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9th ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019

作者： Goldasz, J. Sapinski, B. Jastrzebski, L. Kubik, M. Faculty of Electrical Engineering and Computer Science Cracow University of Technology ul. Warszawska 24 Krakow31-155 Poland BWI Technical Center BWI Group ul. Podgorki Tynieckie 2 Krakow30-399 Poland Department of Process Control AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland Faculty of Mechanical Engineering Brno University of Technology Technicka 2869/2 Brno616 69 Czech Republic

ISBN: (纸本)9788494919466

This study concerns modeling the magnetic hysteretic behaviour of magnetorheological (MR) dampers. Magnetic hysteresis is one of factors influencing the output of such actuators. The origin of magnetic hysteresis in the actuator’s output is obvious - it is the inherent property of ferromagnetic materials which form the electromagnet’s assembly of the actuator. Prior work on solenoid actuators indicates that hysteresis plays a major role in the flux generation mechanism, and it should be accounted for in the controls development process. So far less attention has been paid to studying the contribution of magnetic hysteresis on the output of MR dampers. Majority of studies on the hysteretic behaviour of MR dampers have virtually neglected that specific contributor. Instead, the hysteretic behaviour of MR actuators was studied by observing the relationships between the output (force/torque) and the inputs (current, velocity, position). Instead, in the present study we separate the magnetic hysteresis from the mechanical/hydraulic one by investigating the magnetic flux vs exciting current relationship of an exemplary MR damper subjected to sinusoidal current (voltage) loading. The resulting behaviour of the electromagnets is then examined using the nonlinear inductor approach with hysteresis. The performance of several hysteretic operators is then evaluated based on their ability to reproduce the magnetic flux output of the MR actuator. © 2019 9th ECCOMAS Thematic Conference on Smart Structures and Materials, SMART 2019. All rights reserved.

关键词： Damping

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Customization of the educational process in the study programme of technology and management in the building industry through the BIM application

Customization of the educational process in the study progra...

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International Conference on Emerging eLearning Technologies and Applications (ICETA)

作者： Annamária Behúnová Peter Mésároš Jana Smetanková Katarína Krajníková Tomáš MandiČák Marcel Behún Department of Industrial Engineering and Informatics Technical University of Kosice Bayerova 1 Prešov Slovakia Faculty of Civil Engineering Technical University of Kodice Kosice Slovakia Faculty of Mining Ecology Process Control and Geotechnologies Technical University of Kodice Košice Slovakia

ISBN: (数字)9781728149677

ISBN: (纸本)9781728149684

New trends in the industry sharply follow the dynamic way of life of customers. This has resulted in the need to place greater emphasis on customer understanding and tailor your offer to customers. The same is true about construction industry and education process. It is education that is the first step to meet the needs of industry and thus also the customers. Implement mass communication to the educational proses. BIM technologies represent an effective tool in the construction industry, and it is the customization and customization of the use of individual parts of BIM that can be beneficial for the purpose. This research discuss the issue of customization od educational process in the study programme of technology and management in construction industry through the BIM application at faculty of Civil engineering in Kosice. Main aim of research is to analyze customization of courses for students and their needs through BIM application. There are more describe courses and useful of BIM parts for this reason.

关键词： Education Buildings Mass customization Tools Production Construction industry

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Design of Experiments for Battery Aging Estimation

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IFAC-PapersOnLine 2018年第28期51卷 386-391页

作者： Pózna, Anna I. Hangos, Katalin M. Magyar, Attila Department of Electrical Engineering and Information Systems Faculty of Information Technology University of Pannonia Egyetem str. 10. VeszprémH-8200 Hungary Process Control Research Group HAS Research Institute for Computer Science and Control Kende str. 13-17. BudapestH-1111 Hungary

Li-ion batteries are widely used in EV applications and are imposed to several aging effects during their lifetime. Since battery health cannot be measured directly, information about its health can be obtained by iteratively re-estimating the parameters of the model describing its dynamical behavior. The optimal design of experiments is investigated in this paper. The proposed method applies families of input signals (PRBS current and constant current-constant voltage (CC-CV) signals) to the batteries to estimate the key aging factors. Simulation experiments have been used to analyze the statistical properties of the estimators as a function of the design parameters of the input signal families. The results show that the CC-CV charging-discharging cycle has the possibility to gain the most information out of the battery model parameter estimation. © 2018

关键词： Parameter estimation Battery management systems Design of experiments Electric excitation Iterative methods Lithium ion batteries Planning Electric Experiment design Input Model formulation Storage operations

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Robust cooperative synchronization of homogeneous agents with delays on directed communication graphs

arXiv

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arXiv 2019年

作者： Alikoc, Baran Hengster-Movric, Kristian Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague160 00 Czech Republic Department of Control Engineering Faculty of Electrical Engineering Czech Czech Technical University in Prague Prague166 36 Czech Republic

