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arXiv 2024年

作者： Etesami, S. Rasoul Srikant, R. Department of Industrial and Systems Engineering Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Electrical and Computer Engineering and Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States

We consider the problem of learning stable matchings with unknown preferences in a decentralized and uncoordinated manner, where "decentralized" means that players make decisions individually without the influence of a central platform, and "uncoordinated" means that players do not need to synchronize their decisions using pre-specified rules. First, we provide a game formulation for this problem with known preferences, where the set of pure Nash equilibria (NE) coincides with the set of stable matchings, and mixed NE can be rounded to a stable matching. Then, we show that for hierarchical markets, applying the exponential weight (EXP) learning algorithm to the stable matching game achieves logarithmic regret in a fully decentralized and uncoordinated fashion. Moreover, we show that EXP converges locally and exponentially fast to a stable matching in general markets. We also introduce another decentralized and uncoordinated learning algorithm that globally converges to a stable matching with arbitrarily high probability. Finally, we provide stronger feedback conditions under which it is possible to drive the market faster toward an approximate stable matching. Our proposed game-theoretic framework bridges the discrete problem of learning stable matchings with the problem of learning NE in continuous-action games. Copyright © 2024, The Authors. All rights reserved.

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Large-signal Stability Analysis of Grid-forming Inverters with Equivalent-circuit Models

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IEEE Transactions on Energy Conversion 2025年

作者： Baeckeland, Nathan Pal, Diptak Seo, Gab-Su Johnson, Brian Dhople, Sairaj National Renewable Energy Laboratory Power Systems Engineering Center GoldenCO80401 United States Hitachi Energy Ltd United States University of Texas Chandra Family Department of Electrical and Computer Engineering AustinTX United States University of Minnesota Department of Electrical and Computer Engineering MN United States

This paper proposes an energy function-based direct method for large-signal stability assessment of grid-forming (GFM) inverters leveraging an equivalent-circuit representation of all involved control- and physical-layer dynamics. Three different primary controls, a standard inner-current outer-voltage cascaded-control architecture, output CL filter, and reference-current saturation limiting are featured in the modeling and analysis framework. A composite energy function for the GFM inverter is obtained by summing up individual energy contributions gleaned from the circuit representation. The approach can readily be generalized to different primary controls, output-filter arrangements, and current limiters since it is based on a circuit-theoretic foundation. Numerical simulations validate the efficacy of the approach in estimating the critical clearing time following a large-signal disturbance. © 1986-2012 IEEE.

关键词： Electric network analysis

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Fabrication of MVDC multilayer insulation systems as flat samples for wide-body all-electric aircraft

Fabrication of MVDC multilayer insulation systems as flat sa...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Arian Azizi Anoy Saha Md Asifur Rahman Mona Ghassemi Jane Lehr Zero Emission Realization of Optimized Energy Systems (ZEROES) Laboratory Department of Electrical and Computer Engineering The University of Texas at Dallas Richardson TX USA Department of Electrical and Computer Engineering University of New Mexico Albuquerque UM USA

To fulfill the net zero emission goal, transportation sector, as the largest source of greenhouse gas (GHG) emissions in the United States, must be decarbonized. Electrification is regarded as one of the most promising approaches to decarbonizing transportation. Due to its annual growth, the aviation industry has also been targeted to be decarbonized. Fully electrification of aviation or all-electric aircraft (AEA) requires high power density and low system mass electric power systems (EPS), and to this end, moving towards MVDC is preferred. In our previous work, numerous Multilayer Multifunctional electrical Insulation (MMEI) systems have been designed. However, the dielectric strength and time-to-failure of the designed MMEI systems can only be determined by experimental tests. In this paper, the process of fabricating flat samples of down-selected MMEI designs by a compressionmolding process is discussed in detail.

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Sailing Through Point Clouds: Safe Navigation Using Point Cloud Based control Barrier Functions

arXiv

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arXiv 2024年

作者： Dai, Bolun Khorrambakht, Rooholla Krishnamurthy, Prashanth Khorrami, Farshad Control/Robotics Research Laboratory Electrical & Computer Engineering Department Tandon School of Engineering New York University BrooklynNY11201 United States

The capability to navigate safely in an unstructured environment is crucial when deploying robotic systems in real-world scenarios. Recently, control barrier function (CBF) based approaches have been highly effective in synthesizing safety-critical controllers. In this work, we propose a novel CBF-based local planner comprised of two components: Vessel and Mariner. The Vessel is a novel scaling factor based CBF formulation that synthesizes CBFs using only point cloud data. The Mariner is a CBF-based preview control framework that is used to mitigate getting stuck in spurious equilibria during navigation. To demonstrate the efficacy of our proposed approach, we first compare the proposed point cloud based CBF formulation with other point cloud based CBF formulations. Then, we demonstrate the performance of our proposed approach and its integration with global planners using experimental studies on the Unitree B1 and Unitree Go2 quadruped robots in various environments. © 2024, CC BY.

