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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Lincoln Moura de Oliveira Esio Eloi dos Santos Filho Gean Jacques Maia de Sousa Fernando Luiz Marcelo Antunes Edílson Mineiro Sá Junior Electrical Engineering Department Federal University of Ceara - UFC Fortaleza Brazil Electrical Engineering Department Federal University of Santa Catarina (UFSC) Florianopólis SC Brazil Chair of High-Power Converter Systems Technical University of Munich (TUM) Munich Germany Department of Control and Industrial Processes Federal Institute of Education Science and Technology of Ceará - IFCE Sobral Brazil

The neutral shift technique is a widely known method for three-phase cascaded multilevel converters working under fault conditions. This paper proposes an artificial neural network (ANN) with a custom cost function to solve equations that generate balanced line voltages when a fault occurs. Simulations using Python and TensorFlow are implemented for several fault conditions, showing the performance of the ANN for a wide range of conditions and ensuring convergence boundary conditions.

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Influence of Oil Quality on the Interpretation of Dissolved Gas Analysis Data

Influence of Oil Quality on the Interpretation of Dissolved ...

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International Conference on Condition Assessment Techniques in Electrical systems (CATCON)

作者： Mohammed El Amine Senoussaoui Issouf Fofana Mostefa Brahami Faculty of Sciences and Technology University of Mascara Mascara Algeria Research Chair on the Aging of Power Network Infrastructure (ViAHT) University of Quebec in Chicoutimi Chicoutimi Canada Intelligent Control and Electrical Power Systems Laboratory Djilali Liabes University Sidi Belabbès Algeria

ISBN: (纸本)9781665431361

Dissolved gas analysis (DGA) is being used for many years as a diagnostic tool for the condition monitoring of power transformers. However, field experiences reveal that the interpretation of these dissolved gas data is not an easy task due to the complexity of the gassing phenomenon. This is due to a number of factors. One of those contributing factors namely, the impact of oil quality is investigated in this contribution. The measurement of the dissolved and undissolved (non-gaseous decomposition) aging by-products respectively assessed by UV / VIS spectrophotometry and turbidity allowed assessing the oil’s quality and its relationships with gas generation under electrical or thermal faults. The obtained results indicated that the degraded oils release more CO along with some small amounts of combustible gases under thermal stress. The volume of gases in the case of an electrical fault is almost the same regardless the oil’s condition.

关键词： Degradation Gases Oils Aging Oil insulation Dissolved gas analysis Solids

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NCSbench Demo: Reproducible Benchmarking Platform for networked control systems

NCSbench Demo: Reproducible Benchmarking Platform for Networ...

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Consumer Communications and networking Conference, CCNC IEEE

作者： Samuele Zoppi Onur Ayan Fabio Molinari Zenit Music Sebastian Gallcnmüller Georg Carle Wolfgang Kellerer Chair of Communication Networks TUM Germany Control Systems Group TU Berlin Germany Chair of Network Architectures and Services TUM Germany

ISBN: (数字)9781728138930

ISBN: (纸本)9781728138947

Cyber-Physical systems (CPS) are widely spreading thanks to fast-paced technological breakthroughs of microcontrollers and communication networks. Among them, networked control systems (NCS) gained notable attention thanks to their application in industrial operations. In NCS, the interconnection of a control logic with sensors and actuators used to steer a physical system occurs over a communication network. Despite large research interest on NCS, the reproducibility and comparison of experimental results are difficult to achieve. This is caused by the lack of well-established models and methodologies that combine the theoretical and practical aspects of NCS. We tackle this problem by proposing and demonstrating NCSbench: the first open-source reproducible benchmarking platform for NCS. NCSbench enables the benchmarking of research experiments using a networked two-wheeled inverted pendulum robot. For each benchmarking experiment, a set of values is measured and used to quantify the key performance indicators (KPIs) of the NCS. In our demonstration, we visualize in real-time the evolution of the benchmarking KPIs on a web-based Graphical User Interface.

关键词： Benchmark testing Real-time systems Graphical user interfaces Delays Loss measurement Robot sensing systems

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NCSbench: Reproducible Benchmarking Platform for networked control systems

NCSbench: Reproducible Benchmarking Platform for Networked C...

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Consumer Communications and networking Conference, CCNC IEEE

作者： Samuele Zoppi Onur Ayan Fabio Molinari Zenit Music Sebastian Gallenmüller Georg Carle Wolfgang Kellerer Chair of Communication Networks TUM Germany Control Systems Group TU Berlin Germany Chair of Network Architectures and Services TUM Germany

ISBN: (数字)9781728138930

ISBN: (纸本)9781728138947

The evolution of the Internet of Things accelerated the development of Cyber-Physical systems. Among them, networked control systems (NCS) gained notable attention thanks to their application to industrial operations. Experimental NCS require expertise from control, computation, and communication disciplines. This requirement, together with the fragmentation of implementation platforms and experimental investigations, represents a challenge for the reproducibility and comparison of research results. In this paper, we tackle this problem by proposing a novel NCS benchmarking methodology that aids the reproducibility of NCS experiments. Relying on a novel approach to model the architectural elements and the delays of NCS, the methodology defines the experiment parameters and the relevant Key Performance Indicators (KPIs) that need to be observed during its execution. Furthermore, we detail the implementation of the first reproducible benchmarking platform for NCS. The proposed platform is open-source and designed to be easily reproducible and extensible by anyone. Finally, we replicate and evaluate the platform following the proposed NCS benchmarking methodology. The experimental results evaluate and compare the KPIs during the execution of the platform in different benchmarking scenarios, proving the validity of the proposed benchmarking methodology.

