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Frequency response data based LPV controller synthesis applied to a control moment gyroscope

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arXiv 2021年

作者： Bloemers, Tom Tóth, Roland Oomen, Tom The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Control Systems Technology Department of Mechanical Engineering Eindhoven University of Technology The Systems and Control Laboratory Institute for Computer Science and Control Kende u. 13-17 BudapestH-1111 Hungary

Control of systems with operating condition-dependent dynamics, including control moment gyroscopes, often requires operating condition-dependent controllers to achieve high control performance. The aim of this paper is to develop a frequency response data-driven linear parameter-varying control design approach for single-input single-output systems, which allows improved performance for a control moment gyroscope. A stability theory using closed-loop frequency response function data is developed, which is subsequently used in a synthesis procedure that guarantees local stability and performance. Experimental results on a control moment gyroscope demonstrate the performance improvements. Copyright © 2021, The Authors. All rights reserved.

关键词： Controllers

1D quasi-bound states in the continuum with large operation bandwidth in theω~k space for nonlinear optical applications

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Photonics Research 2022年第7期10卷 1575-1581页

作者： KAILI SUN HUI JIANG DMITRY ABYKOV VIEN VAN URIEL LEVY YANGJIAN CAI ZHANGHUA HAN Shandong Provincial Key Laboratory of Optics and Photonic Devices Center of Light Manipulation and ApplicationsSchool of Physics and ElectronicsShandong Normal UniversityJinan 250358China Image Processing Systems Institute—Branch of the Federal Scientific Research Centre“Crystallography and Photonics”of Russian Academy of Sciences Samara 443001Russia Department of Electrical and Computer Engineering University of AlbertaEdmontonAlberta T6G 2V4Canada Department of Applied Physics and Center for Nanoscience and NanotechnologyThe Hebrew University of JerusalemJerusalemIsrael

The phenomenon of bound state in the continuum(BIC)with an infinite quality factor and lifetime has emerged in recent years in photonics as a new tool to manipulate light-matter ***,most of the investigated structures only support BIC resonances at very few discrete points in theω~k *** when the BIC is switched to a quasi-BIC(QBIC)resonance through perturbation,its frequency will still be located within a narrow spectral band close to that of the original BIC,restricting their applications in many fields where random or multiple input frequencies beyond the narrow band are *** this work,we demonstrate that a new set of QBIC resonances can be supported by using a special binary grating consisting of two alternatingly aligned ridge arrays with the same period and zero-approaching ridge width difference on a slab *** QBIC resonances are distributed continuously over a broad band along a line in theω~k space and can thus be considered as 1 D *** the Q factors generally affected by the ridge difference,it is now possible to arbitrarily choose any frequencies on the dispersion line to achieve significantly enhanced light-matter interactions,facilitating many applications where multiple input wavelengths are required;e.g.,sum or difference frequency generations in nonlinear optics.

关键词： quasi nonlinear narrow

Continuous-Time Digital Twin with Analogue Memristive Neural Ordinary Differential Equation Solver

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arXiv 2024年

作者： Chen, Hegan Yang, Jichang Chen, Jia Wang, Songqi Wang, Shaocong Wang, Dingchen Tian, Xinyu Yu, Yifei Chen, Xi Lin, Yinan He, Yangu Wu, Xiaoshan Li, Yi Zhang, Xinyuan Lin, Ning Xu, Meng Li, Yi Zhang, Xumeng Wang, Zhongrui Wang, Han Shang, Dashan Liu, Qi Cheng, Kwang-Ting Liu, Ming Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong ACCESS – AI Chip Center for Emerging Smart Systems InnoHK Centers Hong Kong Science Park Hong Kong Institute of the Mind The University of Hong Kong Hong Kong Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China University of Chinese Academy of Sciences Beijing100049 China School of Integrated Circuits Hubei Key Laboratory for Advanced Memories Huazhong University of Science and Technology Wuhan430074 China State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai200433 China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

