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On-chip metamaterial-enabled high-order mode-division multiplexing

advanced Photonics 2023年第5期5卷 106-113页

作者： Yu He Xingfeng Li Yong Zhang Shaohua An Hongwei Wang Zhen Wang Haoshuo Chen Yetian Huang Hanzi Huang Nicolas KFontaine Roland Ryf Yuhan Du Lu Sun Xingchen Ji Xuhan Guo Yingxiong Song Qianwu Zhang Yikai Su Shanghai Jiao Tong University Department of Electronic EngineeringState Key Laboratory of Advanced Optical Communication Systems and NetworksShanghaiChina Nokia Bell Labs Murray HillNew JerseyUnited States Shanghai University Key Laboratory of Specialty Fiber Optics and Optical Access NetworksJoint International Research Laboratory of Specialty Fiber Optics and Advanced CommunicationShanghaiChina Shanghai Jiao Tong University School of Electronic Information and Electrical EngineeringJohn Hopcroft Center for Computer ScienceShanghaiChina

Mode-division multiplexing(MDM)technology enables high-bandwidth data transmission using orthogonal waveguide modes to construct parallel data ***,few demonstrations have been realized for generating and supporting high-order modes,mainly due to the intrinsic large material groupvelocity dispersion(GVD),which make it challenging to selectively couple different-order spatial *** show the feasibility of on-chip GVD engineering by introducing a gradient-index metamaterial structure,which enables a robust and fully scalable MDM *** demonstrate a record-high-order MDM device that supports TE_(0)–TE_(15)modes simultaneously.40-GBaud 16-ary quadrature amplitude modulation signals encoded on 16 mode channels contribute to a 2.162 Tbit∕s net data rate,which is the highest data rate ever reported for an on-chip single-wavelength *** method can effectively expand the number of channels provided by MDM technology and promote the emerging research fields with great demand for parallelism,such as high-capacity optical interconnects,high-dimensional quantum communications,and large-scale neural networks.

关键词： integrated photonics metamaterial mode-division multiplexing subwavelength grating

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Attitude Takeover Control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning

arXiv

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arXiv 2023年

作者： Liu, Yuhan Wang, Pengyu Lee, Chang-Hun Tóth, Roland The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands The Flight Dynamics and Control Laboratory Department of Aerospace Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of The Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

One major challenge for autonomous attitude takeover control for on-orbit servicing of spacecraft is that an accurate dynamic motion model of the combined vehicles is highly nonlinear, complex and often costly to identify online, which makes traditional model-based control impractical for this task. To address this issue, a recursive online sparse Gaussian Process (GP)-based learning strategy for attitude takeover control of noncooperative targets with maneuverability is proposed, where the unknown dynamics are online compensated based on the learnt GP model in a semi-feedforward manner. The method enables the continuous use of on-orbit data to successively improve the learnt model during online operation and has reduced computational load compared to standard GP regression. Next to the GP-based feedforward, a feedback controller is proposed that varies its gains based on the predicted model confidence, ensuring robustness of the overall scheme. Moreover, rigorous theoretical proofs of Lyapunov stability and boundedness guarantees of the proposed method-driven closed-loop system are provided in the probabilistic sense. A simulation study based on a high-fidelity simulator is used to show the effectiveness of the proposed strategy and demonstrate its high performance. © 2023, CC BY-NC-SA.

关键词： Maneuverability

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Onboard Rooftop Solar Charging for Green Transportation in tourism sector

Onboard Rooftop Solar Charging for Green Transportation in t...

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Renewable Energy and Hydrogen Technologies (GlobConHT), IEEE IAS Global Conference on

作者： Moumita Pramanik Hiranmay Samanta Sudipta Basu Pal Konika Das Bhattacharya Chandan Kumar Chanda Hiranmay Saha Department of Electrical Engineering(EE) Indian Institute of Engineering Science and Technology (IIEST) Shibpur Howrah India Green Energy and Sensor Systems(SAMGESS) School of Advanced Materials Indian Institute of Engineering Science and Technology(IIEST) Shibpur Howrah India Department of Computer Science Technology and Computer Science Information Technology Engineering University of Engineering and Management(UEM) Kolkata Kolkata India

The need for energy conservation and environmental protection have triggered the development and deployment of electric vehicles. Light electric vehicles and fossil fuel based light vehicles are popular means of transport for short distances in not only remote rural areas but also in places of tourist attractions. For Islands in the tropical belt like the Sunderbans in India and other pristine sea beaches in South East Asia where nature is luxuriantly present, green transportation is proposed in this work. The objective is to develop environment friendly transport for these natural havens and islands that have ample renewable resources especially in the form of solar power. In this work, a model of a light electric vehicle is developed that utilizes the solar energy during the daytime for charging its batteries. Battery charge controller inbuilt with boost based MPPT (Maximum Power Point Tracking) of solar irradiation have especially been designed to meet the requirements. The efficiency of the designed MPPT is studied. As accumulation of dust and sand reduces the solar module efficiency, an automated self-cleaning mechanism has also been designed that automatically cleans the solar panel regularly. The life cycle cost and the reduction in carbon emissions coupled with the Cost of Capital Investment and operating expenses of the developed model of green transportation far outweighs the similar values obtained from other modes of remote transportation.

