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Heterogeneous multi-player imitation learning

Control Theory and Technology 2023年第3期21卷 281-291页

作者： Bosen Lian Wenqian Xue Frank L.Lewis Department of Electrical and Computer Engineering Auburn UniversityAuburnAL 36849USA State Key Laboratory of Synthetical Automation for Process Industries and International Joint Research Laboratory of Integrated Automation Northeastern UniversityShenyang 110819LiaoningChina UTA Research Institute University of Texas at Arlington(UTA)Fort WorthTX 76118USA

This paper studies imitation learning in nonlinear multi-player game systems with heterogeneous control input *** propose a model-free data-driven inverse reinforcement learning(RL)algorithm for a leaner to find the cost functions of a N-player Nash expert system given the expert's states and control *** allows us to address the imitation learning problem without prior knowledge of the expert's system *** achieve this,we provide a basic model-based algorithm that is built upon RL and inverse optimal *** serves as the foundation for our final model-free inverse RL algorithm which is implemented via neural network-based value function *** analysis and simulation examples verify the methods.

关键词： Imitation learning Inverse reinforcement learning Heterogeneous multi-player games Data-driven model-free control

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Prediction of Geopolymer Concrete Compressive Strength Using Convolutional Neural Networks

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computer Modeling in engineering & Sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja Sadula Golla Madhu Sandeep Kautish Abdulaziz S.Almazyad Guojiang Xiong Ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer Science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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Optimal Control of SOEC-Based Hydrogen Production Systems for Demand Response Using Deep Reinforcement Learning in Smart Grids

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IEEE Transactions on Energy Conversion 2025年第2期40卷 724-741页

作者： Zhang, Wei Peng, Jiangkai Luo, Yusheng Liu, Wenxin Westover, Tyler L. Casteel, Micah J. Operation Technology/ETAP IrvineCA92618 United States GoldenCO80401 United States Midcontinent Independent System Operator CarmelIN46032 United States Research Laboratory Department of Electrical and Computer Engineering BethlehemPA18015 United States Idaho National Laboratory Idaho FallsID83415 United States

Solid oxide electrolysis cell (SOEC) hydrogen production technology can range in size from small, appliance-size equipment to large-scale, central production facilities that can be tied directly to renewable or non-greenhouse-gas-emitting forms of electricity production, making it an ideal resource for demand response (DR). The SOEC hydrogen production system is a complex integrated system that encompasses fluid dynamics, electrical dynamics, and electrochemical and thermal dynamics, all of which involve non-linearity and non-convexity. Proper control of the SOEC hydrogen production system is crucial to enable its participation in the DR program. To overcome the difficulty of designing an explicit control law for such nonlinear systems with nonconvex optimization features in DR applications, deep reinforcement learning (DRL) is explored to achieve the optimal control of the SOEC system for DR participation. Specifically, a twin delayed deterministic policy gradient (TD3) control framework is applied to achieve optimal response performance during DR events by considering power tracking error and hydrogen production efficiency with a suitable reward function. Two case studies with grid connections for tracking different DR commands were investigated. The first case study involved operating conditions reaching the boundaries, while the second involved operating conditions within the boundaries. The results showed that the proposed DRL-based control for SOEC can track the DR signal in a timely manner while maintaining high energy efficiency. © 1986-2012 IEEE.

关键词： Deep reinforcement learning

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Hybrid Sub-Harmonic Synchronous Machines Using Series and Parallel Consequent Permanent Magnet

Hybrid Sub-Harmonic Synchronous Machines Using Series and Pa...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Sajjad Hossain Rafin, S.M. Ali, Qasim Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Dept. of Electrical and Computer Engineering MiamiFL United States Sukkur Iba University Department of Electrical Engineering Sukkur Pakistan

ISBN: (纸本)9798350316445

This paper presents novel sub-harmonic synchronous machines having series or parallel permanent magnet structures on rotors for better performance in terms of greater torque density. The stator of the machines has two sets of three-phase winding, where the additional winding is used to generate sub-harmonic magnetomotive force components for brushless operation. Similar to the stator, the rotor of them uses an additional winding to induce that sub-harmonic component. Rotor also uses a permanent magnet to improve machine performance in series or parallel hybrid structures having conventional or consequent pole permanent magnet structures. In this paper, 4 different rotors, 3 having hybrid excitation, are used and their performance is compared. To validate the performance, a 2D finite element analysis of 8 poles and 48 slots of sub-harmonic synchronous machines is carried out with different rotors. Finally, the wide-speed operation of the proposed machine is discussed. © 2023 IEEE.

