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Possibility of Using Technologies of Augmented and Virtual Reality for Acquisition Hard and Soft Skills of Electrical Engineering Specialists

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Possibility of Using Technologies of Augmented and Virtual R...

International Conference on Modern Electrical and Energy systems (MEES)

作者： Olha Chencheva Volodymyr Chenchevoi Andriy Perekrest Yurii Morozov Oksana Zbyrannyk Mykhaylo Lytvynenko Department of Civil and Labour Safety Geodesy and Land Management Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Systems of Automatic Control and Electric Drive department Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Department of computer engineering and electronics Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine “MOBIMODS” Sp. z o.o. Kremenchuk Ukraine Department of Economics and Management Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

ISBN: (纸本)9798350346848

The paper explores the possibilities of using augmented and virtual reality technologies to create distance online courses in order to ensure the acquisition of hard and soft skills of electrical engineering specialists. The use of 3D visualization, animation, sound accompaniment, subtitling in the development and formation of training courses of educational components allows you to fill it with the necessary informational content, immersing the student in a real production environment. The use of augmented reality allows you to adapt the educational process and provide the necessary competencies for the real technological process and equipment.

关键词： Training Electrical engineering Visualization Computer aided instruction Solid modeling Three-dimensional displays Psychology

Combined Extension and Torsion of Hydrogels with Chemo-Mechanical Coupling: Revealing Negative Poynting Effect

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SSRN

SSRN 2024年

作者： Zheng, Chengxiang Hu, Minghui Wu, Tao Pasquale, Ciarletta Li, Qian Deng, Zichen School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'An710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Xi'An710072 China MOX Department di Mathematica Polytechnic di Milano piazza Leonardo da Vinci 32 Milano20133 Italy China Electronic Product Reliability and Environmental Testing Research Institute China Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology China

In this paper, combined extension and torsion of hydrogel subject to a chemo-mechanical coupled loading is described in the framework of continuum mechanics, where the free energy density consists of the elastic, mixing and chemical contributions. A simplified, closed-form and exactly analytical solution to the mechanical response is obtained, which accounts for the coupling effect of external loading, chemical potential and microstructural parameters, such as crosslinking degree, Flory parameter, etc. In particular, the effect of free swelling and microscopic diffusion on deformation of the hydrogel is discussed, reaching some fundamental conclusions. The classic negative Poynting effect is revealed that the cylinder tends to shorten on twisting, and an inhomogeneous deformation, induced by torsion, along the radial direction is demonstrated. Furthermore, the dynamic competition between external loading and solvent environment is revealed and investigated, where the direct connection between internal micro-physical parameters and macroscopic deformation is demonstrated. The theoretical results presented in this paper may provide predictions and guidance for the mechanical analysis and design of hydrogel cylinder subject to extension and torsion in a solvent. © 2024, The Authors. All rights reserved.

关键词： Torsional stress

Robust Beamforming for Localization-Aided Millimeter Wave Communication systems

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arXiv 2022年

作者： Sun, Junchang Ma, Shuai Li, Shiyin Yang, Ruixin Min, Minghui Seco-Granados, Gonzalo The School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China The Department of Telecommunications and Systems Engineering Universitat Autònoma de Barcelona Barcelona08193 Spain The Engineering Research Center of Intelligent Control for Underground Space Ministry of Education China University of Mining and Technology Xuzhou221116 China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Shanxi Key Laboratory of Information Communication Network and Security Xian University of Posts and Telecommunications Xian710121 China

In this letter, we investigate a robust beamforming problem for localization-aided millimeter wave (mmWave) communication systems. To handle this problem, we propose a novel restriction and relaxation (R&R) method. The proposed R&R method aims at minimizing the total transmit power while the positioning error follows a Gaussian distribution. Specifically, in the restriction phase of R&R, the probabilistic constraint is transformed into the deterministic form by using the Bernstein-type inequality. In the relaxation phase of R&R, the non-convex optimization problem is reformulated into a convex semidefinite program (SDP) by using semidefinite relaxation (SDR) and first-order Taylor expansion methods. To the best of our knowledge, we first consider the impact of the distribution of the positioning error on the channel state information (CSI), which further influences the data rate. Numerical results present the trade-off of the beamforming between the communication and positioning. © 2022, CC BY.

