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IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Thomas Pursche Marcel Walz Roland Clauß Robert Roth Bernd Tibken Reinhard Möller School of Electrical Information and Media Engineering Automatic Control University of Wuppertal Wuppertal Germany Faculty of Electrical Information and Media Engineering Automatic Control University of Wuppertal Wuppertal Germany Faculty of Electrical Information and Media Engineering Automation/Computer Science University of Wuppertal Wuppertal Germany

The conventional heart rate measurement techniques using electrocardiogram, wrist belts and so on, are attached with some disadvantages like discomfort, irritation of the skin and even more. From this starting point various video based heart rate measurement techniques were developed in the last years. All of these techniques use video data of the human faces to extract information to estimate the heart rate of the person in front of the camera. Most of them work with the detection of minimal changes in the color spectrum of the recorded video data. With these extracted information and multiple concluding steps, they are able to estimate the heart rate of the person sitting in front of the camera. All of these approaches have some big disadvantages, they are only able to measure the heart rate of one person - and in a small number of cases up to three persons. So the main objective of this work is to adapt and enhance existing research approaches of processing visual biological signals. The focus is set on the design and deployment of a new system, which is able to process visual data as well as detect and localize human faces by using artificial neural networks and calculate each individuals heart rate from the processed data's information. For the first time in this research area, different scenarios with more than three observed participants are being analyzed to calculate the heart rate for each of them separately. It will be shown that by using the applied technical architecture and technologies, it is possible to deploy a comparable and qualitatively competitive system. In addition, the implemented system proves the feasibility of processing various faces' signals and calculating the respective heart rates simultaneously within an acceptable range of tolerance.

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Analytical model of a nonlinear vibration energy harvester

Analytical model of a nonlinear vibration energy harvester

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2018 International Symposium on electrical Machines, SME 2018

作者： Jagiela, Mariusz Kulik, Marcin Automatic Control and Informatics Opole University of Technology Faculty of Electrical Engineering ul. Prószkowska 76 Opole45-758 Poland

ISBN: (纸本)9781538652107

The analytical solution for most useful electromagnetic quantities for a coreless linear-motion nonlinear electromechanical microgenerator, suitable for wideband energy harvesting systems, is presented. The implicit and closed-form formulas for magnetic flux, magnetic stiffness and coil inductance and magnetic stiffness are provided. The results of analytical calculations show remarkable accuracy in comparison with the finite element predictions especially when derivatives of the magnetic quantities are considered. © 2018 IEEE.

关键词： Analytical models

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Steady state analysis of switched reluctance motor with modified geometry of the stator designed for an electric bike

Steady state analysis of switched reluctance motor with modi...

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2018 International Symposium on electrical Machines, SME 2018

作者： Gabor, Rafal Kowol, Marcin Kolodziej, Janusz Mynarek, Piotr Opole University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science Opole Poland

ISBN: (纸本)9781538652107

The paper contains a proposition of the application of a SRM motor with a modified stator geometry for an electric drive, in particular in an electric bicycle. The study involved a comparison of the cyclicity of the electromagnetic torque and self-inductance in the function of the rotor angle in 2D and 3D models based on the application of the finite element method. © 2018 IEEE.

关键词： Finite element method

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Symbolic Regression Driven by Training Data and Prior Knowledge

arXiv

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arXiv 2020年

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

In symbolic regression, the search for analytic models is typically driven purely by the prediction error observed on the training data samples. However, when the data samples do not sufficiently cover the input space, the prediction error does not provide sufficient guidance toward desired models. Standard symbolic regression techniques then yield models that are partially incorrect, for instance, in terms of their steady-state characteristics or local behavior. If these properties were considered already during the search process, more accurate and relevant models could be produced. We propose a multi-objective symbolic regression approach that is driven by both the training data and the prior knowledge of the properties the desired model should manifest. The properties given in the form of formal constraints are internally represented by a set of discrete data samples on which candidate models are exactly checked. The proposed approach was experimentally evaluated on three test problems with results clearly demonstrating its capability to evolve realistic models that fit the training data well while complying with the prior knowledge of the desired model characteristics at the same time. It outperforms standard symbolic regression by several orders of magnitude in terms of the mean squared deviation from a reference model. Copyright © 2020, The Authors. All rights reserved.

关键词： Genetic programming

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Foreword

Lecture Notes in Electrical Engineering

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Lecture Notes in electrical engineering 2020年 554卷 v-vi页

作者： Zelinka, Ivan Brandstetter, Pavel Dao, Tran Trong Duy, Vo Hoang Kim, Sang Bong Department of Computer Science Faculty of Electrical Engineering VŠB-TUO Poruba Ostrava Czech Republic Department of Electronics Faculty of Electrical Engineering VŠB-TUO Ostrava Czech Republic International Cooperation Research and Training Institute Ton Duc Thang University Ho Chi Minh Viet Nam Department of Automatic Control Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Mechanical Design Engineering Pukyong National University Busan Korea Republic of

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Multi-variant scheduling of critical time-triggered communication in incremental development process: Application to FlexRay

arXiv

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arXiv 2019年

作者： Dvořák, Jan Hanzálek, Zdeněk Department of Control Engineering Faculty of Electrical Engineering CTU in Prague Industrial Informatics Research Center Czech Institute of Informatics Robotics and Cybernetics CTU in Prague