关键词： brushless motors consequent pole parallel PM excitation series PM excitation sub-harmonic synchronous machine

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Geometric-Spectral Reconstruction Learning for Multi-Source Open-Set Classification With Hyperspectral and LiDAR Data

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1892-1895页

作者： Leyuan Fang Dingshun Zhu Jun Yue Bob Zhang Min He IEEE the College of Electrical and Information Engineering Hunan University the Peng Cheng Laboratory the Department of Geomatics Engineering Changsha University of Science and Technology the PAMI Research Group the Department of Computer and Information ScienceUniversity of Macao

Dear editor,This letter presents an open-set classification method of remote sensing images(RSIs)based on geometric-spectral reconstruction *** specifically,in order to improve the ability of RSI classification model to adapt to the open-set environment,an openset classification method based on geometric and spectral feature fusion is proposed.

关键词： editor letter Open

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Surge Protection of Residential EV Charging Stations Against Direct Lightning Strikes 37

Surge Protection of Residential EV Charging Stations Against...

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37th International Conference on Lightning Protection, ICLP 2024

作者： Gektidis, Konstantinos Hadjicostas, Alexandros Peppas, George D. Politis, Zafiris Tsovilis, Thomas High Voltage Laboratory School of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece School of Electrical and Computer Engineering Technical University of Crete Chania731 00 Greece Research & Development Department Raycap SA 14 Telou and Petroutsou Athens15124 Greece

ISBN: (纸本)9783800764174

A typical three-story building equipped with a residential electrical vehicle charging station is modelled within the ATP-EMTP environment. Fast-front overvoltages affecting each component of the modelled electrical installation, particularly the charger and the car, are calculated for direct negative lightning strikes to the air termination system of the installation. The assessment of the risk of failure involves examining the rated impulse withstand voltage levels of distribution boards, the residential EV charger, and the plugged car. This evaluation considers the impacts of lightning peak current and soil resistivity. A protection scheme involving the installation of surge protective devices is investigated so as to diminish the risk of failure to equipment and car. The energy absorption capability of surge protective devices is assessed and the necessity of dedicated surge protection for electric cars is discussed. © 2024 IEEE, © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Charging stations

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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

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Journal of Environmental Sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid Ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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Secrecy Throughput Enhancement with ANECE and Multi-Antenna Beamforming in Finite Blocklength

Secrecy Throughput Enhancement with ANECE and Multi-Antenna ...

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IEEE International Conference on Communications (ICC)

作者： Zabir, Ishmam Swami, Ananthram Hua, Yingbo Department of Electrical and Computer Engineering University of California Riverside CA USA DEVCOM Army Research Laboratory USA

ISBN: (数字)9781538683477

ISBN: (纸本)9781538683477

This paper presents a secure downlink communication system where a transmitter with multiple antennas sends information to multiple single antenna users under ultra reliable and low-latency communication (uRLLC) system requirement. To meet uRLLC requirement and provide secrecy against multi-antenna eavesdropper (Eve), transmitter adopts a special channel training scheme called anti-eavesdropping channel estimation (ANECE) as well as a standard transmit beamforming to send secret information in short blocklength regime. Using ANECE, two or more cooperative full-duplex radio devices obtain their receive channel state information (CSI) with respect to each other while preventing Eve from obtaining a consistent estimate of its receive CSI, which improves the secrecy of subsequent transmission of information between the devices. We derive an expression for the average secrecy throughput (AST) of ANECE assisted transmission. This easy-to-evaluate expression of approximated AST in terms of blocklength and various controllable parameters leads to useful insights to maximize AST under uRLLC requirement. Finally, numerical results are presented and discussed.