关键词： Beamforming

Finite time exact quantized average consensus with limited resources and transmission stopping for energy-aware networks

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arXiv 2021年

作者： Rikos, Apostolos I. Hadjicostis, Christoforos N. Johansson, Karl H. Division of Decision and Control Systems KTH Royal Institute of Technology Digital Futures StockholmSE-100 44 Sweden Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

Composed of spatially distributed sensors and actuators that communicate through wireless networks, networked control systems are emerging as a fundamental infrastructure technology in 5G and IoT technologies, including diverse applications, such as autonomous vehicles, UAVs, and various sensing devices. In order to increase flexibility and reduce deployment and maintenance costs, many such applications consider battery-powered or energy-harvesting networks, which bring additional limitations on the energy consumption of the wireless network. Specifically, the operation of battery-powered or energy-harvesting wireless communication networks needs to guarantee (i) efficient communication between nodes and (ii) preservation of available energy. Motivated by these novel requirements, in this paper, we present and analyze a novel distributed average consensus algorithm, which (i) operates exclusively on quantized values (in order to guarantee efficient communication and data storage), and (ii) relies on event-driven updates (in order to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed algorithm and show that its execution, on any time-invariant and strongly connected digraph, will allow all nodes to reach, in finite time, a common consensus value that is equal to the exact average (represented as the ratio of two quantized values). Furthermore, we show that our algorithm allows each node to cease transmissions once the exact average of the initial quantized values has been reached (in order to preserve its battery energy). Then, we present upper bounds on (i) the number of transmissions and computations each node has to perform during the execution of the algorithm, and (ii) the memory and energy requirements of each node in order for the algorithm to be executed. Finally, we provide examples that demonstrate the operation, performance, and potential advantages of our proposed

关键词： Multi agent systems

Mental Stress Tests with Autonomic Responses Induced in Virtual Reality Environment

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Mental Stress Tests with Autonomic Responses Induced in Virt...

IEEE Global Conference on Life Sciences and Technologies (LifeTech)

作者： Nan Bu Department of Control and Information Systems Engineering National Institute of Technology (NIT) Kumamoto Japan

ISBN: (数字)9781728170633

ISBN: (纸本)9781728170640

Psychological stressors used in mental stress tests largely effect quality and outcomes of experimental studies. This paper aims to develop a novel mental stress induction method using autonomic responses in virtual reality (VR) environments. Recent progress in VR technology promises desirable experience of immersion in a virtual space. Mental stress tests in VR are easy to configure and more flexible in experimental procedure. These virtual tests can provide close/improved outcomes comparing with real tests that use actual apparatuses and configurations. VR media contents of a roller coaster is investigated as stress load in this study. Nine subjects took part in the experiments and the electrocardiogram (ECG) data are analyzed with three short-term HRV analysis methods.

关键词： Mental stress induction stress experiments virtual reality autonomic response heart rate variability Psychological Stress virtual reality heart rate variability Variable reluctance virtual reality technology Roller coasters virtual reality environment stress state Autonomic Nervous System

Topologically assisted optimization for rotor design

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arXiv 2023年

作者： Wang, Tianyu Yang, Yannian Chen, Xuanwu Li, Pengyu Iollo, Angelo Maceda, Guy Cornejo Y. Noack, Bernd R. School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Institute of Aero Engine Tsinghua University Beijing10084 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen518055 China Institut de Mathématiques de Bordeaux Université de Bordeaux and Memphis Team Centre Inria de l’Université de Bordeaux Talence33400 France

We develop and apply a novel shape optimization exemplified for a two-blade rotor with respect to the figure of merit (FM). This topologically assisted optimization (TAO) contains two steps. First a global evolutionary optimization is performed for the shape parameters and then a topological analysis reveals the local and global extrema of the objective function directly from the data. This non-dimensional objective function compares the achieved thrust with the required torque. Rotor blades have a decisive contribution to the performance of quadcopters. A two-blade rotor with pre-defined chord length distribution is chosen as the baseline model. The simulation is performed in a moving reference frame with a k−ω turbulence model for the hovering condition. The rotor shape is parameterized by the twist angle distribution. The optimization of this distribution employs a genetic algorithm. The local maxima are distilled from the data using a novel topological analysis inspired by discrete scalar-field topology. We identify one global maximum to be located in the interior of the data and five further local maxima related to errors from non-converged simulations. The interior location of the global optimum suggests that small improvements can be gained from further optimization. The local maxima have a small persistence, i.e., disappear under a small Ε perturbation of the figure of merit values. In other words, the data may be approximated by a smooth mono-modal surrogate model. Thus, the topological data analysis provides valuable insights for optimization and surrogate modeling. Copyright © 2023, The Authors. All rights reserved.

