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5th International Conference on Electrical engineering and control Applications, ICEECA 2022

作者： Ikram, Touitou Salim, Ziani Faculty of Engineering University of Constantine 1 Constantine Algeria Laboratory of Automatic Robotic and Control Systems Constantine Algeria

ISBN: (纸本)9789819700448

The goal of this research is to determine how to lower blood glucose levels when the pancreas is unable to produce the insulin that plays a key part in lowering blood glucose levels. A Bergman’s model of type 1 diabetes was considered and implemented in MATLAB-SIMULINK environment. This study aims to create a monitoring system that can track glucose level. Fuzzy inference system of Mamdani type and a PID controller are utilized to optimize the control of blood glucose levels to normal levels. Initially, MATLAB is used to create the process mathematical model. Then, the system is controlled using PID and fuzzy logic controllers, respectively. Finally, the outcomes of simulations reveal that the fuzzy logic controller (FLC) outperforms the PID controller. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Three term control systems

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On Sparse Nonlinear System Identification Using Orthogonal Matching Pursuit, Orthogonal Least Squares and LASSO 32

On Sparse Nonlinear System Identification Using Orthogonal M...

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32nd Mediterranean Conference on control and Automation, MED 2024

作者： Wei, Hua-Liang The University of Sheffield The Department of Automatic Control and Systems Engineering SheffieldSI 3JD United Kingdom

ISBN: (纸本)9798350395440

System identification, as a rich and vital discipline, provides a practical and general methodology and tool for quantitatively modelling the input-output relationships of dynamical systems. Sparse nonlinear system identification (SNSI), especially parametric sparse nonlinear system identification (PSNSI), is an important and vital field of research with a wide range of applications. This work is concerned with PSNSI and particular attention is paid to the assessment of three well-known mainstream sparse learning methods, namely, orthogonal least squares (OLS), orthogonal matching pursuit (OMP) and least absolute shrinkage and selection operator (LASSO). The performances of these methods are tested and evaluated through three case studies relating to PSNSI problems. The research results and findings of this work provide practical useful information and guidance for researchers to better choose or adapt methods when solving PSNSI problems. © 2024 IEEE.

关键词： Dynamical systems

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Voltage and power control for distributed generation units in islanded microgrids 6th

Voltage and power control for distributed generation units i...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Rouch, T. Bagheri M’zoughi, F. Aboutalebi, P. Ahmad, I. Garrido, A.J. Garrido, I. Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country Bilbao Spain

ISBN: (纸本)9781032905570

This article presents an optimized control strategy tailored for DC islanded microgrids, featuring a voltage controller based on mixed H2/H∞ state feedback using linear matrix inequalities (LMIs) and a power controller guided by droop characteristics. A polytopic modeling approach addresses system uncertainties and nonlinearities. The controller aims to stabilize the system, reject disturbances, equitably distribute power among distributed generation units (DGUs), and minimize energy consumption. Regional pole placement ensures welldamped transient responses. Simulation results demonstrate effective management of load perturbations and DGU disconnections, with a comparative analysis against an H∞ controller offering additional insights into performance. © 2025 The Author(s).

关键词： Microgrids

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Analysis of the Findings of the Study of the Time to Saturation of Current Transformer Magnetic Circuits Located at Electric Power Facilities

Analysis of the Findings of the Study of the Time to Saturat...

