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Robust Beamforming Design and Antenna Selection for Dynamic HRIS-aided MISO systems

IEEE Transactions on Vehicular Technology 2025年

作者： Wang, Jintao Zhou, Binggui Ma, Chengzhi Gong, Shiqi Yang, Guanghua Ma, Shaodan University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering Macau999078 China Beijing Institute of Technology School of Information and Electronics Beijing100081 China Jinan University School of Intelligent Systems Science and Engineering Zhuhai519070 China

In this paper, we propose a dynamic hybrid active-passive reconfigurable intelligent surface (HRIS) to enhance multiple-input-single-output (MISO) communications, leveraging the property of dynamically placing active elements. Specifically, considering the impact of hardware impairments (HWIs), we investigate channel-aware configurations of the receive antennas at the base station (BS) and the active/passive elements at the HRIS to improve transmission reliability. To this end, we propose a penalty-based exact block coordinate descent (PEBCD) algorithm to address the mean-square-error (MSE) minimization problem for the dynamic HRIS-aided MISO system by jointly optimizing the BS receive antenna selection matrix, the reflection phase coefficients, the reflection amplitude matrix, and the mode selection matrix of the HRIS. Numerical simulations demonstrate the significant superiority of our proposed scheme over conventional benchmark schemes. © 1967-2012 IEEE.

关键词： Rectennas

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Learning Provably Stable Local Volt/Var Controllers for Efficient Network Operation

arXiv

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arXiv 2022年

作者： Yuan, Zhenyi Cavraro, Guido Singh, Manish K. Cortés, Jorge The Department of Mechanical and Aerospace Engineering UC San Diego United States The Power Systems Engineering Center National Renewable Energy Laboratory United States The Department of Electrical and Computer Engineering University of Minnesota United States

This paper develops a data-driven framework to synthesize local Volt/Var control strategies for distributed energy resources (DERs) in power distribution grids (DGs). Aiming to improve DG operational efficiency, as quantified by a generic optimal reactive power flow (ORPF) problem, we propose a two-stage approach. The first stage involves learning the manifold of optimal operating points determined by an ORPF instance. To synthesize local Volt/Var controllers, the learning task is partitioned into learning local surrogates (one per DER) of the optimal manifold with voltage input and reactive power output. Since these surrogates characterize efficient DG operating points, in the second stage, we develop local control schemes that steer the DG to these operating points. We identify the conditions on the surrogates and control parameters to ensure that the locally acting controllers collectively converge, in a global asymptotic sense, to a DG operating point agreeing with the local surrogates. We use neural networks to model the surrogates and enforce the identified conditions in the training phase. AC power flow simulations on the IEEE 37-bus network empirically bolster the theoretical stability guarantees obtained under linearized power flow assumptions. The tests further highlight the optimality improvement compared to prevalent benchmark methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Electric load flow

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Multi-Vehicle Cooperative Persistent Coverage for Random Target Search

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IEEE Robotics and Automation Letters 2025年第7期10卷 6680-6687页

作者： Li, Zhuo Li, Guangzheng Sadeghi, Alireza Sun, Jian Wang, Gang Wang, Jialin Beijing Institute of Technology National Key Lab of Autonomous Intelligent Unmanned Systems School of Automation Beijing100084 China Chongqing Innovation Center Beijing Institute of Technology Chongqing401120 China University of Minnesota Department of Electrical and Computer Engineering MinneapolisMN55455 United States Intelligent Game and Decision Laboratory China Academy of Launch Vehicle Technology Beijing100071 China

This letter investigates the target search problem for a network of autonomous vehicles, aiming to maximize the detection of randomly appearing targets within a given area. Considering no prior knowledge of the targets is available, we propose a multi-vehicle cooperative persistent coverage scheme under the framework of multi-agent reinforcement learning, in contrast to heuristic and model-based optimization methods in existing works. We model the persistent coverage problem as a partially observable Markov decision process (POMDP) due to the vehicles' limited observation ranges, and introduce a knowability map to characterize their knowledge of the target area. Each vehicle employs a distributed estimator, leveraging its own observations and shared information from neighboring vehicles, to construct a globally estimated knowability map - thereby mitigating partial observability. The persistent coverage policies are learned with the architecture of centralized training and distributed execution, enabling cooperative and efficient target search by fully exploiting shared information. Moreover, we propose an adaptive partition method for the target area to ensure a fixed dimension of the state space in the POMDP, which can improve scalability of the learned policy to target areas with various sizes. Simulations validate effectiveness and scalability of the proposed cooperative scheme. © 2025 IEEE.