关键词： Maximum power point trackers Renewable energy sources Radiation effects Costs Solar energy Fossil fuels Green transportation

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Directly wireless communication of human minds via non-invasive brain-computer-metasurface platform

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eLight 2022年第1期2卷 132-142页

作者： Qian Ma Wei Gao Qiang Xiao Lingsong Ding Tianyi Gao Yajun Zhou Xinxin Gao Tao Yan Che Liu Ze Gu Xianghong Kong Qammer HAbbasi Lianlin Li Cheng‑Wei Qiu Yuanqing Li Tie Jun Cui Institute of Electromagnetic Space Southeast UniversityNanjing 210096China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China State Key Laboratory of Millimeter Wave Southeast UniversityNanjing 210096China Center of Intelligent Metamaterials Pazhou Laboratory Guangzhou 510330China Research Center for Brain-Computer Interface Pazhou LabGuangzhou 510330China Department of Electrical and Computer Engineering National University of SingaporeSingaporeSingapore University of Glasgow James Watt School of EngineeringGlasgow G128QQUK State Key Laboratory of Advanced Optical Communication Systems and Networks Department of ElectronicsPeking UniversityBeijing 100871China

Brain-computer interfaces(BCIs),invasive or non-invasive,have projected unparalleled vision and promise for assisting patients in need to better their interaction with the *** by the BCI-based rehabilitation technologies for nerve-system impairments and amputation,we propose an electromagnetic brain-computer-metasurface(EBCM)paradigm,regulated by human’s cognition by brain signals directly and *** experimentally show that our EBCM platform can translate human’s mind from evoked potentials of P300-based electroencephalography to digital coding information in the electromagnetic domain non-invasively,which can be further processed and transported by an information metasurface in automated and wireless *** wireless communications of the human minds are performed between two EBCM operators with accurate text ***,several other proof-of-concept mind-control schemes are presented using the same EBCM platform,exhibiting flexibly-customized capabilities of information processing and synthesis like visual-beam scanning,wave modulations,and pattern encoding.

关键词： communication computer surface

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Spiking Neural Networks for LPI Radar Waveform Recognition with Neuromorphic Computing

Spiking Neural Networks for LPI Radar Waveform Recognition w...

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IEEE National Conference on Radar

作者： Alex Henderson Steven Harbour Chris Yakopcic Tarek Taha David Brown Justin Tieman Garrett Hall Dayton Engineering Advanced Projects Lab Southwest Research Institute Beavercreek OH Department of Electrical and Computer Engineering University of Dayton Dayton OH Advanced Electronic Warfare Department Southwest Research Institute Warner Robins GA RF Sensors and Systems Department Southwest Research Institute San Antonio TX

The ultra-wideband, frequency agile and high duty cycle features of Low Probability of Intercept (LPI) radar pose serious concerns for passive radar detection systems that must efficiently identify LPI radar modulation schemes with very low latency and high accuracy. For these tasks, conventional deep learning techniques have often been employed, though this comes at the cost of increased model complexity and high energy consumption when implemented in tactically relevant scenarios with significant channel deterioration and size, weight, and power (SWaP) constrained platforms. In this paper, we propose a neuromorphic approach based on energy-efficient and robust Spiking Neural Networks (SNNs). To demonstrate the effectiveness of our proposed approach, we perform a challenging LPI radar waveform recognition task with a Spiking Convolutional Neural Network (SCNN). Simulation results show that the SCNN achieves a 13-waveform recognition accuracy of 99.1% at OdB SNR with 1.51µJ of total energy per inference. It is found that our system outperforms non-spiking models with a reduction in model size and three orders of magnitude lower energy consumption. To the best of our knowledge, this work presents the first spike-based implementation of an LPI radar waveform recognition system. Moreover, this paper highlights the potential for extremely low SWaP neuromorphic hardware deployment to enable intelligent electronic support systems that demand high throughput efficiency and ultra-low power.

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Design and application of a one-stop mobile application sharing platform for steel enterprises

Design and application of a one-stop mobile application shar...

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第42届中国控制会议

作者： Xinzhe Chen Luefeng Chen Jie Hu Qingfeng Yang Min Wu Witold Pedrycz School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Department of Electrical and Computer Engineering University of Alberta

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance.

