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Analyses of Photovoltaic Systems Performance with Fuzzy Inference Systems and Bayesian Networks

Analyses of Photovoltaic Systems Performance with Fuzzy Infe...

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Power Electronics and Control (SEPOC), Seminar on

作者： Nicole Polityto Cremasco Myriam Regattieri De Biase da Silva Delgado Jair Urbanetz Junior Luiz Ledo Mota Melo Jorge Assade Leludak Keiko Verônica Ono Fonseca Program of Post-Graduation of Electrical Engineering and Industrial Informatics(CPGEI) of Federal University of Technology of Paraná(UTFPR) Program of Post-Graduation of Electrical Engineering and Industrial Informatics(CPGEI) of the Federal University of Technology of Paraná(UTFPR) Program of Post-Graduation in Energy Systems of Federal University of Technology of Paraná(UTFPR Department of Electrical Engineering (DAELT)) Federal University of Technology of Paraná(UTFPR) Curitiba Brazil

Renewable energy sources have been increasingly targeted as an alternative for reducing fossil fuel emissions. This scenario requires a better understanding of energy systems' performance and limitations, notably using photovoltaic setups under diverse meteorological conditions and determining device measurement uncertainties. Accordingly, this study conducts a performance evaluation of a photovoltaic system of copper, indium, and gallium (di)selenide technology. It compares the results provided by a reference normalized equation with two interpretable artificial intelligence techniques, Fuzzy Inference System and Bayesian Networks, when temperature is also considered. In the experiments, the study found significant percentage differences between the normalization procedure and the fuzzy system on days with lower irradiation values. On the other hand, the results provided by Bayesian networks presented lower difference percentages in relation to the normalization equation values.

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Development and Validation of a Digital Twin for a Commercial Mobile Robot

Development and Validation of a Digital Twin for a Commercia...

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IEEE International Conference on Robotic Computing (IRC)

作者： Wilson Eduardo Barioni Igor Pardal Latini Carina Toledo Scoparo Barioni Flavio Neves L.V.R. Arruda Marco Teixeira RCPGEI - UTFPR Curitiba Parana Brazil Graduate Program in Electrical and Computer Engineering (CPGEI) Universidade Tecnologica Federal do Parana (UTFPR) Curitiba Parana Brazil Graduate Program in Informatics (PPGIa) Pontifícia Universidade Católica do Paraná (PUCPR) Curitiba Brazil CPGEI - UTFPR Curitiba Parana Brazil Universidade Positivo Paraná Brasil PPGIa - PUCPR Curitiba Parana Brazil

ISBN: (数字)9798331521554

ISBN: (纸本)9798331521561

In recent decades, there has been a significant increase in the presence of robots in the daily operations of industries. Automated Guided Vehicles (AGVs) used in industrial environments are gaining prominence due to their numerous applications, ranging from logistic tasks such as material transport to more complex process tasks like replacing conveyor belts in production lines. For a mobile robot to operate in these environments, it must possess skills to perform its functions and ensure safety. In this regard, simulating a computational model of a real autonomous system can contribute to developing new operational strategies. The objective of this work is to explore the use of a Digital Twin for an Automated Guided Vehicle (AGV), aiming to design and validate navigation and obstacle avoidance algorithms, with the intent to optimize the operation of these devices in industrial environments. In the current study, the AGV G3R1000 was used, which was modeled in detail in FUSION 360 software, along with a production line from the AGVS company in Brazil. As validation, the digital robot was used to design the navigation software using the PID control system and obstacle avoidance using Fuzzy control. The algorithm developed in the digital robot was applied to the real robot, and a performance comparison was made. In conclusion, it is possible to use the simulated robot to design algorithms for the real robot, saving resources such as time and equipment.

关键词： Remotely guided vehicles Service robots Navigation Computational modeling Software algorithms Production Software Digital twins Safety Mobile robots

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Estimating the 3D center point of an object with Kinect sensor RGB-D images

Estimating the 3D center point of an object with Kinect sens...

