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2023 International Conference on Control, automation and Diagnosis, ICCAD 2023

作者： Dlapa, Marek Tomas Bata University in Zlin Faculty of Applied Informatics Department of Automation and Control Engineering Zlin760 05 Czech Republic

ISBN: (纸本)9798350347074

Application of Robust Control Toolbox for Time Delay Systems implemented in the Matlab system to the oscillating plant with uncertain time delay using the D-K iteration and algebraic approach. The algebraic approach combines the structured singular value, algebraic theory and algorithm of global optimization solving remaining issues in structured singular value framework. The algorithm of global optimization can be alternated with direct search methods such as Nelder-Mead simplex method giving solutions for problems with one local extreme. As a global optimization method, Differential Migration is used proved to be reliable in solving this type of problems. The D-K iteration represents a standard method in the structured singular value theory. The results obtained from the D-K iteration are compared with the algebraic approach. © 2023 IEEE.

关键词： Global optimization

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Diffusion probabilistic model based face anonymization in embedded environments 14

Diffusion probabilistic model based face anonymization in em...

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14th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2023

作者： Morvay, Balázs Tibor Béres, Bálint Torma, Szabolcs Szegletes, Luca Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economic Műegyetem rkp. 3 BudapestH-1111 Hungary

ISBN: (纸本)9798350325652

Computer vision systems depend on vast and diverse datasets to achieve optimal performance. However, in scenarios where data collection involves personal identifiable information, privacy-protecting legislation can impede the acquisition process. To address this challenge, we present a novel face anonymization pipeline capable of running on embedded platforms. The proposed methodology combines denoising diffusion probabilistic models (DDPMs) and advanced image super-resolution techniques, such as DFDNet and ESPCN, to achieve high-quality anonymized facial images while preserving crucial facial keypoint locations. We conduct a comprehensive evaluation of the pipeline’s performance, encompassing image quality, keypoint precision, and efficiency on two popular single-board computers, namely the Nvidia Jetson Nano and the Raspberry Pi 4B. The source code is available at https://***/balazsmorv/facediffusion. © 2023 IEEE.

关键词： Pipelines

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Quadratic Regression Model Based Predictive Control of PMSM Drives with Field Weakening Operation Capability Constrained to the Linear Modulation Range 32

Quadratic Regression Model Based Predictive Control of PMSM ...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Bándy, Kristóf Stumpf, Péter Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics Megyetem rkp. 3. H-1111 Budapest Hungary

ISBN: (纸本)9798350399714

Continuous Control Set Model Predictive Control in power electronics has prospective outlooks, however, due to the computational requirements, these techniques are still underutilized. In the paper, a novel method is discussed that allows the reduction of the complex optimization underlying the predictive control algorithm. However, the optimization is further restricted with a non-linear (circular) constraint, that allows the modulator to remain in the linear modulation region. The paper offers an effective solution to the optimization problem, with simulation results showing the effectiveness of the proposed method. © 2023 IEEE.

关键词： Electric drives

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Model Identification and Control of Electromagnetic Actuation in Continuous Casting Process With Improved Quality

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 203-215页

作者： Isabela Birs Cristina Muresan Dana Copot Clara Ionescu Research Group of Dynamical Systems and Control Faculty of Engineering and ArchitectureGhent University and with EEDT Decision&ControlFlanders Make ConsortiumTech Lane Science Park 125 and 131B-9052 GhentBelgium.I.Birs the Automation Department Faculty of Automation and Applied InformaticsTechnical University of Cluj-NapocaRomania IEEE

This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.

关键词： Electromagnetic actuator fractional order control fractional order system model non-Newtonian material

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Real-Time Validation of Quadratic Regression Model-Based Predictive Control of Grid-Side Converters

Real-Time Validation of Quadratic Regression Model-Based Pre...

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2023 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2023

作者： Bándy, Kristóf Gábor Stumpf, Péter Pál Chowdhury, MD Moshiur Rahman Süto, Zoltán Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

ISBN: (纸本)9783800760916

A quadratic regression model-based predictive control method is presented for grid-side converters. The control scheme calculates the cost function for seven voltage vectors of the inverter and extends it to the entire modulation region using regression. Then a constrained optimization problem must be solved to find the most feasible control action in this continuous control space. The found optimal voltage vector can be generated using Pulse-Width Modulation methods. The control method is validated in a custom Hardware-in-the-Loop environment using model-based rapid-prototyping tools of Matlab/Simulink. Measurement results show the viability of the method. © VDE VERLAG GMBH · Berlin · Offenbach.

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An Industry 4.0 Oriented Predictive Maintenance Solution Deployed in Real-World Automotive Manufacturing Facilities 24

An Industry 4.0 Oriented Predictive Maintenance Solution Dep...