关键词： computer network security cyber-physical systems delays Internet of Things networked control systems networked control systems Internet of things network security Cyber-physical systems BENCHMARKS Platform delay performance indicators

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Real-time analysis of neuronal firing patterns via Hawkes processes

Real-time analysis of neuronal firing patterns via Hawkes pr...

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Asilomar Conference on Signals, systems & Computers

作者： László Gerencsér György Perczel Systems and Control Lab Institute for Computer Science and Control (SZTAKI) Eötvös Loránd Research Network (ELKH) Budapest Hungary Faculty of Information Technology and Bionics Pázmány Péter Catholic University Budapest Hungary

Quick and reliable real-time detection of the onset of epileptic seizures is a key computational component for the development of high quality closed loop neurostimulators. The objective of this paper is the construction of a low-cost algorithm for real-time statistical analysis of EEG signals of epileptic patients. The mathematical methodology is the theory of self-exiting point processes or Hawkes processes, see Truccolo (2016) or Lambert et al. (2018). The main advance is the development of a computationally feasible recursive maximum likelihood method for fitting a Hawkes process the impulse response function of which is a sum of exponential functions. The viability of the method is proven by strong mathematical heuristics and numerical tests on simulated data, based on a priori analysis of human data recorded during both inter-ictal and ictal epochs.

关键词： Maximum likelihood estimation Maximum likelihood detection Statistical analysis Firing Fitting Reliability theory Real-time systems

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Adaptive Modulation Metod for Communication systems Using Signals with Orthogonal Frequency Multiplexing

Adaptive Modulation Metod for Communication Systems Using Si...

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Eugeniy V. Rogozhnikov Yakov V. Kryukov Edgar Dmitriyev Dmitriy A. Pokamestov Danila A. Kondrashov Serafim A. Novichkov dept. of Telecommunications and Basic Principles of Radio Engineering Tomsk State University of Control Systems and Radioelectronics Tomsk Russian Federation Leading Research Center &#x201C 5G Radio Access Network with Open Architecture&#x201D Skolkovo Institute of Science and Technology Moscow Russian Federation

ISBN: (数字)9781665498043

ISBN: (纸本)9781665498050

This paper is devoted to the description of the adaptive modulation method for communication systems using signals with orthogonal frequency-division multiplexing. The present paper describes a method aimed at reducing the number of bit errors in signal transmission at low signal-to-noise ratio in channels with active interference, as well as multipath channels with unstable, rapidly changing characteristics. Reducing the probability of bit errors is one of the main tasks in the design of communication systems, along with increasing the data rate, reducing delay and increasing the number of users. Therefore, finding ways to optimally use the frequency-time resource for data transmission is an urgent task. The presented adaptive modulation technique uses pilot symbols to estimate the data link and compute maximum error vector magnitude. The proposed method made it possible to reduce the probability of a bit error by 15% compared to existing methods. Also, the presented method showed a spectral efficiency 1.5 times greater than the considered methods.

关键词： Performance evaluation Adaptive systems Spectral efficiency Channel estimation Symbols Interference Frequency division multiplexing

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Cybersecurity Threat Detection in the Behavior of IoT Devices: Analysis of Data Mining Competition Results

Cybersecurity Threat Detection in the Behavior of IoT Device...

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Federated Conference on Computer Science and Information systems (FedCSIS)

作者： Michał Czerwiński Marcin Michalak Piotr Biczyk Błażej Adamczyk Daniel Iwanicki Iwona Kostorz Maksym Brzęczek Andrzej Janusz Marek Hermansa Łukasz Wawrowski Artur Kozłowski QED Software Warsaw Poland Faculty of Mathematics University of Warsaw Warsaw Poland Łukasiewicz Research Network - Institute of Innovative Technologies EMAG Katowice Poland Department of Computer Networks and Systems Silesian<file://Silesian> University of Technology Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Silesian<file://Silesian> University of Technology Gliwice Poland EFIGO sp. z o.o. Katowice Poland

The paper discusses a data science competition centered around the development of an anomaly detection system for IoT devices. The competition utilized a unique environment that allowed for the operation and monitoring of real IoT devices, including scheduling of attacks on these devices. The environment was used to collect the data, which included both normal and attack-induced behavior of IoT devices. The paper presents the background of the competition, the top models submitted, and the competition results. The paper also includes a discussion about restrictions related to the use of synthetic attack data as input for constructing anomaly detection systems.