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IEEE Latin American Robotics Symposium, LARS

作者： Gustavo Fardo Armênio João Alberto Fabro Renzo De Rosa Tognella Felipe Pierre Conter Marlon Vaz De Oliveira Everson De Souza Silva Computer Engineering Course - UTFPR Curitiba PR Brazil PPGCA-Graduate Program on Applied Informatics UTFPR-Federal University of Technology - Paraná Curitiba PR Brazil Information System Course - UTFPR Curitiba PR Brazil UNILA - University of Latin American Integration Foz do Iguaçu PR Brazil CPGEI-Graduate Program on Electrical Engineering and Industrial Informatics/UTFPR IFPR- Federal Institute of Technology - Paraná Pinhais PR Brazil PPGCA-Graduate Program on Applied Informatics UTFPR Curitiba Brazil

This article describes the estimation of a 3D point using a Kinect sensor and the Robot Operating System (ROS) along with You Only Look Once (YOLO) for object detection. The Kinect sensor provides RGB-D images, which are used to create a Point Cloud representing the geometry of the environment. ROS is used as a robotics development framework, while YOLO is employed to identify objects in the scene. The article presents the packages used, the datasets used for measurement, and the configuration of ROS and YOLO. Additionally, the functionalities of RViz, a 3D visualization tool used in the tests, are explored. Furthermore, it covers the methods employed, the acquired data, and an analysis of the error margin in relation to the measurement of the distance between the Kinect and the object. The findings and techniques presented in this study contribute to addressing the challenges faced in the RoboCup@Home competition, specifically in the context of object manipulation tasks.

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Running Cooperative Tasks in a Multi-Robot System with Cyber-Physical Features

Running Cooperative Tasks in a Multi-Robot System with Cyber...

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IEEE Latin American Robotics Symposium, LARS

作者： Héber Renato Fadel de Morais João Paulo Lima Silva de Almeida Lúcia Valéria Ramos de Arruda Graduate Program in Electrical Engineering and Industrial Informatics (CPGEI) Federal University of Technology - Paraná Curitiba Brazil Federal Institute of Paraná Jacarezinho Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

This paper develops a system based on cyber-physical concepts to support robots in tasks that require cooperative work and information sharing. The work's inspiration is the need of the 4.0 industry for cobots visiting different workstations to assist human workers, for tools and raw material transportation, and other tasks. As in any industrial environment, unexpected events may occur, and the cobots must face them, reducing their effects on the production line. In this work, multiple robots (MR) managed by a system with cyber-physical (CP) features cooperate in an experimental dynamic environment to safely accomplish several tasks. For this, the robots must visit targets (analogous to workstations) in an orderly way, while one support robot must deal with oil stains on the environment's floor detected along the robots' navigation (unexpected event). The proposed CP-MR system is evaluated through experimental results allowing a performance analysis.

关键词： Visualization Service robots Federated learning Information sharing Robot sensing systems Workstations Multi-robot systems

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WaiterBot: Comparison of Fuzzy Logic Approaches for Obstacle Avoidance in Dynamic Unmapped Environments Using a Laser Scanning System (LiDAR)

WaiterBot: Comparison of Fuzzy Logic Approaches for Obstacle...

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IEEE Latin American Robotics Symposium, LARS

作者： Jonathan Cerbaro Dieisson Martinelli André Schneider de Oliveira João Alberto Fabro ederal University of Technology - Paraná (UTFPR) Graduate Program on Electrical Engineering and Applied Informatics (CPGEI) Advanced Laboratory of Embedded Systems and Robotics (LASER) Curitiba Paraná Brazil

ISBN: (数字)9780738111537

ISBN: (纸本)9781665419857

Fuzzy logic is a control technique commonly applied in mobile robotics. This paper contains the analysis of three implementations of control systems for obstacle avoidance of a mobile robot. The simulation environment simulate situations with both fixed and dynamic obstacles - like people walking - aiming to compare the fuzzy control approach most suitable to avoid different kinds of obstacles. The analyzed approaches differ by segmenting the sensor data (provided by a LiDAR sensor) into three regions, five regions or by considering only the position of the nearest obstacle. The three approaches were tested in scenarios containing different obstacles and in a simulation where the robot delivers to tables in a dynamic environment, simulating a social event as an application example of a waiter robot.