关键词： Robot programming

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Consensus control of Leader-Following Multi-Agent systems in Directed Topology With Heterogeneous Disturbances

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IEEE/CAA Journal of Automatica Sinica 2021年第2期8卷 423-431页

作者： Qinglai Wei Xin Wang Xiangnan Zhong Naiqi Wu the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049and also with Qingdao Academy of Intelligent IndustriesQingdao 266109China the Department of Computer and Electrical Engineering and Computer Science Florida Atlantic UniversityBoca Raton FL33431 USA the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and TechnologyMacao 999078China

This paper investigates the consensus problem for linear multi-agent systems with the heterogeneous disturbances generated by the Brown *** main contribution is that a control scheme is designed to achieve the dynamic consensus for the multi-agent systems in directed topology interfered by stochastic *** traditional ways,the coupling weights depending on the communication structure are static.A new distributed controller is designed based on Riccati inequalities,while updating the coupling weights associated with the gain matrix by state errors between adjacent *** introducing time-varying coupling weights into this novel control law,the state errors between leader and followers asymptotically converge to the minimum value utilizing the local *** the Lyapunov directed method and It?formula,the stability of the closed-loop system with the proposed control law is *** simulation results conducted by the new and traditional schemes are presented to demonstrate the effectiveness and advantage of the developed control method.

关键词： Consensus control directed topology external disturbance multi-agent(MA)systems

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Integration of ANN for Accurate Estimation and control in Wastewater Treatment 28

Integration of ANN for Accurate Estimation and Control in Wa...

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28th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2023

作者： Ţiru, Andreea Elena Vasiliev, Iulian Diaconu, Larisa Vilanova, Ramon Voipan, Daniel Ratnaweera, Harsha Dunǎrea de Jos University of Galaţi Department of Automatic Control and Electrical Engineering Galaţi Romania Autonomous University of Barcelona Department of Automation Systems and Advanced Control Research Barcelona Spain Dunǎrea de Jos University of Galaţi Department of Computer Science and Information Technology Galaţi Romania Ås Norway

ISBN: (纸本)9798350339918

The management of wastewater is a significant global concern that calls for innovative solutions to lessen its negative effects on the environment. Conventional techniques of treating wastewater need improvement in order to deal with newly discovered contaminants, which highlights the importance of providing precise estimates of process performance and resource requirements. The worsening water shortage situation requires a paradigm shift in which wastewater is viewed as a useful resource. It is possible to create an economy that is both sustainable and circular by treating and recycling wastewater, putting less pressure on freshwater supplies, and leaving as little of an environmental footprint as possible. This study investigates the use of Artificial Neural Networks (ANNs) as software estimators in the treatment of wastewater, with a particular emphasis on predicting ammonium concentrations in effluent. In order to deal with imbalanced time-series data, the research introduces innovative data pretreatment strategies. These techniques include a Sliding Window protocol, Data Normalization, and a K-Fold training scheme. This illustrates the potential of ANNs to revolutionize wastewater treatment procedures and drive developments in this field. The suggested method demonstrates higher performance when estimating pollutant concentrations, showing the ability of ANNs to do so. © 2023 IEEE.

关键词： Neural networks

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On Convergence in Distribution of Stein's Unbiased Risk Hyper-parameter Estimator for Regularized System Identification 41

On Convergence in Distribution of Stein's Unbiased Risk Hype...

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第41届中国控制会议

作者： Yue Ju Tianshi Chen Biqiang Mu Lennart Ljung School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of Sciences Division of Automatic Control Department of Electrical EngineeringLink?ping University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Asymptotic theory for the regularized system identification has received increasing interests in recent *** this paper,for the finite impulse response(FIR) model and filtered white noise inputs,we show the convergence in distribution of the Stein's unbiased risk estimator(SURE) based hyper-parameter estimator and find factors that influence its convergence *** particular,we consider the ridge regression case to obtain closed-form expressions of the limit of the regression matrix and the variance of the limiting distribution of the SURE based hyper-parameter estimator,and then demonstrate their relation numerically.

关键词： Asymptotic theory Stein's unbiased risk estimator Hyper-parameter estimator Regularized system identification

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Multi-Objective Particle Swarm Optimisation for Pareto Optimal Tuning of Super-Twisting controller in Quadcopter 4

Multi-Objective Particle Swarm Optimisation for Pareto Optim...