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Barrier Offset Varying-Parameter Dynamic Learning network for Solving Dual-Arms Human-Like Behavior Generation

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IEEE Transactions on Cognitive and Developmental systems 2025年

作者： Zhang, Zhijun Zhang, Mingyang Guo, Jinjia He, Haotian School of Automation Science and Engineering South China University of Technology Guangzhou510640 China Key Library of Autonomous Systems and Network Control Ministry of Education China Jiangxi Thousand Talents Plan Nanchang University Nanchang330031 China Guangzhou510335 China Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Shanxi University of Technology Hanzhong723001 China School of Information Science and Engineering Changsha Normal University Changsha410100 China School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Guangdong University of Petrochemical Technology Maoming525000 China School of Computer Science and Engineering Jishou University Jishou416000 China

Enabling robots to imitate human actions and perform tasks with high precision while avoiding potential obstacles in the environment can effectively enhance the interaction between social robots and humans. In this paper, to achieve higher precision trajectory tracking and obstacle avoidance for dual-arm humanoid robots, the barrier offset varying-parameter dynamic learning neural (BOVDL) network method is proposed and applied to dual-arm humanoid behavior generation scheme. To do so, a dual-arms humanoid robot model is set up, and transformed into a constrained time-varying quadratic programming (TVQP) problem. Secondly, by using lagrangian multiplier method and Karush-Kuhn-Tuchker condition, the inequality constrained TVQP is converted as a time-varying equation with a barrier parameter. Thirdly, a varying-parameter dynamic learning network is presented to solve the time-varying equation with a barrier parameter. Computer simulation experiments are conducted to verify the feasibility, accuracy, and safety of the proposed BOVDL network method. Experimental results show that all 14 joints of the humanoid robot's arms are within the motion range of each real human arm's physical constraints. The maximum position error and velocity error between the desired trajectory and the actual trajectory of the end effector are less than 10-6m magnitude and 10-7m magnitude, respectively, representing a reduction of 5 orders of magnitude compared to the traditional varying-parameter convergent-differential neural network. Furthermore, the proposed method also enables the dual-arm humanoid robot to avoid collisions with obstacles while performing tasks, demonstrating the superiority of the proposed BOVDL network scheme. © 2016 IEEE.

关键词： Anthropomorphic robots

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Bayesian Framework for Multi-User Cooperative Radio SLAM

Bayesian Framework for Multi-User Cooperative Radio SLAM

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Hang Que Jie Yang Tao Du Shuqiang Xia Chao-Kai Wen Shi Jin National Mobile Communications Research Laboratory Southeast University Nanjing China Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China ZTE Corporation Shenzhen China State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung Taiwan

ISBN: (数字)9798350362244

ISBN: (纸本)9798350362251

The advancement of millimeter-wave communication technology heralds new sensing capabilities. By leveraging channel multipath parameter estimates, we can harness simultaneous localization and mapping (SLAM) for precise user equipment (UE) localization and radio map construction in 6 G communication systems. Particularly in multi-UE scenarios, SLAM empowers base stations to amalgamate the local radio maps of various UEs efficiently. This study introduces a novel Bayesian framework specifically designed for multi-UE SLAM, complemented by a tailored factor graph. We also unveil a two-stage multi-UE SLAM algorithm. Our simulation results reveal that this algorithm substantially enhances radio map construction accuracy by $\mathbf{4 8. 5 \%}$ and UE localization accuracy by $13.5 \%$, outperforming single-UE cases. Moreover, the algorithm demonstrates remarkable adaptability to environmental changes, showcasing its potential for long-term evolution in dynamic settings.

关键词： Location awareness Simultaneous localization and mapping Accuracy Communication systems Heuristic algorithms Simulation Bayes methods Sensors Millimeter wave communication Land mobile radio

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Learning-based control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy

Learning-based Control for PMSM Using Distributed Gaussian P...

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Annual Conference of Industrial Electronics Society

作者： Zhenxiao Yin Xiaobing Dai Zewen Yang Yang Shen Georges Hattab Hang Zhao Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Chair of Information-oriented Control Technical University of Munich Munich Germany Center for Artificial Intelligence in Public Health Research (ZKI-PH) Robert Koch Institute Berlin Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Hong Kong China

The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase in the requirements for power supply components, including permanent magnet synchronous motors (PMSMs). To infer the unknown part of the system, machine learning techniques are widely employed, especially Gaussian process regression (GPR) due to its flexibility of continuous system modeling and its guaranteed performance. For practical implementation, distributed GPR is adopted to alleviate the high computational complexity. However, the study of distributed GPR from a control perspective remains an open problem. In this paper, a control-aware optimal aggregation strategy of distributed GPR for PMSMs is proposed based on the Lyapunov stability theory. This strategy exclusively leverages the posterior mean, thereby obviating the need for computationally intensive calculations associated with posterior variance in alternative approaches. Moreover, the straightforward calculation process of our proposed strategy lends itself to seamless implementation in high-frequency PMSM control. The effectiveness of the proposed strategy is demonstrated in the simulations.

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