关键词： Robot sensing systems Robots Collision avoidance Robot kinematics Laser radar Fuzzy logic Input variables

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Training of an Artificial Neural Network with Backpropagation algorithm using notification oriented paradigm

Training of an Artificial Neural Network with Backpropagatio...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： Fenando Schütz João A. Fabro Carlos R. E. Lima Adriano F. Ronszcka Paulo C. Stadzisz Jean M. Simão Graduate School in Electrical Engineering and Industrial Informatics (CPGEI) Federal University of Technology - Paraná (UTFPR) - Av. Sete de Setembro 3165. Curitiba-PR Brazil. 80-230-901 Graduate School of Applied Computing (PPGCA) Federal University of Technology - Parana (UTFPR) Curitiba PR Brazil Graduate School in Electrical Engineering and Industrial Informatics (CPGEI)

When implementing Artificial Neural Networks with imperative programing languages, the resulting programs are usually highly coupled. This problem usually hampers distribution over multiple processors, especially when the ANN executes on general-purpose processors. An emerging technique called Notification Oriented Paradigm (NOP) facilitates the development of distributed and decoupled systems, and minimizes the amount of processing calculations, while avoiding structural and temporal redundancies in the logical-causal evaluation. These advantages seem to be relevant to parallel systems, especially in the case of ANNs. In this sense, this paper presents the development of a Multi-Layer Perceptron using Backpropagation training algorithm, based on the concepts of NOP in its implementation. The overall performance of NOP implementation was not so good in comparison with the Imperative Paradigm (IP) implementation, because the current materialization of NOP (framework) is still based on a single thread implementation. Even though, this implementation proved to be plausible and decoupled, as well as parallelizable according the inherent parallelism of ANNs, conceptually intrinsic on the NOP.

关键词： Artificial neural networks Training Neurons Computer architecture Hardware program processors

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Analysis of combined ultrasound therapy and medium frequency current in abdominal adiposity

Analysis of combined ultrasound therapy and medium frequency...

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13th Mediterranean Conference on Medical and Biological engineering and Computing 2013, MEDICON 2013

作者： Gripp, Paula Alessandra Garcia Stadnik, A.M.W. Bona, A.A. Neves, E.B. UTFPR/Graduate Program in Biomedical Engineering Curitiba Brazil UTFPR/Department of Electrical Engineering and Industrial Informatics Curitiba Brazil

ISBN: (纸本)9783319008455

Brazil is the second country in the world in aesthetic surgical procedures, with 905,000 procedures, being behind only the U.S., according to information corresponding to the year 2011 from the International Society of Aesthetic Plastic Surgery (ISAPS) and the Brazilian Society of Plastic Surgery (BSPS). Given this scenario, we chose to study the adipose cells, which are a organ with intense metabolic and endocrine activity. Accumulated in excess adipocytes causes the disadvantages metabolic and endocrine in the organism, leading to obesity in general and located. This research referred to obesity marked by deposition in the abdominal area, that is denominated central or androide obesity, in the case of a localized adiposity. The objective of the research was to analyze the effects of therapeutic ultrasound and medium frequency current in this particular type of adiposity. The therapeutic protocol consisted of the utilization therapy of therapeutic ultrasound 3 MHz and medium frequency current (1 kHz, with Bursts of 2 ms), performed in ten sessions of 40-minute each. The sample consisted of 16 women, of whom 14 have finalized treatment. The assessment instruments used were: percentage of total body fat by bioimpedance, skinfold measurement in the region where localized adiposity was. We observed the reduction in measures measured in abdominal circumference and percentage decrease in total body fat measured on a digital scale bipolar bioimpedance, as well as the decrease measured by skinfold plicometer in all patients submitted to treatment. The results of submission to the treatment of Combined Therapy can be considered satisfactory, due the record in reducing the parameters analyzed, despite being necessary to a more thorough study on the subject and scientific substantiation in a larger sample. Based on this study has observed a dearth of studies on the subject so that the same password be a non-invasive alternative in the treatment of localized adiposity and derm

关键词： Ultrasonics

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An Extension to the Contract-Net Protocol Applied to the Transport Planning Problem of Oil Products

An Extension to the Contract-Net Protocol Applied to the Tra...

