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World engineering Education Forum - Global engineering Deans Council (WEEF-GEDC)

作者： Ricardo A. Diogo André L.A.C. Venâncio Maria Angela M. Roveredo Santos Eduardo F.R. Loures Neri dos Santos Knowledge Engineering&Management Graduate Program Federal University of Santa Catarina Florianopolis Brazil Industrial&Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Brazil Control and Automation Engineering/Mechatronics Engineering Pontifical Catholic University of Parana Curitiba Brazil

ISBN: (纸本)9781665424899

This paper presents the context of the Ubiquitous Computing course carried out in an Industrial engineering undergraduate program throughout 2020 and the first semester of 2021. This course took advantage of the Institutional Modernization program led by the control and automation engineering Undergraduate program, which consists in the modernization of undergraduate engineering programs at the Pontifical Catholic University of Paraná. The course aimed to help develop competencies, i.e., a set of knowledge, skills, and attributes aligned with Student Outcomes suggested by ABET. Also, the course proposal brought the productive sector very close to the academic environment, proposing real engineering problems as challenges. However, what are the methods and assessment tools for practical learning in a course with modern elements? This paper proposed the flipped learning and the Challenge-Based Learning Framework with the support of the CDIO Framework as learning methodologies to answer such question. Additionally, quizzes, tests, presentations, rubrics, and peer evaluation were applied as assessment tools to measure the student's progress. Finally, students were listened to about their perceptions during the course. The results suggested that the learning methodologies and assessment tools are suitable for the course context, although some improvements are expected for the following course offers. Moreover, students approved the initiative to bring in real challenges proposed by companies, the mentoring hours, and the feedback about the projects.

关键词： automation Companies Industrial engineering Ubiquitous computing Proposals Mentoring engineering education

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Temporal networks provide a unifying understanding of the evolution of cooperation

arXiv

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arXiv 2023年

作者： Li, Aming Meng, Yao Zhou, Lei Masuda, Naoki Wang, Long Center for Systems and Control College of Engineering Peking University Beijing100871 China Center for Multi-Agent Research Institute for Artificial Intelligence Peking University Beijing100871 China School of Automation Beijing Institute of Technology Beijing100081 China Department of Mathematics State University of New York at Buffalo BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260 United States

Understanding the evolution of cooperation in structured populations represented by networks is a problem of long research interest, and a most fundamental and widespread property of social networks related to cooperation phenomena is that the node’s degree (i.e., number of edges connected to the node) is heterogeneously distributed. Previous results indicate that static heterogeneous (i.e., degree-heterogeneous) networks promote cooperation in stationarity compared to static regular (i.e., degree-homogeneous) networks if equilibrium dynamics starting from many cooperators and defectors is employed. However, the above conclusion reverses if we employ non-equilibrium stochastic processes to measure the fixation probability for cooperation, i.e., the probability that a single cooperator successfully invades a population. Here we resolve this conundrum by analyzing the fixation of cooperation on temporal (i.e., time-varying) networks. We theoretically prove and numerically confirm that on both synthetic and empirical networks, contrary to the case of static networks, temporal heterogeneous networks can promote cooperation more than temporal regular networks in terms of the fixation probability of cooperation. Given that the same conclusion is known for the equilibrium fraction of cooperators on temporal networks, the present results provide a unified understanding of the effect of temporal degree heterogeneity on promoting cooperation across two main analytical frameworks, i.e., equilibrium and non-equilibrium ones. Copyright © 2023, The Authors. All rights reserved.

关键词： Heterogeneous networks

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Quantification of C02 emission reductions from energy efficiency actions and solar photovoltaic generation at the Federal Institute of Education, Science, and Technology of Goiás

Renewable Energy and Power Quality Journal

引用

Renewable Energy and Power Quality Journal 2021年 19卷 45-50页

作者： Vidal, M.A. Faria, A.F. Stach, A.H.M. Netou, D.P. Pinto, L.S. Pinlio, A.G. Domingues, E.G. Master’s Program in Technology of Sustainable Process Federal Institute of Education Science and Technology Goias-Cainpuj Rua 75. n°46 - Centro Goiania - GO74055-110 Brazil Electiical Engineering Control and Automation Engineering Program Federal Institute of Education Science and Technology Goias-Cainpuj Rua 75. n°46 - Centro Goiania - GO74055-110 Brazil NeXT - Nucleus of Experimental and Technological Studies Federal Institute of Education Science and Technology Goias-Cainpuj Rua 75. n°46 - Centro Goiania - GO74055-110 Brazil

In 2016. die Brazilian Agency of Electric Energy-launched a public call for research and development projects to reduce barriers to implementing energy efficiency projects and own electricity generation. One objective of this public call was to encourage pilot projects at the Brazilian public higher education institutions. In this context, the Federal Institute of Education. Science, and Technology of Goias has approved the research project, entided "Energy efficiency and mini generation ai the Federal Institute of Education. Science, and Technology - IFG." The project consists of implementing energy efficiency actions and installing photovoltaic distributed generation (mini generation) in twelve of the fourteen IFG campuses. The main objective of this work is to quantify the C0;emission reductions from die project through the methodologies used by the United Nations Framework Climate Change Convention for projects under the Clean Development Mechanism The emission reductions over the project lifetime was estimated at approximately 37,400 iC’O- equivalent, evidencing the environmental benefit to be provided by the referred project. © 2021, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Energy efficiency

