable energy technology gave rise to the implementation of small wind towers in urban areas. A major problem in predicting the use of such facilities is the difficulty of measuring in micro-regions that suffer different influences of the surrounding environment. Thus a wind tower may be installed where it does not work properly. Fuzzy inference systems try to approach the thinking process of human language allowing for a more assertive decision process. For the development of a fuzzy inference system dealing with this issue it was necessary to determine the variables that most impact on the variation of the wind distribution in micro urban environment as well as using data from automatic weather stations which allow to estimate the wind regime for a macro region. These data are fed in a fuzzy inference system that outputs an adequacy rank for sitting a small wind tower.

关键词： Wind power

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A hybrid evolutionary probabilistic forecasting model applied for rainfall and wind power forecast

A hybrid evolutionary probabilistic forecasting model applie...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Guilherme G. Netto Alexandre C. Barbosa Mateus N. Coelho Arthur R. L. Miranda Vitor N. Coelho Marcone J. F. Souza Frederico G. Guimarães Agnaldo J. R. Reis Department of Control and Automation Engineering Universidade Federal de Ouro Preto Ouro Preto MG Brazil Graduate Program of Electrical Engineering Univesidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto MG Brazil Departament of Electrical Engineering Univesidade Federal de Minas Gerais Belo Horizonte MG Brazil

Several works in the literature so far have been focused on deterministic point forecasts, which, usually, indicates the conditional mean of future observations. An increasing need for generating the entire conditional distribution of future observations has been required for the new generation of soft sensors. This study aims the probabilistic forecasts, reporting the use of a hybrid fuzzy forecasting model applied in two different forecasting problems. Our adapted model is applied to predict the rain of the city of Vitoria, in the state of Espírito Santo, Brazil. Real data from a wind farm, provided by the Irish EirGrid institute, was used for analyzing the proposal over a real time series with high fluctuations. Due to the stochasticity of the the hybrid model, which is calibrated through the use of an evolutionary metaheuristic, we adapted it in order to generate future using quantile regression. Computational experiments indicated the ability of the model in finding useful probabilistic quantiles, which were flexible enough in order to limit the lower and upper bounds of the historical datasets. While the probabilistic quantiles suggested the probability of rain and its magnitude, they were also able to predict expected ranges of the amount of energy generated from the wind farm.

关键词： Forecasting Predictive models Wind forecasting Probabilistic logic Wind power generation Adaptation models Time series analysis

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A Hybrid Deep Learning Forecasting Model Using GPU Disaggregated Function Evaluations Applied for Household Electricity Demand Forecasting

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Energy Procedia 2016年 103卷 280-285页

作者： Vitor N. Coelho Igor M. Coelho Eyder Rios Alexandre S.T. Filho Agnaldo J.R. Reis Bruno N. Coelho Alysson Alves Guilherme G. Netto Marcone J.F. Souza Frederico G. Guimarães Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Instituto de Pesquisa e Desenvolvimento de Tecnologias Ouro Preto Brazil Department of Computer Science State University of Rio de Janeiro Rio de Janeiro Brazil Institute of Computer Science Fluminense Federal University Niteroi Brazil Department of Control Engineering and Automation Universidade Federal de Ouro Preto Ouro Preto Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais BeloHorizonte Brazil

As the new generation of smart sensors is evolving towards high sampling acquisitions systems, the amount of information to be handled by learning algorithms has been increasing. The Graphics Processing Unit (GPU) architectures provide a greener alternative with low energy consumption for mining big-data, harnessing the power of thousands of processing cores in a single chip, opening a widely range of possible applications. Here, we design a novel evolutionary computing GPU parallel function evaluation mechanism, in which different parts of time series are evaluated by different processing threads. By applying a metaheuristics fuzzy model in a low-frequency data for household electricity demand forecasting, results suggested that the proposed GPU learning strategy is scalable as the number of training rounds increases.