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24th International Conference on Control Systems and Computer Science, CSCS 2023

作者： Nicolae, Andrei Burlacu, Camelia Stanciu, Andrei Korodi, Adrian Posa, Bogdan Mihaila, Flavius Politehnica University Department of Automation and Applied Informatics Timişoara Romania Industrial Engineering Continental Automotive Romania Timişoara Romania

ISBN: (纸本)9798350313390

Industry 4.0 drives a significant revolution in the industrial manufacturing area in recent years, with predictive maintenance consolidating its potential to increase efficiency and productivity by reducing downtime. The research presented in the current paper transposes the previously mentioned concepts into a real-world automotive manufacturing facility. A software solution capable of predicting the probability of wear down-induced cylinder break downs was developed and installed at an industrial partner, aiming to reduce the number of productivity-impacting complete production line shutdown events. © 2023 IEEE.

关键词： Industry 4.0

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Artificial Intelligence in Primary Care: An Overview

Artificial Intelligence in Primary Care: An Overview

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作者： Turcian, Darius Stoicu-Tivadar, Vasile Politehnica University Timişoara Department of Automation and Applied Informatics Timişoara Romania

ISBN: (纸本)9781643682501

With the increase in computing power and the development of numerous technological devices that facilitate remote work, the involvement of artificial intelligence in medicine has seen a significant increase to help the doctor make decisions and intervene in the medical process and telemedicine. In this paper, we gave an overview of the practical involvement of artificial intelligence through different support systems used in primary medicine or telemedicine and also identified the possibilities and opportunities for the development of new support systems for family medicine. Thus, we identified systems used for primary diagnosis, diagnosis of hypertension, early detection of heart abnormalities, detection of diabetes, support in the prescription process, helping clinicians in the daily workflow by providing certain answers to questions, treatment guidance, determining patient priority for treatment for SARS-CoV-2 infection or early detection of disease, support of artificial ventilation in medical emergency centers, remote support for treatments and medication. © 2022 The authors and IOS Press.

关键词： Telemedicine

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A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow

A Machine Learning-Based Privacy-Preserving Approach to Inco...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Dindar, Burak Saner, Can Berk Polat, Dogukan Yigit Çakmak, Huseyin Kemâl Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany National University of Singapore Department of Electrical and Computer Engineering Singapore National University of Singapore School of Computing Singapore

ISBN: (纸本)9789531842976

In order to achieve the goal of a carbon-neutral power system, significant changes to the power grid are underway, necessitating enhanced interoperability between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) for effective grid operation, particularly in light of the growing number of distributed generators (DGs). Data privacy concerns, however, complicate decision-making processes, particularly when integrating DGs into system-wide dispatch decisions. In this paper, we propose a machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs. The methodology involves training three ML models to represent the behavior of the DS, thereby replacing the standard power flow model that contains sensitive information. Notably, we utilize a novel tailored neural network (NN) architecture to enhance computational efficiency in mapping the feasible region of the DS. Additionally, we employ open-source data to construct the Baden-Wü rttemberg (Germany) electricity grid, allowing to test our method not only on standard systems but also on a model that more accurately represents real-world power systems. The numerical case studies verify that the proposed method achieves results comparable to standard AC optimal power flow (AC-OPF) in both cost-optimality and computational time. © 2024 IEEE.

关键词： Differential privacy

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Matlab GUI-based Tool to Determine Performance Metrics of Physical Unclonable Functions 31

Matlab GUI-based Tool to Determine Performance Metrics of Ph...

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31st International Conference on Cybernetics and informatics, K and I 2022

作者： Kareem, Husam Almousa, Khaleel Dunaev, Dmitriy Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics BudapestH-1111 Hungary

ISBN: (数字)9781665487757

ISBN: (纸本)9781665487757

This paper presents a MATLAB Graphical User Interface (GUI) based tool that determines the performance evaluation metrics of the physically unclonable functions (PUFs). The PUFs are hardware security primitives which can be utilized in several hardware security applications like integrated circuits protection, device authentication, secret key generation, and hardware obfuscation. Like any other technology approach, PUFs evaluation requires testing different performance metrics, each of which can be determined by at least one mathematical equation. The proposed tool (PUFs Tool) reads the PUF instances' output and then computes and generates the values of the main PUFs' performance metrics: uniqueness, reliability, uniformity, and bit-aliasing. In addition, it generates a bar code for each PUF instance considered in the evaluation process. The PUFs Tool is designed and developed using the app designer of MATLAB software 2021b. © 2022 IEEE.

关键词： MATLAB

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Senkerik, Roman Byrski, Aleksander Guzowski, Hubert Janku, Peter Kadavy, Tomas Oplatkova, Zuzana Kominkova Matusu, Radek Pluhacek, Michal Pekar, Libor Smolka, MacIej Viktorin, Adam Tomas Bata University A.I. Lab Faculty of Applied Informatics Department of Informatics and Artificial Intelligence Zlin Czech Republic Tomas Bata University Faculty of Applied Informatics Department of Automation and Control Engineering Zlin Czech Republic Institute of Computer Science Agh University of Science and Technology Krakow Poland

ISBN: (纸本)9798350337020

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics. © 2023 IEEE.

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