关键词： Reinforcement learning

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Federated Optimization of Smooth Loss Functions

arXiv

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arXiv 2022年

作者： Jadbabaie, Ali Makur, Anuran Shah, Devavrat The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Computer Science The Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States

In this work, we study empirical risk minimization (ERM) within a federated learning framework, where a central server seeks to minimize an ERM objective function using n samples of training data that is stored across m clients and the server. The recent flurry of research in this area has identified the Federated Averaging (FedAve) algorithm as the staple for determining ϵ-approximate solutions to the ERM problem. Similar to standard optimization algorithms, e.g., stochastic gradient descent, the convergence analysis of FedAve and its variants only relies on smoothness of the loss function in the optimization parameter. However, loss functions are often very smooth in the training data too. To exploit this additional smoothness in data in a federated learning context, we propose the Federated Low Rank Gradient Descent (FedLRGD) algorithm. Since smoothness in data induces an approximate low rank structure on the gradient of the loss function, our algorithm first performs a few rounds of communication between the server and clients to learn weights that the server can use to approximate clients' gradients using its own gradients. Then, our algorithm solves the ERM problem at the server using an inexact gradient descent method. To theoretically demonstrate that FedLRGD can have superior performance to FedAve, we present a notion of federated oracle complexity as a counterpart to canonical oracle complexity in the optimization literature. Under some assumptions on the loss function, e.g., strong convexity and smoothness in the parameter, η-Hölder class smoothness in the data, etc., we prove that the federated oracle complexity of FedLRGD scales like (Equation presented) and that of FedAve scales like (Equation presented) (neglecting typically sub-dominant factors), where 1 is the ratio of client-to-server communication time to gradient computation time, p is the parameter dimension, and d is the data dimension. Then, we show that when d is small compared to n and the l

关键词： Optimization

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Triple Point Masking

arXiv

引用

arXiv 2024年

作者： Liu, Jiaming Kong, Linghe Wu, Yue Gong, Maoguo Li, Hao Miao, Qiguang Ma, Wenping Qin, Can School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China School of Computer Science and Technology Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xidian University Xi’an710071 China School of Electronic Engineering Key Laboratory of Collaborative Intelligence Systems Ministry of Education Xidian University Xi’an710071 China College of Mathematics Science Inner Mongolia Normal University Hohhot010022 China School of Artificial Intelligence Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi’an710071 China Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States

Existing 3D mask learning methods encounter performance bottlenecks under limited data, and our objective is to overcome this limitation. In this paper, we introduce a triple point masking scheme, named TPM, which serves as a scalable plug- and-play framework for MAE pre-training to achieve multi-mask learning for 3D point clouds. Specifically, we augment the baseline methods with two additional mask choices (i.e., medium mask and low mask) as our core insight is that the recovery process of an object can manifest in diverse ways. Previous high-masking schemes focus on capturing the global representation information but lack fine-grained recovery capabilities, so that the generated pre-training weights tend to play a limited role in the fine-tuning process. With the support of the proposed TPM, current methods can exhibit more flexible and accurate completion capabilities, enabling the potential autoencoder in the pre-training stage to consider multiple representations of a single 3D point cloud object. In addition, during the fine-tuning stage, an SVM-guided weight selection module is proposed to fill the encoder parameters for downstream networks with the optimal weight, maximizing linear accuracy and facilitating the acquisition of intricate representations for new objects. Extensive experimental results and theoretical analysis show that five baselines equipped with the proposed TPM achieve comprehensive performance improvements on various downstream tasks. Our code and models are available at https://***/liujia99/TPM. © 2024, CC BY.

关键词： Signal encoding

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Recent Advancements in Vehicle to Vehicle Charging

Recent Advancements in Vehicle to Vehicle Charging

引用

International Conference on Power Electronics and Drive systems (PEDS)

作者： Anindita Golder Kushan Tharuka Lulbadda Tarlochan Sidhu Sheldon S. Williamson Department of Electrical and Computer Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Ontario Tech University Oshawa ON Canada

More and more electric vehicles and charging stations are penetrating into the power system today which introduce new challenges. As a result, the concept of vehicle to vehicle charging (V2V) is gaining interest. Therefore, it is important to understand the concept of V2V charging. In this paper, some of the recent developments in the area of vehicle to vehicle (V2V) charging are explored.

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Design Considerations for Electric Traction Power systems

Design Considerations for Electric Traction Power Systems

引用

IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Anindita Golder Jigyesh Sharma Kushan Tharuka Tarlochan Sidhu Sheldon S. Williamson Department of Electrical and Computer Engineering Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Smart Transportation Electrification and Energy Research (STEER) Group Ontario Tech University Oshawa ON Canada

There is growing interest in e-mobility which is not only limited to electric vehicles but also mass transit systems, heavy duty vehicles, off-road vehicles and so on. With the intense focus on sustainability and achieving net zero emissions, most transit systems will be electrified. The impact of mass transit electrification on the existing power system needs a thorough and detailed analysis. Also, the upgrade from fuel powered transit systems to electric transit systems needs to be done with minimal changes to the existing power network and maximum utilization of available resources in the transit system. Therefore, the study of electric transit systems, its impact on the power system and challenges that can arise from electrifying railways are presented in this paper.

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First demonstration of a fiber optic bolometer on a tokamak plasma (invited)

First demonstration of a fiber optic bolometer on a tokamak ...

