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A low voltage ride through (LVRT) strategy using an active superconductor fault current limiter (SFCL) for a virtual synchronous generator (VSG) connected to a weak grid

A low voltage ride through (LVRT) strategy using an active s...

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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Kisinga, Daniel Angelo Trodden, Paul Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9798350396782

A function of grid-connected VSGs is facilitating the recovery of sagging voltages to nominal levels, achieved by supplying reactive power (Q) to the grid. During normal operation, however, a VSG is required to supply active power (P) at unity power factor and, therefore, in order to supply the Q required in the event of a sagging voltage, the VSG must change its control mode from P-supply to PQ- or Q-supply. Such transitions may induce high current flows—caused by the sudden reduction of the voltage during the sag—which are potentially damaging to the power semiconductor devices of the VSG;if these effects are to be avoided, the supplied current must be limited to its rated value, but this may result in a low power transfer from the VSG to the grid. To circumvent these problems, in this paper we propose a LVRT strategy using an active SFCL. We show that the proposed strategy, which combines a PQ decoupling scheme with an active SFCL, ensures maximum power transfer with an improved transient response during LVRT. © 2023 IEEE.

关键词： active SFCL LVRT PQ control voltage sag VSG

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Reinforcement Learning for Multiple-Input Multiple-Output control in Metal Additive Manufacturing 20

Reinforcement Learning for Multiple-Input Multiple-Output Co...

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20th IEEE International Conference on Networking, Sensing and control, ICNSC 2023

作者： Grais, Emad M. Notley, Scott V. Panoutsos, George University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350369502

In laser powder bed fusion additive manufacturing, using fixed values for the process parameters (beam power, velocity, and other parameters) may not lead to homogeneously distributed heat in all locations in the build, especially around complex design features. This could lead to builds with defects, leading to poor mechanical and micro-structure properties. To guarantee heat homogeneity, the process parameters need to be actively controlled to adapt to different locations in the build. Builds with varying geometrical features would need different control strategies. In this work, we propose to use reinforcement learning (RL) to control, for the first time, simultaneously multiple AM process parameters to achieve consistent melting properties. Our results show that using RL as a multiple-input multiple-output control system achieves a more consistent meltpool geometry. © 2023 IEEE.

关键词： Reinforcement learning

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Hybrid offshore wind turbines: control-oriented modeling approaches 6th

Hybrid offshore wind turbines: Control-oriented modeling app...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Ahmad, I. M’zoughi, F. Aboutalebi, P. Garrido, I. Garrido, A.J. Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Engineering School of Bilbao—EIB/BIE Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Bilbao Spain

ISBN: (纸本)9781032905570

In the pursuit of sustainable electricity generation from offshore wind and wave energy, the combination of Floating Offshore Wind Turbines (FOWTs) and Oscillating Water Columns (OWCs) has emerged as a promising solution to enhance the working lifespan of this kind of systems. This study introduces a control-focused modeling approach, using empirical data collected from the widely accepted FAST environment, to implement advanced control laws for these integrated platforms. Leveraging Long Short-Term Memory (LSTM) and Artificial Neural Networks (ANN), the research yields predictive models that effectively capture the platform pitch dynamics so as to optimize control strategies. By integrating advanced machine learning techniques, these approaches address the challenges of modeling floating offshore structures in dynamic environments. In this sense, the neuro-estimators developed in this study closely match the original plant results, offering researchers a straightforward way to implement complex control schemes that could hardly be implemented over the original non-linear system. © 2025 The Author(s).

关键词： Offshore wind turbines

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Utilization of Uniform Circular Array for Estimating RF Source Location in Real-time

Utilization of Uniform Circular Array for Estimating RF Sour...

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2024 International Conference on control, Automation and Diagnosis, ICCAD 2024

作者： Alsayegh, Hamad Almuhaihi, Mohammad University of Sheffield Automatic Control and Systems Engineering Department United Kingdom University of Michigan Aerospace Engineering Department United States

ISBN: (纸本)9798350361025

This Radio Frequency (RF) source location estimation scheme utilizes angles of arrival of a signal source acquired from the Multiple Signal Classification (MUSIC) algorithm. In reliance on that as a Maximum Likelihood estimation, the obtained angles are augmented to an adaptive probability distribution function (PDF), which is then employed to estimate the location of the RF emitter by feeding the PDF to an Extended Kalman Filter (EKF). Numerous use cases and theoretical works have been presented in the literature. Some of these papers mention applications regarding implementing DoA algorithms in dynamic platforms like in [9], [10], [11], [12], and [13] mostly all of them use Uniform Linear Array (ULA), four of them working with Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT), and one with MUSIC Direction of Arrival (DoA) method. In [14], MUSIC was used with a Uniform Circular Array (UCA). However, less coupling has been incorporated with the covariance of measurement error. In this paper, the dynamic 2D DoA MUSIC algorithm used in a platform, applied together with an EKF estimation and coupled with measurement covariance in a simulation environment to precisely locate an RF emitter and provide high-resolution Line-of-Sight (LOS). © 2024 IEEE.

关键词： Multiple signal classification

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control of Blood Glucose Level in Diabetics: A Simulation and Comparison Study 5th

Control of Blood Glucose Level in Diabetics: A Simulation an...

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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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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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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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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

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IEEE Transactions on Affective Computing 2024年第2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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