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Guest Editorial: Advances in High Voltage DC Systems/Grids control, Operation, and Protection

High Voltage 2020年第5期5卷 499-500页

作者： Kumars Rouzbehi Ali Mehrizi-Sani Department of Systems Engineering and Automatic Control University of SevilleSpain. Bradley Department of Electrical and Computer Engineering Virginia TechUSA.

Interconnections between AC power systems,power transmission with higher efficiency,and aggregation and delivery of power from offshore wind farms to different AC regions are among the main drivers for the development of HVDC *** grids can result in lower demand variability,higher flexibility,superior electricity market management,and higher economic *** is expected that isolated HVDC systems transition to an HVDC grid that overlays the existing AC *** a substantial development also results in a number of critical technical challenges related to system control,operation,and protection,which should be properly and accurately *** Special Issue focuses on the recent achievements and advancements in overcoming these *** papers for publications in this Special Issue fall into four major topics:devices,control,operation,and protection.

关键词： properly operation offshore

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Multi-agent Collision Avoidance Based on Buffered Voronoi Cells and B-Splines 16th

Multi-agent Collision Avoidance Based on Buffered Voronoi C...

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16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： Dinh, Cong Khanh Prodan, Ionela Stoican, Florin LCIS Valence26000 France Department of Automatic Control and Systems Engineering National University of Science and Technology "Politehnica" Bucharest 313 Splaiul Independenţei Bucharest060042 Romania

ISBN: (纸本)9783031817236

This paper tackles the challenging issue of collision avoidance among multiple dynamical agents, a problem known for its non-convex nature and computational complexity. Our proposed solution involves decomposing the space into time-varying Voronoi cells with buffer zones, exploiting the versatility of B-splines to reconfigure trajectories when collisions are predicted. This approach is integrated into a Model Predictive control (MPC) framework, implemented in a distributed manner where agents communicate predicted control point sequences defining the B-spline curves. Through simulation testing across various scenarios, our approach demonstrates significant promise, paving the way for experimental validation and real-world applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive control systems

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Enriching Physical-Virtual Interaction in AR Gaming by Tracking Identical Real Objects

arXiv

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arXiv 2025年

作者： Yu, Liuchuan Huang, Ching-I Wang, Hsueh-Cheng Yu, Lap-Fai Computer Science Department George Mason University FairfaxVA United States Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Taiwan Faculty of Electrical and Computer Engineering Department and Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Taiwan Faculty of Computer Science Department George Mason University FairfaxVA United States

Augmented reality (AR) games, particularly those designed for headsets, have become increasingly prevalent with advancements in both hardware and software. However, the majority of AR games still rely on pre-scanned or static scenes, and interaction mechanisms are often limited to controllers or hand-tracking. Additionally, the presence of identical objects in AR games poses challenges for conventional object tracking techniques, which often struggle to differentiate between identical objects or necessitate the installation of fixed cameras for global object movement tracking. In response to these limitations, we present a novel approach to address the tracking of identical objects in an AR scene to enrich physical-virtual interaction. Our method leverages partial scene observations captured by an AR headset, utilizing the perspective and spatial data provided by this technology. Object identities within the scene are determined through the solution of a label assignment problem using integer programming. To enhance computational efficiency, we incorporate a Voronoi diagram-based pruning method into our approach. Our implementation of this approach in a farm-to-table AR game demonstrates its satisfactory performance and robustness. Furthermore, we showcase the versatility and practicality of our method through applications in AR storytelling and a simulated gaming robot. Our video demo is available at: https://***/ rPGkLYuKvCQ. Copyright © 2025, The Authors. All rights reserved.

关键词： Computational efficiency

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Machine Learning Detects Anomalies in OPS-SAT Telemetry 23rd

Machine Learning Detects Anomalies in OPS-SAT Telemetry

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23rd International Conference on Computational science, ICCS 2023

作者： Ruszczak, Bogdan Kotowski, Krzysztof Andrzejewski, Jacek Musial, Alicja Evans, David Zelenevskiy, Vladimir Bammens, Sam Laurinovics, Rodrigo Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka 16 Gliwice44-100 Poland KP Labs Konarskiego 18C Gliwice44-100 Poland European Space Agency/ESOC Robert-Bosch-Str. 5 Darmstadt64293 Germany Telespazio Germany GmbH Europaplatz 5 Darmstadt64293 Germany IrbGS ltd "Viraki" Ance Parish IrbeneLV-3601 Latvia