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Traffic Flow Estimation using Graph Neural Network with Aggregation of Traffic Features

Traffic Flow Estimation using Graph Neural Network with Aggr...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Adiyana Putri Ferio Brahmana Endra Joelianto Herman Y. Sutarto Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Artificial Intelligence Control and Automation Laboratory Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia

ISBN: (纸本)9781665476881

The increasing vehicle volume every year affects the prediction of the traffic system. The purpose of predicting traffic flow is to estimate the lost data caused by sensor malfunctions due to connection disruptions or ages. In estimating traffic flow, obtaining and explaining the historical data from the nearest segment sensor is necessary. The graph model can describe the spatial relationship between segments by connecting nodes with edges. Graph Neural Network (GNN) has been used as a learning method to predict the traffic flow in the segment sensor. GNN gets input in the form of spatial data built through a graph model, and the features are traffic density, average vehicle speed, and delay time on the road network. This paper shows that GNN's capability performs better in extracting spatial features and predicting the traffic flow by aggregating the features through connectivity nodes and edges.

关键词： Learning systems Roads Estimation Feature extraction Robot sensing systems Graph neural networks Spatial databases

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Educational robotics with tangible programming: A digital circuit for blocks communication with code and visual feedback transfer capabilities

Educational robotics with tangible programming: A digital ci...

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IEEE Latin American Robotics Symposium, LARS

作者： Jessica Toledo Salles Cristiane Pelisolli Cabral Rosane Aragon Alexandre Da Silva Simões Postgraduate Program in Electrical Engineering São Paulo State University (Unesp) Institute of Science and Technology Sorocaba Brazil Postgraduate Program in Education Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Faculty of Education (FACED) Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Control and Automation Engineering Department (DECA) São Paulo State University (Unesp) Institute of Science and Technology Sorocaba Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

A large number of robotic kits is commercially available for children education nowadays. Regarding the programming possibilities of these kits, they are usually divided into three categories: i) textual languages based kits, ii) digital blocks based kits and iii) tangible blocks based kits. In tangible blocks kits, the programming instructions are represented by physical - touchable - elements like blocks, cards or buttons. Since these are concrete objects, they are usually more playful and accessible for young children mainly in the concrete operational stage. Another relevant aspect in robotic kits is the possibility for children to follow the code execution at runtime. This process may be crucial for comprehending the programming process and for developing debugging abilities. In tangible programming based kits, this visual tracking is far more complex than in textual or digital blocks based kits since it typically requires the transmission of information between a lot of distinct physical pieces. The present work proposes and discusses the implementation of a digital electronic circuit with bluetooth communication designed for educational robotics kit and capable to provide a visual feedback. Results demonstrate that the proposed circuit is functional and feasible for embedding in robotic kits at a low cost.

关键词： Visualization Codes Runtime Costs Education Debugging Robots

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Deep-operator-network-based Mars entry parametric bank angle profile optimization

引用

Chinese Journal of Aeronautics 2025年

作者： Bo TANG Yanning GUO Youmin GONG Jie MEI Weiren WU School of Aerospace Science Harbin Institute of Technology Shenzhen 518055 China Department of Control Science and Engineering Harbin Institute of Technology Harbin 150001 China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China Lunar Exploration Program and Space Engineering Center Beijing 100190 China

Rapid and reliable onboard optimization of bank angle profiles is crucial for mitigating uncertainties during Mars atmospheric entry. This paper presents a neural-network-accelerated methodology for optimizing parametric bank angle profiles in Mars atmospheric entry missions. The methodology includes a universal approach to handling path constraints and a reliable solution method based on the Particle Swarm Optimization (PSO) algorithm. For illustrative purposes, a mission with the objective of maximizing terminal altitude is considered. The original entry optimization problem is converted into optimizing three coefficients for the bank angle profiles with terminal constraints by formulating a parametric Mars entry bank angle profile and constraint handling methods. The parameter optimization problem is addressed using the PSO algorithm, with reliability enhanced by increasing the PSO swarm size. To improve computational efficiency, an enhanced Deep Operator Network (DeepONet) is used as a dynamics solver to predict terminal states under various bank angle profiles rapidly. Numerical simulations demonstrate that the proposed methodology ensures reliable convergence with a sufficiently large PSO swarm while maintaining high computational efficiency facilitated by the neural-network-based dynamics solver. Compared to the existing methodologies, this methodology offers a streamlined process, the reduced sensitivity to initial guesses, and the improved computational efficiency.