关键词： Turbulence models

The Problem of Tasks Scheduling with Due Dates in a Flexible Multi-machine Production Cell 21st

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The Problem of Tasks Scheduling with Due Dates in a Flexible...

21st International Conference on Computational Science, ICCS 2021

作者： Bożejko, Wojciech Nadybski, Piotr Rajba, Pawel Wodecki, Mieczyslaw Department of Automatics Mechatronics and Control Systems Wroclaw University of Technology Janiszewskiego 11-17 Wroclaw50-372 Poland Witelon State University of Applied Science in Legnica Sejmowa 5A Legnica59-220 Poland Institute of Computer Science University of Wroclaw Joliot-Curie 15 Wroclaw50-383 Poland Department of Telecommunications and Teleinformatics Wroclaw University of Science and Technology Wybrzeże Wyspiańskiego 27 Wroclaw50-370 Poland

ISBN: (纸本)9783030779696

In the paper we consider an NP-hard problem of tasks scheduling with due dates and penalties for the delay in a flexible production cell. Each task should be assigned to one of the cell’s machines and the order of their execution on machines should be determined. The sum of penalties for tardiness of tasks execution should be minimized. We propose to use the tabu search algorithm to solve the problem. Neighborhoods are generated by moves based on changing the order of tasks on the machine and changing the machine on which the task will be performed. We prove properties of moves that significantly accelerate the search of the neighborhoods and shorten the time of the algorithm execution and in result significantly improves the efficiency of the algorithm compared to the version that does not use these properties. © 2021, Springer Nature Switzerland AG.

关键词： Scheduling

Distributed Coverage Hole Prevention for Visual Environmental Monitoring with Quadcopters via Nonsmooth control Barrier Functions

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arXiv 2022年

作者： Funada, Riku Santos, María Maniwa, Ryuichi Yamauchi, Junya Fujita, Masayuki Sampei, Mitsuji Egerstedt, Magnus The Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8550 Japan The Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States The Department of Information Physics and Computing The University of Tokyo Tokyo113-8656 Japan The Department of Electrical Engineering and Computer Science University of California Irvine IrvineCA92697 United States

This paper proposes a distributed coverage control strategy for quadcopters equipped with downward-facing cameras that prevents the appearance of unmonitored areas in between the quadcopters' fields of view (FOVs). We derive a necessary and sufficient condition for eliminating any unsurveilled area that may arise in between the FOVs among a trio of quadcopters by utilizing a power diagram, i.e. a weighted Voronoi diagram defined by radii of FOVs. Because this condition can be described as logically combined constraints, we leverage nonsmooth control barrier functions (NCBFs) to prevent the appearance of unmonitored areas among a team's FOV. We then investigate the symmetric properties of the proposed NCBFs to develop a distributed algorithm. The proposed algorithm can support the switching of the NCBFs caused by changes of the quadcopters composing trios. The existence of the control input satisfying NCBF conditions is analyzed by employing the characteristics of the power diagram. The proposed framework is synthesized with a coverage control law that maximizes the monitoring quality while reducing overlaps of FOVs. The proposed method is demonstrated in simulation and experiment. Copyright © 2022, The Authors. All rights reserved.

关键词： Sensor networks

Proving Ground Test of a DDPG-based Vehicle Trajectory Planner

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Proving Ground Test of a DDPG-based Vehicle Trajectory Plann...

European control Conference (ECC)

作者： Árpád Fehér Szilárd Aradi Tamás Bécsi Péter Gáspár Zsolt Szalay Department of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

The paper presents real-world test cases of an optimal trajectory design solution that combines modern control techniques with machine learning. The first step of the current research is to train a reinforcement learning agent in a simulated environment, where the conditions and the applied vehicle are modeled. System dynamics is described by a nonlinear single-track vehicle with dynamic wheel model. The designed trajectory is evaluated by driving the vehicle using a control loop. The reward of the method is based on the sum of different measures considering safety and passenger comfort. The proposed method forms a special one-step reinforcement learning task handled by Deep Deterministic Policy Gradient (DDPG) learning agent. As a result, the learning process provides a real-time neural-network-based motion planner and a tracking algorithm. The evaluation of the algorithm under real conditions is made by using an experimental test vehicle. The test setup contains a high precision GPS module, an automotive inertial sensor, an industrial PC, and communication interface devices. The test cases were performed on the ZalaZone automotive proving ground.

关键词： Trajectory Wheels Learning (artificial intelligence) Planning Training Axles Machine learning