ISBN: (纸本)9783031359941

Detecting anomalies in satellite telemetry data is pivotal in ensuring its safe operations. Although there exist various data-driven techniques for the task of determining abnormal parts of the signal, they are virtually never validated over real telemetries. Analyzing such data is challenging due to its intrinsic characteristics, as telemetry may be noisy and affected by incorrect acquisition, resulting in missing parts of the signal. In this paper, we tackle this issue and propose a machine learning approach for detecting anomalies in single-channel satellite telemetry. To validate its capabilities in a practical scenario, we build a dataset capturing the nominal and anomalous telemetry data captured on board OPS-SAT—a nanosatellite launched and operated by the European Space Agency. Our extensive experimental study showed that the proposed algorithm offers high-quality anomaly detection in real-life satellite telemetry, reaching 98.4% accuracy over the unseen test set. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Sample Complexity for Evaluating the Robust Linear Observers Performance under Coprime Factors Uncertainty

arXiv

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arXiv 2022年

作者： Zhang, Yifei Ukil, Sourav Kumar Sperilă, Andrei Sabău, Şerban Department of Electrical and Computer Engineering Stevens Institute of Technology NJ07030 United States Department of Automatic Control and Computer Science "Politehnica" University of Bucharest Bucharest Romania

This paper addresses the end-to-end sample complexity bound for learning in closed loop the state estimator-based robust H2 controller for an unknown (possibly unstable) Linear Time Invariant (LTI) system, when given a fixed state-feedback gain. We build on the results from Ding et al. (1994) to bridge the gap between the parameterization of all state-estimators and the celebrated Youla parameterization. Refitting the expression of the relevant closed loop allows for the optimal linear observer problem given a fixed state feedback gain to be recast as a convex problem in the Youla parameter. The robust synthesis procedure is performed by considering bounded additive model uncertainty on the coprime factors of the plant, such that a min-max optimization problem is formulated for the robust H2 controller via an observer approach. The closed-loop identification scheme follows Zhang et al. (2021), where the nominal model of the true plant is identified by constructing a Hankel-like matrix from a single time-series of noisy, finite length input-output data by using the ordinary least squares algorithm from Sarkar et al. (2020). Finally, a H∞ bound on the estimated model error is provided, as the robust synthesis procedure requires bounded additive uncertainty on the coprime factors of the model. Copyright © 2022, The Authors. All rights reserved.

关键词： Additives

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Gain Scheduling Position control for Fully-Actuated Morphing Multi-Rotor UAVs

Gain Scheduling Position Control for Fully-Actuated Morphing...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Youssef Aboudorra Aaron Saini Antonio Franchi Robotics and Mechatronics Faculty of Electrical Engineering Mathematics & Computer Science University of Twente Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This work presents techniques for scheduling the position controller gains for a class of fully-actuated morphing multi-rotor UAVs that use synchronized tilting to change their actuation capabilities. The feasible set of forces and torques that can be produced by the platform changes with the tilting angle, thus the tracking and disturbance rejection capabilities also change. To exploit the platform limits, two methods are proposed for gain scheduling using a simplified example, then one method is tested in simulation with an omnidirectional morphing multi-rotor (OmniMorph). The simulation results show that the developed techniques achieve consistent position tracking performance along the range of tilting angles when rejecting step disturbance forces of values close to the maximum force capabilities. The proposed methods offer a trade-off between simplicity and accuracy, that could be potentially applied for any multi-rotor with synchronized tilting capabilities. A video summary can be found in: https://***/kH-rrO8gWeU

关键词： Accuracy Processor scheduling Attitude control Simulation Force Rotors Position control

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Carbon-Aware Computing in a Network of Data Centers: A Hierarchical Game-Theoretic Approach

arXiv

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arXiv 2024年

作者： Breukelman, Enno Hall, Sophie Belgioioso, Giuseppe Dörfler, Florian The KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Division of Decision and Control Systems Malvinas väg 10 StockholmSE-100 44 Sweden The Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Physikstrasse 3 Zürich8092 Switzerland

Over the past decade, the continuous surge in cloud computing demand has intensified data center workloads, leading to significant carbon emissions and driving the need for improving their efficiency and sustainability. This paper focuses on the optimal allocation problem of batch compute loads with temporal and spatial flexibility across a global network of data centers. We propose a bilevel game-theoretic solution approach that captures the inherent hierarchical relationship between supervisory control objectives, such as carbon reduction and peak shaving, and operational objectives, such as priority-aware scheduling. Numerical simulations with real carbon intensity data demonstrate that the proposed approach successfully reduces carbon emissions while simultaneously ensuring operational reliability and priority-aware scheduling. © 2024, CC BY-NC-ND.