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2024 International Ural Conference on Electrical Power engineering, UralCon 2024

作者： Yablokov, Andrey Panashchatenko, Anton Ivanovo State Power Engineering University ISPU Department of Electric Power Systems Automatic Control Ivanovo Russia

ISBN: (纸本)9798350386028

Emergencies associated with incorrect operation of relay protection and automation (RPA) devices due to saturation of current transformers (CTs) can lead to great economic damage. The article presents an analysis of regulatory and technical documentation containing requirements for the quality of CT functioning in transient modes, statistical data on the results of calculations performed in accordance with the requirements of GOST R 58869-2019, as well as an analysis of the correctness of the assumptions introduced by it. To calculate the time to CTs saturation a special program was developed that automates the calculation methods, taking into account the assumptions focused on performing the manual calculations. The program takes into account the variation of the short circuit switching angle, the phase difference of the short circuit currents flowing through the branches feeding the short circuit point, the calculation of all CTs of a three-phase group with automatic selection of the worst result. The results obtained allow us to conclude about the relative number of CTs that do not meet the requirements of GOST R 58869-2019, the need to modernize existing methods and possible directions for such modernization. In addition, the article provides recommendations on the creation of automatic specialized software systems that can be used in the work of design, operating and research entities when they calculate the time to saturation of the CT magnetic circuits. © 2024 IEEE.

关键词： Transformer protection

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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2024年第02期16卷 1-18页

作者： PETRESCU, Alexandru TRUICA, Ciprian-Octavian APOSTOL, Elena-Simona PASCHKE, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania Fraunhofer Institute for Open Communication Systems Berlin Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors

关键词： Sentiment analysis

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Improving Common Spatial Patterns in Brain-Computer Interface Using Dynamic Time Warping and EEG Normalization 2

Improving Common Spatial Patterns in Brain-Computer Interfac...

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2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Mohamed, Mohamed A.A. Mansour, Salem Soulatiantork, Payam Ang, Kai Keng Soon, Phua Kok Arvaneh, Mahnaz University of Sheffield Automatic Control and Systems Engineering Department Sheffield United Kingdom Singapore

ISBN: (纸本)9798350300802

Common spatial patterns (CSP) is widely employed for spatial filtering and feature extraction in electroencephalogram (EEG)-based brain-computer interfaces (BCIs), However, the non-stationary nature of EEG signals can lead to poor estimation of CSP. To address this drawback, this paper proposes a novel algorithm called scaled and warped CSP (SW-CSP). The proposed algorithm enhances the classical CSP by reducing within EEG class non-stationarity across both time and amplitude domains, followed by automatically selecting the most discriminative features. First, the maximum-minimum scaling is applied to align amplitude of each EEG trial to its class average. Next, dynamic time warping (DTW) temporally aligns each scaled EEG trial to its class average. Thereafter, the scaled and warped EEG trials are used to compute the CSP covariance matrices. Finally, the proposed Fisher's score is used to select most discriminative SW-CSP filters. The proposed SW-CSP algorithm is evaluated using two datasets, and compared with the CSP algorithm and the previously proposed DTW-CSP. The results showed that the SW-CSP significantly outperformed both CSP and DTW-CSP (p © 2023 IEEE.

关键词： brain-computer interface common spatial patterns dynamic time warping EEG Fisher's score non-stationarity

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Assessing Uncertainty in Space Weather Forecasting Using Quantile Regression and Complex Nonlinear systems Identification Techniques 6

Assessing Uncertainty in Space Weather Forecasting Using Qua...

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6th International Conference on Computing, Electronics and Communications engineering, iCCECE 2023

作者： Wei, Hua-Liang Balikhin, Michael A. Boynton, Richard J. Walker, Simon N. The University of Sheffield Dept. of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350340921

Space weather forecasting is of global interest, and its importance is well established in research community and recognized by government, industries and stockholders. Over the past years, many types of predictive models have been developed in the literature. There is a general agreement that forecasting models should not only provide point prediction but also inform the uncertainty associated with the prediction. This study presents a novel method bases on quantile regression and complex dynamic modelling for measuring uncertainties in space weather forecasting. The approach is implemented using Quantile regression and Nonlinear AutoRegressive Moving Average with Exogenous inputs (NARMAX) methods (for short the approach is called Q-NARMAX). The method is applied to Disturbance storm index (Dst) observations to examine its interpretability and capability for uncertainty analysis. Results show that the proposed Q-NARX model can produce excellent predictions of the Dst index, and meanwhile provides a measure for assessing the uncertainty in the forecast. The innovative integration of quantile regression, complex dynamic modelling and nonlinear system identification techniques enables the proposed work to have following attractive advantages and properties: 1) it can produce excellent prediction accuracy for space weather forecasting, 2) it uses transparent models to approximate (represent) black-box systems, enabling to interpret the dependent relationship between space weather indices (system outputs) and their drivers (system inputs), and 3) more importantly, it allows for uncertainty assessment and analysis of models and forecasts. © 2023 IEEE.