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4th International Conference on Innovative Research in Applied Science, engineering and Technology, IRASET 2024

作者： Vera, Octavio Gomez, Victor Rodas, Jorge Kali, Yassine Saad, Maarouf Comparatore, Leonardo Universidad Nacional De Asunción Lab. Of Power And Control Systems Facultad De Ingeniería Luque Paraguay School Of Engineering Université Du Québec En Abitibi-Témiscamingue Rouyn-Noranda Canada Grepci Laboratory École De Technologie Supérieure Department Of Electrical Engineering Montreal Canada

ISBN: (纸本)9798350309508

This work introduces the Multi-Objective Particle Swarm Optimisation (MOPSO) algorithm to optimise and speed up adjusting gains of a modified super-twisting second-order sliding-mode (MSTSOSM) attitude controller designed for a quadcopter. The tuning process is executed in MATLAB/Simulink, utilising a non-linear model that incorporates the physical characteristics of the quadcopter. The optimised parameters correspond to the MSTSOSM gains associated with each attitude state. The MSTSOSM constructs vectors using the gains of each Euler angle, employing particle coordinates computed by the MOPSO algorithm. These coordinates dynamically evolve during the algorithm's execution, exploring the parameter space for optimal positions. Consequently, the Pareto front emerges, showcasing Pareto's optimal solutions. The optimisation methodology is grounded in Pareto dominance theory, evaluating performance indicators such as rise time, root-mean-square error, and overshoot across all attitude axes in step responses. This systematic approach transcends traditional trial-and-error methods, comprehensively exploring the parameter space. Simulation and experimental results affirm the efficacy of this tuning process, demonstrating its capacity to enhance quadcopter control with precision and efficiency. © 2024 IEEE.

关键词： Sliding mode control

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Efficient photoelectrochemical conversion of CO_(2)to syngas by photocathode engineering

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Green Energy & Environment 2022年第3期7卷 545-553页

作者： Sheng Chu Pengfei Ou Roksana Tonny Rashid Yuyang Pan Daolun Liang Huiyan Zhang Jun Song Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China Department of Electrical and Computer Engineering McGill UniversityMontrealQC H3A 0E9Canada Department of Mining and Materials Engineering McGill UniversityMontrealQC H3A 0C5Canada

The synthesis of renewable chemical fuels from CO_(2) and H_(2)O via photoelectrochemical(PEC)route reprensents a promising room-temperature approach for transforming greenhouse gas into value-added chemicals(e.g.,syngas),but to date it has been hampered by the lack of efficient photocathode for CO_(2) ***,we report efficient PEC CO_(2) reduction into syngas by photocathode *** photocathode is consisting of a planar p-n Si junction for strong light harvesting,GaN nanowires for efficient electron extraction and transfer,and Au/TiO_(2)for rapid electrocatalytic syngas *** photocathode yields a record-high solar energy conversion efficiency of 2.3%.Furthermore,desirable syngas compositions with CO/H_(2)ratios such as 1:2 and 1:1 can be produced by simply varying the size of Au *** calculations reveal that the active sites for CO and H_(2)generation are the facet and undercoordinated sites of Au particles,respectively.

关键词： syngas photocathode photoelectrochemical

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Communication Network Layer State Estimation Measurement Model for a Cyber-Secure Smart Grid

Communication Network Layer State Estimation Measurement Mod...

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2024 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2024

作者： Mathieu, Reynold Boamah, Sharon Cooper, Austin Agnew, Dennis McNair, Janise Bretas, Arturo University of Florida Department of Electrical and Computer Engineering GainesvilleFL United States Distributed Systems Group Pacific Northwest National Laboratory RichlandWA United States G2Elab Grenoble INP CNRS Universite Grenoble Alpes Grenoble38000 France

ISBN: (纸本)9798350313604

Network communication has been proven to be a very important tool and a key factor in the recent development and progress of the power grid operation. It is also considered as the foundation for the smart grid because information and communication are integrated into electricity distribution to achieve reliable and accurate knowledge of the power grid. In previous years, absorbing energy from substations and delivering it to customers was the only type of interaction we knew between utility companies and customers. Presently, the growing connections of small distributed generation units caused by the cost reduction of most of the technologies used in the generation and storage of electrical energy, along with the potential benefits of renewable energy have pushed many researchers to look into the improvement of information and communication technologies (ICT) in order to ensure a bidirectional flow of power and data. Moreover, the evolution of information and communication technologies and its applications to smart grid have converted the smart grid into a cyber-physical system where vulnerabilities and additional security challenges such as cyber-threats and cyber-attacks have emerged. Previously, we have demonstrated that using machine learning-based processing on data gathered from communication networks and the power grid was a promising solution for detecting cyber threats by implementing a co-simulation of cyber-security for cross-layer strategy. Since the majority of the challenges observed can only be solved in the network communication layer, we present in this work a physics-based state estimation model of the communication network system towards enhanced cyber-physical security of the smart grid. Information integration with the previously developed machine learning model is developed, providing an enhanced cyber-physical security application for the smart grid. Easy-to-implement model, without hard-to-derive parameters, highlights potential aspects of th

关键词： Smart power grids

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