关键词： Mars entry Bank angle profile Particle swarm optimization Neural networks Operator learning

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Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

arXiv

引用

arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Liu, Yinqiu Wang, Jiacheng Lin, Yijing Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Cui, Shuguang Ai, Bo Zhou, Haibo Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Shenzhen China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Electronic Science and Engineering Nanjing University Jiangsu Nanjing210093 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This paper serves as a comprehensive tutorial on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains, such as vision, text, and audio generation. We detail how GDMs can be effectively harnessed to solve complex optimization problems inherent in networks. The paper first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), incentive mechanism design, Semantic Communications (SemCom), Internet of Vehicles (IoV) networks, etc. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design. We conclude with a discussion on potential future directions for GDM research and applications, providing major insights into how they can continue to shape the future of network optimization. © 2023, CC BY.

关键词： Reinforcement learning

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AImotion Challenge Results: a Framework for AirSim Autonomous Vehicles and Motion Replication

AImotion Challenge Results: a Framework for AirSim Autonomou...

引用

Computers and automation (CompAuto), International Conference on

作者： Bruno J. Souza Lucas C. de Assis Dominik Rößle Roberto Z. Freire Daniel Cremers Torsten Schön Munir Georges Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil Control and Automation Eng. Department Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil Technische Hochschule Ingolstadt AImotion Bavaria Institute Ingolstadt Germany Department of Informatics Technical University of Munich Munich Germany

ISBN: (纸本)9781665481953

The use of simulation environments is becoming more significant in the development of autonomous cars, as it allows for the simulation of high-risk situations while also being less expensive. In this paper, we presented a framework that allows the creation of an autonomous vehicle in the AirSim simulation environment and then transporting the simulated movements to the TurtleBot. To maintain the car in the correct direction, computer vision techniques such as object detection and lane detection were assumed. The vehicle's speed and steering are both determined by Proportional-Integral-Derivative (PID) controllers. A virtual personal assistant was developed employing natural language processing to allow the user to interact with the environment, providing movement instructions related to the vehicle's direction. Additionally, the conversion of the simulator movements for a robot was implemented to test the proposed system in a practical experiment. A comparison between the real position of the robot and the position of the vehicle in the simulated environment was considered in this study to evaluate the performance of the algorithms.

关键词： Computer vision Lane detection Robot kinematics Atmospheric modeling Computational modeling Virtual environments Natural language processing

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Robust Current control of Three-Phase Grid-Connected Converters by Using the ADRC Method 16

Robust Current Control of Three-Phase Grid-Connected Convert...

引用

16th Brazilian Power Electronics Conference, COBEP 2021

作者： Campos De Araujo, Diana Alves Moor Neto, Joao Amin Do Brasil, Thiago Americano Gouvea, Josiel Alves Lopes Zachi, Alessandro Rosa Electrical Engineering Graduate Program Centro Fed. de Educ. Tecn. Celso Suckow da Fonseca CEFET/RJ Rio de Janeiro Brazil Centro Fed. de Educ. Tecn. Celso Suckow da Fonseca CEFET/RJ Department of Electrical Engineering Rio de Janeiro Brazil Centro Fed. de Educ. Tecn. Celso Suckow da Fonseca CEFET/RJ Department of Control Systems and Automation Rio de Janeiro Brazil

ISBN: (纸本)9781665421294

This paper addresses the control design of a current mode control for a three-phase voltage source converter. A variant of the Active Disturbance Rejection control (ADRC) scheme is proposed for comparison with the classical inner control approach. The ADRC method has a straightforward design procedure and has well-known abilities for disturbance rejection and robustness to parametric uncertainties of the system. Theoretical studies are presented and simulation results are discussed by using EMTP-RV environment considering the system Synchronous Reference Frame control, whose modeling was extracted from the analysis performed in a classical refer-ence. © 2021 IEEE.

关键词： Electric current control

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Extension of Kalman Filtering to Semilinear PDE Systems-Application to Pulp and Paper

Extension of Kalman Filtering to Semilinear PDE Systems-Appl...

引用

International Conference on System Theory, control, and Computing (ICSTCC)

作者： Ivan Francisco Yupanqui Tello Alain Vande Wouver Daniel Coutinho Systems Estimation Control and Optimization (SECO) University of Mons Belgium Postgraduate Program in Engineering of Automation and Systems Federal University of Santa Catarina Brazil

ISBN: (数字)9781728198095

ISBN: (纸本)9781728198101

This paper deals with the observer design of nonlinear tubular chemical reactor models. The analysis is performed on a linearized version of the model around a steady-state profile, in which some coefficients are a function of the spatial variable. The study starts from a general model of chemical tubular reactors that will serve as a benchmark model for the formulation in the infinite dimensional Hilbert state space. The optimal output injection operator associated to the proposed observer is computed via the solution of the infinite-dimensional Riccati equation in the space variable. The performance of the observer is illustrated through numerical experiments of an industrial pulp bleaching tubular reactor model.

关键词： Mathematical model Inductors Observers Bleaching Steady-state Computational modeling Estimation

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