关键词： Finite blocklength physical layer security secrecy throughput full-duplex ultra-reliable low-latency communications

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Maritime Path Planning Using Heuristic Evaluation Functions for Weather Parameters

Maritime Path Planning Using Heuristic Evaluation Functions ...

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

作者： Bienkowski, Adam Pattipati, Krishna R. Sidoti, David University of Connecticut Department of Electrical and Computer Engineering StorrsCT United States Us Naval Research Laboratory MontereyCA United States

ISBN: (纸本)9798350337020

Planning ship routes that take into account meteorological and oceanographic conditions is a salient problem for both commercial and Naval applications. The A∗ algorithm is a very common method for finding the minimum cost path in a graph. Finding appropriate heuristics for a cost function is critical to the computational efficiency and memory requirements of the A∗ algorithm. We propose heuristic evaluation functions (HEFs) based on the minimum, mean, median, and mode of the cost function values over the reachable nodes given time constraints. Only the HEF based on the minimum is admissible, but we show that the other heuristics are able to find near-optimal solutions in substantially shorter times than the Dijkstra's algorithm, which does not use a heuristic. We evaluate these heuristics over many scenarios and show that overall the HEF based on the mean value performs the best. This HEF can be used in time-critical applications where an occasional loss of optimality is sacrificed for faster run time, such as real-time planning and control, or as part of a multi-objective shortest path algorithm for planning and execution. © 2023 IEEE.

关键词： A∗ heuristics meteorology oceanography Shortest path planning with time windows weather

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A decouple-decomposition noise analysis model for closed-loop mode-localized tilt sensors

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Microsystems & Nanoengineering 2023年第6期9卷 297-307页

作者： Kunfeng Wang XingYin Xiong Zheng Wang Liangbo Ma BoWen Wang WuHao Yang Xiaorui Bie ZhiTian Li XuDong Zou The State Key Laboratory of Transducer Technology Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina School of Electronic Electrical and Communication EngineeringUniversity of Chinese Academy of SciencesBeijingChina Ming Hsieh Department of Electrical and Computer Engineering University of Southern CaliforniaLos AngelesCAUSA Shangdong Key Laboratory of Low-altitude Airspace Surveillance Network Technology QiLu Aerospace Information Research InstituteJinanChina

The development of mode-localized sensors based on amplitude output metrics has attracted increasing attention in recent years due to the potential of such sensors for high sensitivity and ***-localization phenomena leverage the interaction between multiple coupled resonant modes to achieve enhanced performance,providing a promising solution to overcome the limitations of traditional sensing *** noise plays a key role in determining the resolution of mode-localized sensors,as the output metric is derived from the measured AR(amplitude ratio)within the weakly coupled resonator ***,the amplitude noise originating from the weakly coupled resonator's closed-loop circuit has not yet been fully *** paper presents a decouple-decomposition(DD)noise analysis model,which is applied to achieve high resolution in a mode-localized tilt sensor based on a weakly coupled resonator closed-loop *** DD noise model separates the weakly coupled resonators using the decoupling method considering the nonlinearity of the *** integrating the decoupled weakly coupled resonators,the model decomposes the weakly coupled resonator's closed-loop circuit into distinct paths for amplitude and phase noise *** DD noise model reveals noise effects at various circuit nodes and models the system noise in the closed-loop circuit of the weakly coupled ***/Simulink simulations verify the model's accuracy when compared to theoretical *** the optimal operating point,the mode-localized tilt sensor achieves an input-referred instability of 3.91×10^(-4°)and an input-referred AR of PSD of 2.01×10^(-4°)⁄√Hz using the closed-loop noise *** model is also applicable to other varieties of mode-localized sensors.

关键词： weakly couple overcome

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