关键词： Microgrid Household Electricity Demand Deep Learning Graphics Processing Unit Parallel forecasting model Big Time-series Data

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Photovoltaic power plant submitted to voltage sags: Model and performance evaluation 13

Photovoltaic power plant submitted to voltage sags: Model an...

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13th IEEE Brazilian Power Electronics Conference and 1st Southern Power Electronics Conference, COBEP/SPEC 2016

作者： Pires, Igor A. Machado, Alysson Foureaux, Nicole Silva, Sidelmo M. Filho, Braz J. Cardoso Brito, Jose Department of Electronic Engineering - UFMG Belo Horizonte - MG Brazil Control and Automation Engineering Undergraduate Course - UFMG City - Belo Horizonte - MG Brazil Electrical Engineering Graduate Program- UFMG Belo Horizonte - MG Brazil Department of Electrical Engineering - UFMG Belo Horizonte - MG Brazil Companhia de Eletricidade Do Estado da Bahia Salvador-BA Brazil

ISBN: (纸本)9781479987795

This paper brings the PV model of a real PV farm installation with a total power of 917 kW. All the elements of the PV farm (panels and inverter) are described. Simulation on PSCAD and experimental results at the installation are reported. The PV model is submitted to voltage sags originated in the grid as well as their impact on the photovoltaic power plant. © 2015 IEEE.

关键词： Solar panels

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Author Correction: A consensus protocol for functional connectivity analysis in the rat brain

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Nature neuroscience 2023年 2023 Apr 18页