关键词： Carbon

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Safety Assessment of Liquid Launch Vehicle Structures Based on Interpretable Belief Rule Base

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computer Systems science & engineering 2023年第10期47卷 273-298页

作者： Gang Xiang Xiaoyu Cheng Wei He Peng Han Beihang University School of Automation Science and Electrical Engineering Beijing100083China Beijing Aerospace Automatic Control Institute Beijing100070China School of Computer Science and Information Engineering Harbin Normal UniversityHarbin150025China Rocket Force University of Engineering Xi’an710025China

A liquid launch vehicle is an important carrier in aviation,and its regular operation is essential to maintain space *** the safety assessment of fluid launch vehicle body structure,it is necessary to ensure that the assessmentmodel can learn self-response rules from various uncertain data and not differently to provide a traceable and interpretable assessment ***,a belief rule base with interpretability(BRB-i)assessment method of liquid launch vehicle structure safety status combines data and ***,an innovative whale optimization algorithm with interpretable constraints is *** experiments are carried out based on the liquid launch vehicle safety experiment platform,and the information on the safety status of the liquid launch vehicle is obtained by monitoring the detection indicators under the simulation *** MSEs of the proposed model are 3.8000e-03,1.3000e-03,2.1000e-03,and 1.8936e-04 for 25%,45%,65%,and 84%of the training samples,*** can be seen that the proposed model also shows a better ability to handle small sample ***,the belief distribution of the BRB-i model output has a high fitting trend with the belief distribution of the expert knowledge settings,which indicates the interpretability of the BRB-i *** results show that,compared with other methods,the BRB-i model guarantees the model’s interpretability and the high precision of experimental results.

关键词： Liquid launch vehicle belief rule base with interpretability belief rule base whale optimization algorithm vibration frequency swaying angle

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Optimizing Membrane Distillation Configuration for Superior Heat and Mass Transfer

Optimizing Membrane Distillation Configuration for Superior ...

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2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024

作者： Arslan, Muhammad Haizhen, Xian Nouman Khalid Khan, M. Ali, Kashif Baig, Zaid Bin Tariq North China Electric Power University School Of Energy Power And Mechanical Engineering Beijing China University Of Engineering & Technology School Of Mechanical Engineering Lahore Pakistan North China Electric Power University School Of Renewable And Clean Energy Beijing China North China Electric Power University Department Of Control And Computer Science Beijing China

ISBN: (纸本)9798331515850

Membrane distillation (MD) has emerged as a promising technique for desalination and water purification, offering potential advantages in terms of energy efficiency and operational flexibility. However, challenges related to heat and mass transfer inefficiencies limit its widespread adoption. This study explores the use of innovative materials and optimized configurations to enhance heat and mass transfer in direct contact membrane distillation (DCMD) systems. By integrating advanced hybrid membranes with nano-coating techniques and evaluating their performance through simulation-based methodologies, we demonstrate significant improvements in thermal conductivity, mass transfer efficiency, and fouling resistance. The results indicate that the newly developed hybrid membranes not only enhance heat and mass transfer rates but also maintain high separation efficiency, ultimately leading to improved overall system performance. These findings provide a foundation for the further development of MD technologies and suggest pathways for overcoming existing limitations, paving the way for more sustainable and efficient water treatment solutions. © 2024 IEEE.

关键词： Desalination

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Transforming stroop task cognitive assessments with multimodal inverse reinforcement learning

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Smart Health 2025年 36卷

作者： Abbasi, Ali Gong, Jiaqi Korivand, Soroush Department of Control and Computer Engineering Polytechnic University of Turin Italy Department of Computer Science The University of Alabama United States Department of Mechanical Engineering Mississippi State University United States

Stroop tasks, recognized for their cognitively demanding nature, hold promise for diagnosing and monitoring neurodegenerative diseases. Understanding how humans allocate attention and resolve interference in the Stroop test remains a challenge;yet addressing this gap could reveal key opportunities for early-stage detection. Traditional approaches overlook the interplay between overt behavior and underlying neural processes, limiting insights into the complex color-word associations at play. To tackle this, we propose a framework that applies Inverse Reinforcement Learning (IRL) to fuse electroencephalography (EEG) signals with eye-tracking data, bridging the gap between neural and behavioral markers of cognition. We designed a Stroop experiment featuring congruent and incongruent conditions to evaluate attention allocation under varying levels of interference. By framing gaze as actions guided by an internally derived reward, IRL uncovers hidden motivations behind scanning patterns, while EEG data — processed with advanced feature extraction — reveals task-specific neural dynamics under high conflict. We validate our approach by measuring Probability Mismatch, Target Fixation Probability-Area Under the Curve, Sequence Score, and MultiMatch metrics. Results show that the IRL-EEG model outperforms an IRL-Image baseline, demonstrating improved alignment with human scanpaths and heightened sensitivity to attentional shifts in incongruent trials. These findings highlight the value of integrating neural data into computational models of cognition and illuminate possibilities for early detection of neurodegenerative disorders, where subclinical deficits may first emerge. Our IRL-based integration of EEG and eye-tracking further supports personalized cognitive assessments and adaptive user interfaces. © 2025 The Authors

关键词： Cognitive assessment EEG Eye-tracking Inverse reinforcement learning Neurodegenerative diseases

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