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Progress in artificial intelligence-based visual servoing of autonomous unmanned aerial vehicles (UAVs)

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International Journal of Thermofluids 2024年 21卷

作者： Al Radi, Muaz AlMallahi, Maryam Nooman Al-Sumaiti, Ameena Saad Semeraro, Concetta Abdelkareem, Mohammad Ali Olabi, Abdul Ghani Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Department of Mechanical and Aerospace Engineering United Arab Emirates University P.O. Box 15551 Al Ain City United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Department of Industrial and Management Engineering University of Sharjah PO Box 27272 Sharjah United Arab Emirates Chemical Engineering Department Minia University Elminia Egypt Advanced Power and Energy Center Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

Unmanned aerial vehicles (UAVs) have attracted massive attention in many engineering and practical applications in the last years for their characteristics and operation flexibility. For the UAV system, suitable control systems are required to operate appropriately and efficiently. An emerging control technique is visual servoing utilizing the onboard camera systems for inspecting the UAV's environment and autonomously controlling the UAV's operation. Artificial intelligence (AI) techniques are widely deployed in the visual servoing of autonomous UAV applications. Despite the increasing research in the field of AI-based visual control of UAV systems, comprehensive review articles that showcase the general trends and future directions in this field of research are limited. This work comprehensively examines the application and advancements of AI-enhanced visual servoing in autonomous UAV systems, covering critical control tasks and offering insights into future research directions for enhancing performance and applicability which is limited in the current literature. The paper first reviews the application of intelligent visual servoing systems for autonomously executing various UAV control tasks, including 3D UAV positioning, aerial and ground object following, obstacle avoidance, and autonomous landing. Second, the research progresses in applying AI techniques in the visual servoing of autonomous UAV systems are discussed and analyzed. Finally, future directions and critical research gaps for further improving the performance and applicability of intelligent visual servoing systems are included. © 2024

关键词： Fuzzy logic

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Computing Power in the Sky: Digital Twin-assisted Collaborative Computing with Multi-UAV Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Chao Han, Yu Zhang, Long Jia, Ziye Zhang, Hongliang Hong, Choong Seon Han, Zhu Hebei University of Engineering School of Information and Electrical Engineering Handan056038 China Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Jinan250014 China Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Southeast University National Mobile Communications Research Laboratory Jiangsu Nanjing211111 China Peking University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Beijing100871 China Kyung Hee University Department of Computer Science and Engineering Gyeonggi-do Yongin-si17104 Korea Republic of University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The collaboration of computing powers (CPs) among unmanned aerial vehicles (UAVs)-mounted edge servers is essential to handle data-intensive tasks of user equipments (UEs). This paper presents a multi-UAV computing power network (CPN) that orchestrates the CP resources of edge servers to cooperatively process tasks through collaborative computing. Due to the frequent interactions among edge servers and the increased complexities for large-scale task executions, we propose a digital twin (DT)-driven multi-UAV CPN framework, where the aerial DT network is created as a digital replica of the multi-UAV network to assist collaborative computing. A joint optimization problem of the service association, offloading power control, task partitions, CP allocation, and UAV trajectory design is formulated to minimize the long-term average delay of UEs. We use the Lyapunov technique to tackle the long-term energy constraint, forming a tractable optimization problem, which is modeled as a Markov decision process to balance the UAV's deficit queue stability and the UE's task completion delay. A hybrid soft actor-critic based deep reinforcement learning algorithm is developed to optimize the joint design by sampling the hybrid action from the Gumbel and Gaussian distributions. Simulation results verify that the multi-UAV CPN contributes to significant performance gains when supported by DTs. © 2025 IEEE.

关键词： Markov processes

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Robust Control of Feeding Speed in Coal Seam Drilling Process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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Chinese Automation Congress (CAC)

作者： Xiao Liu Luefeng Chen Chengda Lu Haipeng Fan Min Wu Witold Pedrycz School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Department of Computer Engineering Istinye University Istanbul Turkey

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust $H_{\infty}$ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller's effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction.

关键词： Drilling Robust control Friction Simulation Geology Velocity control Stability criteria Process control Coal Output feedback

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Non-Hermitian Band Structure of Photonic Temporal Crystals

Non-Hermitian Band Structure of Photonic Temporal Crystals

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Conference on Lasers and Electro-Optics (CLEO)

作者： Jagang Park Hyukjoon Cho Seojoo Lee Kyungmin Lee Kanghee Lee Hee Chul Park Jung-Wan Ryu Namkyoo Park Sanggeun Jeon Bumki Min Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Daejeon Republic of Korea Department of Physics Korea Advanced Institute of Science and Technology Daejeon Republic of Korea Center for Theoretical Physics of Complex Systems Institute of Basic Science Daejeon Republic of Korea Department of Electrical and Computer Engineering Seoul National University Seoul Republic of Korea School of Electrical Engineering Korea University Seoul Republic of Korea

We experimentally confirm the non-Hermitian band structures of a photonic temporal crystal in the microwave. These non-Hermitian band structures are shown to be two measurable distinct subsets of complex eigenfrequenc... 详细信息

ISBN: (纸本)9781957171258

关键词： Microwaves Optical properties Optical resonators Photonic crystals Split ring resonators Surfaces

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