The portfolio of models offered by car manufacturing groups often includes many variants (i.e., different car models and their versions). With such diversity in car models, variant management becomes a formidable task. Thus, there is an effort to keep the variants as close as possible. This simple requirement forms a big challenge in the area of communication protocols. When several vehicle variants use the same signal, it is often required to simultaneously schedule such a signal in all vehicle variants. Furthermore, new vehicle variants are designed incrementally in such a way as to maintain backward compatibility with the older vehicles. Backward compatibility of time-triggered schedules reduces expenses relating to testing and fine-tuning of the components that interact with physical environment (e.g., electromagnetic compatibility issues). As this requirement provides for using the same platform, it simplifies signal traceability and diagnostics, across different vehicle variants, besides simplifying the reuse of components and tools. This paper proposes an efficient and robust heuristic algorithm, which creates the schedules for internal communication of new vehicle variants. The algorithm provides for variant management by ensuring compatibility among the new variants, besides preserving backward compatibility with the preceding vehicle variants. The proposed method can save about 20% of the bandwidth with respect to the schedule common to all variants. Based on the results of the proposed algorithm, the impact of maintaining compatibility among new variants and of preserving backward compatibility with the preceding variants on the scheduling procedure is examined and discussed. Thanks to the execution time of the algorithm, which is less than one second, the network parameters like the frame length and cycle duration are explored to find their best choice concerning the schedule feasibility. Finally, the algorithm is tested on benchmark sets and the concept

关键词： Scheduling

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On an IFAC online pilot survey for a first course on control 5

On an IFAC online pilot survey for a first course on control

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5th Experiment at International Conference, exp.at 2019

作者： Huba, Mikulas Anthony Rossiter, J. Zakova, Katarina Serbezov, Atanas Visioli, Antonio Institute of Automotive Mechatronics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Bratislava Slovakia Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Rose-Hulman Institute of Technology Terre Haute United States Department of Mechanical and Industrial Engineering University of Brescia Brescia Italy

ISBN: (纸本)9781728136370

关键词： engineering education

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Fast Statistical Outlier Removal Based Method for Large 3D Point Clouds of Outdoor Environments

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IFAC-PapersOnLine 2018年第22期51卷 348-353页

作者： Balta, Haris Velagic, Jasmin Bosschaerts, Walter De Cubber, Geert Siciliano, Bruno Royal Military Academy Department of Mechanics Brussels Belgium Department of Automatic Control and Electronics Faculty of Electrical Engineering Sarajevo Bosnia and Herzegovina Department of Electrical Engineering and Information Technology University of Naples Federico II Napoli Italy

This paper proposes a very effective method for data handling and preparation of the input 3D scans acquired from laser scanner mounted on the Unmanned Ground Vehicle (UGV). The main objectives are to improve and speed up the process of outliers removal for large-scale outdoor environments. This process is necessary in order to filter out the noise and to downsample the input data which will spare computational and memory resources for further processing steps, such as 3D mapping of rough terrain and unstructured environments. It includes the Voxel-subsampling and Fast Cluster Statistical Outlier Removal (FCSOR) subprocesses. The introduced FCSOR represents an extension on the Statistical Outliers Removal (SOR) method which is effective for both homogeneous and heterogeneous point clouds. This method is evaluated on real data obtained in outdoor environment. © 2018

关键词： Intelligent vehicle highway systems Data handling Ground vehicles Statistics 3D point cloud FCSOR large scale environment Outlier removals Unmanned ground vehicles

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Fast Iterative 3D Mapping for Large-Scale Outdoor Environments with Local Minima Escape Mechanism

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IFAC-PapersOnLine 2018年第22期51卷 298-305页

This paper introduces a novel iterative 3D mapping framework for large scale natural terrain and complex environments. The framework is based on an Iterative-Closest-Point (ICP) algorithm and an iterative error minimization mechanism, allowing robust 3D map registration. This was accomplished by performing pairwise scan registrations without any prior known pose estimation information and taking into account the measurement uncertainties due to the 6D coordinates (translation and rotation) deviations in the acquired scans. Since the ICP algorithm does not guarantee to escape from local minima during the mapping, new algorithms for the local minima estimation and local minima escape process were proposed. The proposed framework is validated using large scale field test data sets. The experimental results were compared with those of standard, generalized and non-linear ICP registration methods and the performance evaluation is presented, showing improved performance of the proposed 3D mapping framework. © 2018

关键词： Iterative methods Image registration Mapping Uncertainty analysis 3D point cloud FCSOR large scale environment Outlier removals Unmanned ground vehicles

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Learning dynamical systems using local stability priors

arXiv

引用

arXiv 2020年

作者： Mehrjou, Arash Iannelli, Andrea Schölkopf, Bernhard Empirical Inference Department of Max Planck Institute for Intelligent Systems Tübingen Germany Department of Computer Science ETH Zürich Faculty of Electrical Engineering Zürich Switzerland Department of Electrical Engineering Automatic Control Lab ETH Zürich8092 Switzerland Empirical Inference Department of Max Planck Institute for Intelligent Systems Tübingen Germany

A coupled computational approach to simultaneously learn a vector field and the region of attraction of an equilibrium point from generated trajectories of the system is proposed. The nonlinear identification leverages the local stability information as a prior on the system, effectively endowing the estimate with this important structural property. In addition, the knowledge of the region of attraction plays an experiment design role by informing the selection of initial conditions from which trajectories are generated and by enabling the use of a Lyapunov function of the system as a regularization term. Numerical results show that the proposed method allows efficient sampling and provides an accurate estimate of the dynamics in an inner approximation of its region of attraction. Copyright © 2020, The Authors. All rights reserved.

关键词： Lyapunov functions

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