Digital twins, the cornerstone of Industry 4.0, replicate real-world entities through computer models, revolutionising fields such as manufacturing management and industrial automation. Recent advances in machine learning provide data-driven methods for developing digital twins using discrete-time data and finite-depth models on digital computers. However, this approach fails to capture the underlying continuous dynamics and struggles with modelling complex system behaviour. Additionally, the architecture of digital computers, with separate storage and processing units, necessitates frequent data transfers and Analogue-Digital (A/D) conversion, thereby significantly increasing both time and energy costs. Here, we introduce a memristive neural ordinary differential equation (ODE) solver for digital twins, which is capable of capturing continuous-time dynamics and facilitates the modelling of complex systems using an infinite-depth model. By integrating storage and computation within analogue memristor arrays, we circumvent the von Neumann bottleneck, thus enhancing both speed and energy efficiency. We experimentally validate our approach by developing a digital twin of the HP memristor, which accurately extrapolates its nonlinear dynamics, achieving a 4.2-fold projected speedup and a 41.4-fold projected decrease in energy consumption compared to state-of-the-art digital hardware, while maintaining an acceptable error margin. Additionally, we demonstrate scalability through experimentally grounded simulations of Lorenz96 dynamics, exhibiting projected performance improvements of 12.6-fold in speed and 189.7-fold in energy efficiency relative to traditional digital approaches. By harnessing the capabilities of fully analogue computing, our breakthrough accelerates the development of digital twins, offering an efficient and rapid solution to meet the demands of Industry 4.0. © 2024, CC BY-NC-SA.

关键词： Energy utilization

A Zeroth-Order Momentum Method for Risk-Averse Online Convex Games

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A Zeroth-Order Momentum Method for Risk-Averse Online Convex...

IEEE Conference on Decision and Control

作者： Zifan Wang Yi Shen Zachary I. Bell Scott Nivison Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA Air Force Research Laboratory Eglin AFB FL USA

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We consider risk-averse learning in repeated unknown games where the goal of the agents is to minimize their individual risk of incurring significantly high cost. Specifically, the agents use the conditional value at risk (CVaR) as a risk measure and rely on bandit feedback in the form of the cost values of the selected actions at every episode to estimate their CVaR values and update their actions. A major challenge in using bandit feedback to estimate CVaR is that the agents can only access their own cost values, which, however, depend on the actions of all agents. To address this challenge, we propose a new risk-averse learning algorithm with momentum that utilizes the full historical information on the cost values. We show that this algorithm achieves sub-linear regret and matches the best known algorithms in the literature. We provide numerical experiments for a Cournot game that show that our method outperforms existing methods.

关键词： Costs Estimation Games Numerical simulation Standards

Natural Language Processing for Smart Healthcare

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arXiv 2021年

作者： Zhou, Binggui Yang, Guanghua Shi, Zheng Ma, Shaodan The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China The State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China The State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau 999078 China

Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural language processing (NLP) plays a key role in smart healthcare due to its capability of analysing and understanding human language. In this work, we review existing studies that concern NLP for smart healthcare from the perspectives of technique and application. We first elaborate on different NLP approaches and the NLP pipeline for smart healthcare from the technical point of view. Then, in the context of smart healthcare applications employing NLP techniques, we introduce representative smart healthcare scenarios, including clinical practice, hospital management, personal care, public health, and drug development. We further discuss two specific medical issues, i.e., the coronavirus disease 2019 (COVID-19) pandemic and mental health, in which NLP-driven smart healthcare plays an important role. Finally, we discuss the limitations of current works and identify the directions for future works. Copyright © 2021, The Authors. All rights reserved.

关键词： Artificial intelligence

Virtual Gram staining of label-free bacteria using darkfield microscopy and deep learning

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arXiv 2024年

作者： Işıl, Çağatay Koydemir, Hatice Ceylan Eryilmaz, Merve de Haan, Kevin Pillar, Nir Mentesoglu, Koray Unal, Aras Firat Rivenson, Yair Chandrasekaran, Sukantha Garner, Omai B. Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Department of Biomedical Engineering Texas A&M University College StationTX77843 United States Center for Remote Health Technologies and Systems Texas A&M Engineering Experiment Station College StationTX77843 United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los AngelesCA90095 United States