This study deals with analysis and control of cooperative synchronization for identical agents interacting on a directed graph topology. The agents are considered to have general continuous linear time-invariant dynamics with homogeneous communication and/or control delays. An LMI approach based on a Lyapunov-Krasovskii functional is proposed, together with the synchronizing region concept, which decouples the single-agent dynamics from the detailed graph topology. Moreover, the conventional notion of synchronizing region is here extended by an LMI relaxation utilizing quasi-convex characteristic of the problem. This leads to less conservative results for the region of graph matrix eigenvalues in the complex domain, where the synchronization is guaranteed. The proposed method to calculate the allowable delay bound for synchronization is also less conservative as compared to the results from the literature. Furthermore, two designs for distributed state-feedback control are suggested. The precise delay value and the detailed graph topology need not be known for their application;it suffices only to know the upper bound on the delay and the approximate region where the Laplacian eigenvalues lie. Specific improvements over the results existing in the literature are demonstrated by a numerical example, which validates the proposed approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Lyapunov functions

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Symbolic regression for constructing analytic models in reinforcement learning

arXiv

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arXiv 2019年

作者： Derner, Erik Kubalík, Jiří Ancona, Nicola Babuška, Robert Czech Institute of Informatics Robotics and Cybernetics Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Prague16000 Czech Republic Czech Institute of Informatics Robotics Cybernetics Czech Technical University Prague Prague16000 Czech Republic Cognitive Robotics Delft University of Technology Delft2628 CD Netherlands

Reinforcement learning (RL) is a widely used approach for controlling systems with unknown or time-varying dynamics. Even though RL does not require a model of the system, it is known to be faster and safer when using models learned online. We propose to employ symbolic regression (SR) to construct parsimonious process models described by analytic equations for real-time RL control. We have tested our method with two different state-of-the-art SR algorithms which automatically search for equations that fit the measured data. In addition to the standard problem formulation in the state-space domain, we show how the method can also be applied to input-output models of the NARX (nonlinear autoregressive with exogenous input) type. We present the approach on three simulated examples with up to 14-dimensional state space: an inverted pendulum, a mobile robot, and a biped walking robot. A comparison with deep neural networks and local linear regression shows that SR in most cases outperforms these commonly used alternative methods. We demonstrate on a real pendulum system that the analytic model found enables RL to successfully perform the swing-up task, based on a model constructed from only 100 data samples. Copyright © 2019, The Authors. All rights reserved.

关键词： Reinforcement learning

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Behavioural Approach to Network Anomaly Detection for Resource-Constrained System – Presentation of the Novel Solution – Preliminary Study

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IFAC-PapersOnLine 2019年第27期52卷 121-126页

作者： Mariusz Pelc Dawid Galus Magda Zolubak Stepan Ozana Wojciech Chlewicki Katarzyna Cichon Michal Podpora Aleksandra Kawala-Sterniuk Opole University of Technology – Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland University of Greenwich – Department of Computing and Information Systems – Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK VSB – Technical University Ostrava – FEECS Department of Cybernetics and Biomedical Engineering Ostrava Czech Republic West Pomeranian University of Technology in Szczecin – Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland

In this paper some preliminary results of network anomaly detection for resource-constrained systems have been presented. All described algorithms are embedded into a three-tier system application. The presented solution is a response to nowadays trends in computer/network security domain that indicate gradual shifting from signature-based anomaly detection typically based on some selected statistical measures toward systems that are based on behavioural analysis of computer systems and/or networks. The presented system requirements, explain relevant terminology as well as we include some selected results and their analysis. The solution is potentially destined for very resource-constrained systems (IoT specifically), all tests were carried out in an example network to additionally analyse their effect of the presented approach on the computer resources.

关键词： Network Anomaly Detection Behavioural Analysis Internet of Things

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Application of Cognitive Changes Markers for Diagnostics’ Purposes and in Neurofeedback Therapy

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IFAC-PapersOnLine 2019年第27期52卷 520-523页

作者： Magda Zolubak Mariusz Pelc Michal Podpora Wojciech Chlewicki Katarzyna Cichon Aleksandra Kawala-Sterniuk Opole University of Technology - Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland West Pomeranian University of Technology in Szczecin - Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland University of Greenwich - Department of Computing and Information Systems - Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK

Thanks to the automation of diagnostic processes based on the EEG signal and the creation of classifications of various attention disorders based on the analysis of the EEG signals (as diagnostic markers) - it may be possible to refer patients to appropriate specialists and provide them with appropriate neurofeedback-based treatment. The marker method proposed by the authors of the hereof paper is based on analysis of the EEG, which signal can be widely use in screening diagnostics. The proposed solution in this work may be used for neurofeedback or Brain Computer Interfaces (BCI). In this paper the authors presented implementation of markers for the purpose of analysis of some memory disorders and short-time attention disorder. The study is still in progress. Presented results have initial-study character.