作者： Joanes Grandjean Gabriel Desrosiers-Gregoire Cynthia Anckaerts Diego Angeles-Valdez Fadi Ayad David A Barrière Ines Blockx Aleksandra Bortel Margaret Broadwater Beatriz M Cardoso Marina Célestine Jorge E Chavez-Negrete Sangcheon Choi Emma Christiaen Perrin Clavijo Luis Colon-Perez Samuel Cramer Tolomeo Daniele Elaine Dempsey Yujian Diao Arno Doelemeyer David Dopfel Lenka Dvořáková Claudia Falfán-Melgoza Francisca F Fernandes Caitlin F Fowler Antonio Fuentes-Ibañez Clément M Garin Eveline Gelderman Carla E M Golden Chao C G Guo Marloes J A G Henckens Lauren A Hennessy Peter Herman Nita Hofwijks Corey Horien Tudor M Ionescu Jolyon Jones Johannes Kaesser Eugene Kim Henriette Lambers Alberto Lazari Sung-Ho Lee Amanda Lillywhite Yikang Liu Yanyan Y Liu Alejandra López-Castro Xavier López-Gil Zilu Ma Eilidh MacNicol Dan Madularu Francesca Mandino Sabina Marciano Matthew J McAuslan Patrick McCunn Alison McIntosh Xianzong Meng Lisa Meyer-Baese Stephan Missault Federico Moro Daphne M P Naessens Laura J Nava-Gomez Hiroi Nonaka Juan J Ortiz Jaakko Paasonen Lore M Peeters Mickaël Pereira Pablo D Perez Marjory Pompilus Malcolm Prior Rustam Rakhmatullin Henning M Reimann Jonathan Reinwald Rodrigo Triana Del Rio Alejandro Rivera-Olvera Daniel Ruiz-Pérez Gabriele Russo Tobias J Rutten Rie Ryoke Markus Sack Piergiorgio Salvan Basavaraju G Sanganahalli Aileen Schroeter Bhedita J Seewoo Erwan Selingue Aline Seuwen Bowen Shi Nikoloz Sirmpilatze Joanna A B Smith Corrie Smith Filip Sobczak Petteri J Stenroos Milou Straathof Sandra Strobelt Akira Sumiyoshi Kengo Takahashi Maria E Torres-García Raul Tudela Monica van den Berg Kajo van der Marel Aran T B van Hout Roberta Vertullo Benjamin Vidal Roël M Vrooman Victora X Wang Isabel Wank David J G Watson Ting Yin Yongzhi Zhang Stefan Zurbruegg Sophie Achard Sarael Alcauter Dorothee P Auer Emmanuel L Barbier Jürgen Baudewig Christian F Beckmann Nicolau Beckmann Guillaume J P C Becq Erwin L A Blezer Radu Bolbos Susann Boretius Sandrine Bouvard Eike Budinger Joseph D Buxbaum Diana Cash Victor Donders Institute for Brain Behaviour and Cognition Radboud University Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Department for Medical Imaging Radboud University Medical Center Nijmegen The Netherlands. joanes.grandjean@radboudumc.nl. Cerebral Imaging Centre Douglas Mental Health University Institute Verdun QC Canada. Integrated Program in Neuroscience McGill University Montreal QC Canada. Bio-imaging Lab University of Antwerp Antwerp Belgium. µNEURO Research Centre of Excellence University of Antwerp Antwerp Belgium. Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro Mexico. Biological and Biomedical Engineering McGill University Montreal QC Canada. McConnell Brain Imaging Centre McGill University Montreal QC Canada. Montreal Neurological Institute McGill University Montreal QC Canada. UMR INRAE/CNRS 7247 Physiologie des Comportements et de la Reproduction Physiologie de la reproduction et des comportements Centre de recherche INRAE de Nouzilly Tours France. Department of Neurology and Neurosurgery McGill University Montreal QC Canada. Center for Animal MRI University of North Carolina at Chapel Hill Chapel Hill NC USA. Department of Neurology University of North Carolina at Chapel Hill Chapel Hill NC USA. Biomedical Research Imaging Center University of North Carolina at Chapel Hill Chapel Hill NC USA. Preclinical MRI Champalimaud Research Champalimaud Centre for the Unknown Lisbon Portugal. Laboratoire des Maladies Neurodégénératives Molecular Imaging Research Center (MIRCen) Université Paris-Saclay Commissariat à l'Énergie Atomique et aux Énergies Alternatives (CEA) CNRS Fontenay-aux-Roses France. Departamento de Neurobiología Conductual y Cognitiva Instituto de Neurobiología Universidad Nacional Autónoma de México Campus Juriquilla Querétaro México. Translational Neuroimaging and Neural Control Group High-Field Magnetic Resonance Max Planck Institute for Biological Cyberneti

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Evolving Ensemble of Fuzzy Models for Multivariate Time Series Prediction

Evolving Ensemble of Fuzzy Models for Multivariate Time Seri...

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IEEE International Conference on Fuzzy Systems

作者： Lourenco Bueno Pyramo Costa Israel Mendes Enderson Cruz Daniel Leite the Dept. of Graduate Program in Electrical Engineering Pontifical Catholic University of Minas Gerais Belo Horizonte Brazil the Dept. of Electronics Federal Center for Technological Education of Minas Gerais Nepomuceno Brazil the Control and Automation Research Group Dept. of Engineering Federal University of Lavras Brazil

ISBN: (纸本)9781467374293

Weather modeling and prediction has been quite a challenge over the years. Predictions based on climatic models whose dynamical behavior is nonlinear, nonstationary, and based on high order difference equations is a tough task and usually requires a demanding and non-intuitive tuning expertise. This paper suggests an ensemble of evolving fuzzy models for multivariate time series prediction. The proposed ensemble approach is able to model the weather dynamics from data streams concerning variables such as wet bulb temperature, atmospheric pressure, maximum temperature, and relative humidity of the air. The purpose is to predict rainfalls 5 days ahead while providing a linguistic description of the reasoning used to give the predictions. Empirical results show that the ensemble-based fuzzy evolving modeling approach outperforms other evolving approaches in terms of accurate predictions.

关键词： Evolving Ensemble Fuzzy Models Multivariate Time Series Prediction

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