Gram staining has been one of the most frequently used staining protocols in microbiology for over a century, utilized across various fields, including diagnostics, food safety, and environmental monitoring. Its manual procedures make it vulnerable to staining errors and artifacts due to, e.g., operator inexperience and chemical variations. Here, we introduce virtual Gram staining of label-free bacteria using a trained deep neural network that digitally transforms darkfield images of unstained bacteria into their Gram-stained equivalents matching brightfield image contrast. After a one-time training effort, the virtual Gram staining model processes an axial stack of darkfield microscopy images of label-free bacteria (never seen before) to rapidly generate Gram staining, bypassing several chemical steps involved in the conventional staining process. We demonstrated the success of the virtual Gram staining workflow on label-free bacteria samples containing Escherichia coli and Listeria innocua by quantifying the staining accuracy of the virtual Gram staining model and comparing the chromatic and morphological features of the virtually stained bacteria against their chemically stained counterparts. This virtual bacteria staining framework effectively bypasses the traditional Gram staining protocol and its challenges, including stain standardization, operator errors, and sensitivity to chemical variations. Copyright © 2024, The Authors. All rights reserved.

关键词： Sensitivity analysis

Optics for terawatt-scale photovoltaics: review and perspectives

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Advances in Optics and Photonics 2025年第1期17卷 185-294页

作者： Jäger, Klaus Aeberhard, Urs Llado, Esther Alarcon Bläsi, Benedikt Burger, Sven Ehrler, Bruno Favre, Wilfried Fejfar, Antonín Gageot, Tristan Gordon, Ivan Helmers, Henning Höhn, Oliver Isabella, Olindo Jošt, Marko Ledinský, Martin Mandal, Jyotirmoy Manley, Phillip Muñoz, Delfina Omair, Zunaid Lizcano, Juan Camilo Ortiz Paetzold, Ulrich W. Raman, Aaswath P. Sai, Hitoshi Saive, Rebecca Schmid, Martina Yablonovitch, Eli Becker, Christiane Department Optics for Solar Energy Helmholtz-Zentrum Berlin für Materialien und Energie Kekuléstraße 5 Berlin12489 Germany Computational Nano Optics Zuse Institute Berlin Takustraße 7 Berlin14195 Germany Fluxim AG Katharina-Sulzer-Platz 2 Winterthur8400 Switzerland LMPV-Sustainable Energy Materials Department AMOLF Science Park 104 Amsterdam1098 XG Netherlands Fraunhofer Institute for Solar Energy Systems ISE Heidenhofstraße 2 Freiburg79100 Germany JCMwave GmbH Bolivarallee 22 Berlin14050 Germany Université Grenoble Alpes CEA LITEN Campus INES 50 avenue du Lac Léman Le Bourget-du-Lac73375 France FZU - Institute of Physics The Czech Academy of Sciences Na Slovance 1999/2 Prague 8182 00 Czech Republic IMEC/Energyville Thor Park 8320 Genk3600 Belgium Hasselt University Martelarenlaan 42 Hasselt3500 Belgium Photovoltaic Materials and Devices Laboratory Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands University of Freiburg Emmy-Noether-Str.2 Freiburg79110 Germany Faculty of Electrical Engineering University of Ljubljana Tržaška 25 Ljubljana1000 Slovenia Department of Civil and Environmental Engineering Princeton University E209A Engineering Quadrangle PrincetonNJ08544 United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Institute of Microstructure Technology Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Light Technology Institute Karlsruhe Institute of Technology Karlsruhe76131 Germany Department of Materials Science and Engineering University of California Los AngelesCA90095 United States Ibaraki Tsukuba305-8568 Japan MESA+ Institute for Nanotechnology Inorganic Materials Science University of Twente NB Enschede7522 Netherlands University of Duisburg-Essen Forsthausweg 2 Duisburg47057 Germany Faculty 1 School of Engineering – Energy and Information Hochschule für Technik und Wirtschaft Berlin

In this section, we described the various device architectures in production for crystalline-silicon PV as well as the various absorber materials being used and developed for thin-film PV. We also explained why multijunction PV technology is considered the future of PV technology. We identified four major technological challenges (Fig. 1) for future mass production and deployment of PV technology in order to achieve the goal of climate neutrality and indicated how optics could help resolve these challenges. The four main challenges (Fig. 1) are: • Sustainable production of PV systems;• Higher energy conversion efficiencies;• Higher energy output and operational lifetime;• Integration of PV systems in their environment. © 2025 Optica Publishing Group (formerly OSA). All rights reserved.