关键词： Uncertainty analysis

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Real-time Tiredness Detection System using Nvidia Jetson Nano and OpenCV 11

Real-time Tiredness Detection System using Nvidia Jetson Nan...

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11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Florian, Nicolae Popescu, Dumitru Hossu, Andrei Department of Automatic Control and Systems Engineering University Politehnica Bucuresti Bucharest060042 Romania Academy of Romanian Scientists Romania

In this paper, we explore how to use a Nvidia Jetson Nano and Python to create a system that detects weariness in a person's face using computer vision and machine learning techniques. The system captures the person's face in real time, preprocesses the picture to cut noise, then detects the face using Haar cascades. Next, using computer vision algorithms, characteristics associated with weariness, such as the eyes, are retrieved. These characteristics are then used to build a machine learning model that can predict weariness in the live stream feed. Lastly, using a graphical user interface, the findings are shown, and the system may be fine-tuned to increase accuracy. This device might be used in applications such as driver monitoring and traffic safety. © 2024 The Authors.

关键词： Graphical user interfaces

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Distributed formation control of multiple aerial vehicles based on guidance route

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Chinese Journal of Aeronautics 2023年第3期36卷 368-381页

作者： Jinyong CHEN Rui ZHOU Guibin SUN Qingwei LI Ning ZHANG School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Science and Technology on Information Systems Engineering Laboratory Nanjing 210007China AVIC Xi’an Flight Automatic Control Research Institute Xi’an 710076China

Formation control of fixed-wing aerial vehicles is an important yet rarely addressed problem because of their complex dynamics and various motion constraints,such as nonholonomic and velocity *** guidance-route-based strategy has been demonstrated to be applicable to fixed-wing ***,it requires a global coordinator and there exists control lag,due to its own *** this reason,this paper presents a fully distributed guidance-route-based formation approach to address the aforementioned ***,a hop-count scheme is introduced to achieve distributed implementation,in which each aircraft chooses a neighbor with the minimum hop-count as a reference to generate its guidance route using only local ***,the model predictive control algorithm is employed to eliminate the control lag and achieve precise formation shape *** addition,the stall protection and collision avoidance are also ***,three numerical simulations demonstrate that our proposed approach can implement precise formation shape control of fixed-wing aircraft in a fully distributed manner.

关键词： Formation shape control Fixed-wing aircraft Guidance route Hop-count estimation Model predictive control

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Foreign Object Debris detection at aerodromes using YOLOv5 27

Foreign Object Debris detection at aerodromes using YOLOv5

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27th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2024

作者： Suder, Jakub Marciniak, Tomasz Poznan University of Technology Faculty of Automatic Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Division of Electronic Systems and Signal Processing Jana Pawla II 24 Poznań60-965 Poland

ISBN: (纸本)9788362065486

The latest EASA recommendations from 2024 indicate the possibility of using machine learning techniques in aerodrome monitoring. The aim of the work was to analyze solutions and prepare FOD (Foreign Object Debris) object detection software on aerodromes. In order to implement the issue, a dataset of photos and video recordings for testing algorithms was developed. The dataset consists of 1480 photos showing FOD at aerodromes and photos of the runway itself, according to EASA and FAA recommendations. FOD detection was implemented using a classical, k-means method and effective YOLOv5. © 2024 Division of Signal Processing and Electronic systems, Poznan University of Technology (DSPES PUT).

关键词： Video recording

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