关键词： EEG neurofeedback BCI algoritms

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Vision-based Navigation Using Deep Reinforcement Learning

arXiv

引用

arXiv 2019年

作者： Kulhánek, Jonáš Derner, Erik de Bruin, Tim Babuška, Robert Cognitive Robotics Faculty of 3mE Delft University of Technology Delft2628 CD Netherlands Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague16636 Czech Republic Department of Control Engineering Faculty of Electrical Engineering Czech Technical University in Prague Prague16627 Czech Republic

— Deep reinforcement learning (RL) has been successfully applied to a variety of game-like environments. However, the application of deep RL to visual navigation with realistic environments is a challenging task. We propose a novel learning architecture capable of navigating an agent, e.g. a mobile robot, to a target given by an image. To achieve this, we have extended the batched A2C algorithm with auxiliary tasks designed to improve visual navigation performance. We propose three additional auxiliary tasks: predicting the segmentation of the observation image and of the target image and predicting the depth-map. These tasks enable the use of supervised learning to pre-train a large part of the network and to reduce the number of training steps substantially. The training performance has been further improved by increasing the environment complexity gradually over time. An efficient neural network structure is proposed, which is capable of learning for multiple targets in multiple environments. Our method navigates in continuous state spaces and on the AI2-THOR environment simulator outperforms state-of-the-art goal-oriented visual navigation methods from the literature. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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Algorithms for robust production scheduling with energy consumption limits

arXiv

引用

arXiv 2018年

作者： Modos, Istvan Sucha, Premysl Hanzalek, Zdenek Department of Control Engineering Faculty of Electrical Engineering Czech Technical University Czech Institute of Informatics Robotics and Cybernetics Czech Technical University

In this work, we consider a scheduling problem faced by production companies with large electricity consumption. Due to the contract with the electric utility, the production companies are obligated to comply with the total energy consumption limits in the specified time intervals (usually 15-minutes long);otherwise, the companies pay substantial penalty fees. Although it is possible to design production schedules that consider these limits as hard constraints, uncertainties occurring during the execution of the schedules are usually not taken into account. This may lead to situations in which the unexpected delays of the operations cause the violations of the energy consumption limits. Our goal is to design robust production schedules pro-actively guaranteeing that the energy consumption limits are not violated for the given set of uncertainty scenarios. We consider scheduling on one machine with release times of the operations and total tardiness as the objective function. To tackle this problem, we first propose a pseudo-polynomial algorithm for finding the optimal robust schedule for the given permutation of the operations. This algorithm is then utilised in three different algorithms for finding the optimal permutation: Two exact (Branch-and-Bound and logic-based Benders decomposition) and one heuristic algorithm (tabu search). All the algorithms were experimentally evaluated on random instances with different sizes of the uncertainty scenarios set. Using the tabu search algorithm, we are able to solve large instances within one minute. Copyright © 2018, The Authors. All rights reserved.

关键词： Electric power utilization

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Development of a Decision Support Tool for Intelligent Manufacturing using Classification and Correlation Analysis

Development of a Decision Support Tool for Intelligent Manuf...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Dariusz Król Jan Skowroński Maciej Zareba Krzysztof Bartecki Department of Information Systems Faculty of Computer Science and Management Wrocław University of Science and Technology Poland Legnicka 55F 53–203 Wrocław Wrocław University of Science and Technology Poland DSR Legnicka 55F 53—203 Wrocław Poland Institute of Automatic Control Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Poland

The development of the Production Unit Performance Management Tool (PUPMT), a monitoring and diagnostic tool to select basic signals that have a significant impact on output KPIs, is based on a hierarchical analysis of key performance indicators presented in the ISO 22400 standard. The growing number of quantified signals, such as ambient temperature or even the frequency of vibrations makes decision support tools more intelligent. Moreover, they also include predictive analysis in addition to online presentation of the current state of resources. PUPMT tool allows identifying key events that have a significant impact on current or future benefit in production output. It also allows what-if type analysis, running the simulation of the impact of the proposed changes, and the results of this simulation depend on the effects of similar changes that occurred in the past in a given smart manufacturing environment. Thanks to the automatic identification of potential dependencies, the proposed solution adapts to the specifics of a given environment or even a selected production unit. The paper describes the most important methods featured in the tool. Specifically, it considers a signal classification method, a signal correlation analysis and selection of key factors affecting the efficiency of the production process. In order to verify the methods various tests were carried out to calculate and control of OEE index on 20 production units. Finally, we conclude current results and future research directions.

关键词： Conferences Cybernetics

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