关键词： Energy conversion efficiency

Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communications

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arXiv 2023年

作者： Ma, Zhe Wu, Wen Gao, Feifei Shen, Xuemin The Institute for Artificial Intelligence Tsinghua University State Key Lab of Intelligent Technologies and Systems Beijing National Research Center for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China The Frontier Research Center Peng Cheng Laboratory Guangdong Shenzhen518055 China The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

In this paper, we investigate the joint device activity and data detection in massive machine-type communications (mMTC) with a one-phase non-coherent scheme, where data bits are embedded in the pilot sequences and the base station simultaneously detects active devices and their embedded data bits without explicit channel estimation. Due to the correlated sparsity pattern introduced by the noncoherent transmission scheme, the traditional approximate message passing (AMP) algorithm cannot achieve satisfactory performance. Therefore, we propose a deep learning (DL) modified AMP network (DL-mAMPnet) that enhances the detection performance by effectively exploiting the pilot activity correlation. The DL-mAMPnet is constructed by unfolding the AMP algorithm into a feedforward neural network, which combines the principled mathematical model of the AMP algorithm with the powerful learning capability, thereby benefiting from the advantages of both techniques. Trainable parameters are introduced in the DL-mAMPnet to approximate the correlated sparsity pattern and the large-scale fading coefficient. Moreover, a refinement module is designed to further advance the performance by utilizing the spatial feature caused by the correlated sparsity pattern. Simulation results demonstrate that the proposed DL-mAMPnet can significantly outperform traditional algorithms in terms of the symbol error rate performance. © 2023, CC BY-NC-SA.

关键词： Message passing

Physics-Based Model for Nonuniform Thermionic Electron Emission from Polycrystalline Cathodes

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Physical Review Applied 2022年第5期18卷 054010-054010页

作者： Dongzheng Chen Ryan Jacobs John Petillo Vasilios Vlahos Kevin L. Jensen Dane Morgan John Booske Department of Materials Science and Engineering University of Wisconsin-Madison 1509 University Ave Madison Wisconsin 53706 USA Leidos 700 Technology Park Dr. Billerica Massachusetts 01821 USA Viasat Space Systems 2040 E. Technology Circle Tempe Arizona 85284 USA Code 6362 MSTD Naval Research Laboratory Washington DC 20375 USA Department of Electrical and Computer Engineering University of Wisconsin-Madison 1415 Engineering Dr. Madison Wisconsin 53706 USA

A physics-based model that predicts the emitted current from thermionic cathodes is developed, which accurately spans from the temperature-limited (TL) to full-space-charge-limited (FSCL) regions. Experimental observations of thermionic electron emission demonstrate a smooth transition between TL and FSCL regions of the emitted-current-density-versus-temperature (J-T) (Miram) curve and the emitted-current-density-versus-voltage (J-V) curve. Knowledge of the temperature and shape of the TL-FSCL transition is important in evaluating the thermionic electron-emission performance of cathodes, including predicting the lifetime. However, there are no first-principles physics-based models that predict the smooth TL-FSCL transition region for real thermionic cathodes without applying a priori assumptions or empirical phenomenological equations that are physically difficult to justify. Previous work detailing the nonuniform thermionic emission found that the effects of three-dimensional space charge, patch fields (electrostatic potential nonuniformity on the cathode surface based on local work-function values), and Schottky barrier lowering can lead to a smooth TL-FSCL transition region from a model thermionic cathode surface with a checkerboard spatial distribution of work-function values. In this work, we construct a physics-based nonuniform emission model for commercial dispenser cathodes. This emission model is obtained by incorporating the cathode surface grain orientation via electron-backscatter diffraction and the facet-orientation-specific work-function values from density-functional-theory calculations. The model enables the construction of two-dimensional emitted-current-density maps of the cathode surface and corresponding J-T and J-V curves. The predicted emission curves show excellent agreement with experiment, not only in the TL and FSCL regions but, crucially, also in the TL-FSCL transition region. This model provides a method to predict the thermionic emissio

关键词： Surface & interfacial phenomena Thermal energy harvesting devices Thermionic emission Complex oxides Free-electron lasers Electron diffraction First-principles calculations Materials modeling