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Workshop and School of Agent Systems, their Environment and Applications (WESAAC)

作者： Roni F. Banaszewski Kelvin E. Nogueira Jean M. Simão Lucia V. Arruda Cesar A. Tacla Graduate Program in Electrical Engineering and Industrial Computer Science (CPGEI) Federal University of Technology of Paraná (UTFPR) Curitiba Brazil

In supply chains of petroleum industry, maintaining a proper inventory level for multiple petroleum products is a crucial issue. Basically, this chain has several elements like producer bases, consumer bases and terminals that are linked by means of a multi-modal transport network. These elements must cooperate to achieve the global goal of the system with a minimized cost. To achieve this goal, this paper presents a multiagent protocol for simultaneous negotiations based on the Contract-Net and the application of this in the chain aforementioned. As a result, this protocol proved to be very efficient to return a feasible solution in a low processing time.

关键词： Computational modeling Waste materials Protocols Educational institutions Planning Proposals Conferences

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Empirical Studies on Application of Genetic Algorithms and Ant Colony Optimization for Data Clustering

Empirical Studies on Application of Genetic Algorithms and A...

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Computer Science Society (SCCC) International Conference Chilean FLAGGED

作者： Thelma Elita Colanzi Wesley Klewerton Guez Assunção Aurora Trinidad Ramirez Pozo Ana Cristina B. Kochem Vendramin Diogo Augusto Barros Pereira Computer Science Postgraduate Program Federal University of Paraná (UFPR) Curitiba Paraná Brazil Graduate School of Electrical Engineering and Computer Science (CPGEI) Federal Technological University of Paraná (UTFPR) Curitiba Paraná Brazil Informatics Department (DAINF)

Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), have been applied in order to increase the clustering algorithm performance. GA and ACO-based clustering algorithms are capable of efficiently and automatically forming natural groups from a pre-defined number of clusters. This paper presents a GA and an ACO algorithm to the clustering problem. Both algorithms were refined using local search in order to improve the clustering accuracy. The results are compared on numeric UCI databases.

关键词： Clustering algorithms Search problems Equations Mathematical model Gallium Genetic algorithms Memetics

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Multivariable nonlinear boiler power plant identification through neural networks and Particle Swarm Optimization approaches

Multivariable nonlinear boiler power plant identification th...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Fábio A. Guerra Helon V. H. Ayala André E. Lazzaretti Marcio R. Sans Leandro S. Coelho Cesar A. Tacla Eletroelectronics Department (DPEE) Electrical System Division (DVSE) Centro Politécnico da UFPR LACTEC-Institute of Technology for Development Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program (LAS/PPGEPS) Pontifical Catholic University of Paraná Curitiba Parana Brazil Graduate Program in Eletrical Engineering and Industrial Informatics (CPGEI) Federal University of Technology Parana Curitiba Parana Brazil

The identification of nonlinear systems with artificial neural networks models has been successfully used in many applications. Most processes in industry are characterized by nonlinear and time-varying behavior. In this context, the identification of mathematical models for nonlinear systems is vital in many fields of engineering. The Radial Basis Function Neural Network (RBF-NN) is a powerful approach for nonlinear identification and can be improved using Particle Swarm Optimization (PSO) approaches. This paper presents a multivariable nonlinear system identification using RBF-NN combined with standard PSO and Constriction Factor PSO (CFPSO) approaches in order to determine the RBF-NN parameters. RBF-NN is considered to be a good choice for black-box modeling problems due to its rapid learning capacity and, therefore, has been applied successfully to nonlinear time series modeling and nonlinear identification. On the other hand, PSO was inspired by the choreography of bird flocks and fish schools and can be seen as a distributed behavior algorithm that performs multidimensional search. Furthermore, promising simulation results from performance analysis of the proposed RBF-NN with PSO training approaches are presented and discussed in this paper showing promising results.

关键词： Artificial neural networks Boilers Neurons Modeling Power generation Optimization Nonlinear systems

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