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作者： Lee, S. Shafer, M. Reinke, M. Uddin, N. Sheng, Q. Han, M. Donovan, D. O'Neill, R. Department of Nuclear Engineering University of Tennessee KnoxvilleTN37996 United States Oak Ridge National Laboratory Oak RidgeTN37831 United States Commonwealth Fusion Systems CambridgeMA02139 United States Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States General Atomics San DiegoCA92121-1122 United States

A fiber optic bolometer (FOB) was demonstrated observing a fusion plasma for the first time at the DIII-D tokamak. A FOB uses a fiber optics-based interferometric technique that is designed to have a high sensitivity to temperature changes [75 mK/(W/m2) responsivity in high vacuum with 0.38 mK noise level] with a negligible susceptibility to electromagnetic interference (EMI) that can be problematic for resistive bolometers in a tokamak environment. A single-channel test apparatus was installed on DIII-D consisting of a measurement FOB and shielded reference FOB. The single-channel FOB showed a negligible increase in the noise level during typical plasma operations (0.39 mK) compared to the benchtop results (0.38 mK), confirming an insignificant EMI impact to the FOB. Comparisons to DIII-D resistive bolometers showed good agreement with the single-channel FOB, indicating that the FOB is comparable to a resistive bolometer when the impulse calibration is applied. The noise-equivalent power density of the calibrated FOB during a plasma operation was 0.55 W/m2 with an average sampling time of 20 ms. The major potential effect of ionizing radiation on the FOB would be the radiation-induced attenuation, which can be efficiently compensated for by adjusting the probing light power. © 2022 Author(s).

关键词： Interferometry

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Comparison of two newly suggested power, refrigeration, and hydrogen production, for moving towards sustainability schemes using improved solar-powered evolutionary algorithm optimization

引用

Chemosphere 2023年第1期336卷 139160页

作者： Hai, Tao Abd El-Salam, Nasser M. Kh, Teeba Ismail Chaturvedi, Rishabh El-Shafai, Walid Farhang, Babak School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun558000 China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Province Guizhou Duyun558000 China Universiti Teknologi MARA Selangor Shah Alam40450 Malaysia Natural Science Department Community College King Saud University Riyadh12642 Saudi Arabia Department of Computer Engineering College of Engineering and Computer Science Lebanese French University Kurdistan Region Iraq Department of Mechanical Engineering Institute of Engineering & Technology GLA University UP Mathura281001 India Department Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Energy Technology Aalborg University Denmark

In the third millennium, developing countries will confront significant environmental problems such as ozone depletion, global warming, the shortage of fossil resources, and greenhouse gas emissions. This research looked at a multigenerational system that can generate clean hydrogen, fresh water, electricity, heat, and cooling. The system's components include Rankine and Brayton cycles, an Organic Rankine Cycle (ORC), flash desalination, an Alkaline electrolyzer, and a solar heliostat. The proposed process has been compared for two different start-up modes with a combustion chamber and solar heliostat to compare renewable and fossil fuel sources. This research evaluated various characteristics, including turbine pressure, system efficiency, solar radiation, and isentropic efficiency. The energy and exergy efficiency of the proposed system were obtained at around 78.93% and 47.56%, respectively. Exergy study revealed that heat exchangers and alkaline electrolyzers had the greatest exergy destruction rates, at 78.93% and 47.56%, respectively. The suggested system produces 0.04663 kg/s of hydrogen. Results indicate that at the best operational conditions, the exergetic efficiency, power, and hydrogen generation of 56%, 6000 kW, and 1.28 kg/s is reached, respectively. Also, With a 15% improvement in the Brayton cycle's isentropic efficacy, the quantity of hydrogen produced increases from 0.040 kg/s to 0.0520 kg/s. © 2023 Elsevier Ltd

关键词： Solar energy

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Autonomous nanorobots with powerful thrust under dry solid-contact conditions by photothermal shock

Research Square

引用

Research Square 2023年

作者： Gu, Zhaoqi Zhu, Runlin Shen, Tianci Dou, Lin Liu, Hongjiang Liu, Yifei Liu, Xu Liu, Jia Zhuang, Songlin Gu, Fuxing Laboratory of Integrated Opto-Mechanics and Electronics Shanghai Key Laboratory of Modern Optical System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Department of Industrial and Systems Engineering Auburn University AuburnAL36849 United States

Nanorobotic motion on solid substrates is greatly hindered by strong nanofriction, and powerful nanomotors‒the core components for nanorobotic motion‒are still lacking. Optical actuation addresses power and motion control issues simultaneously, while conventional technologies with small thrust usually apply to fluid environments. Here, we demonstrate micronewton-thrust nanomotors that enable the autonomous nanorobots working like conventional robots with precise motion control on dry surfaces by a photothermal-shock technique. We build a pulsed laser-based actuation and trapping platform, termed photothermal-shock tweezers, for general motion control of metallic nanomaterials and assembled nanorobots with nanoscale precision. The thrust-to-weight ratios up to 107 enable nanomotors output forces to interact with external micro/nano-objects. Leveraging machine vision and deep learning technologies, we assemble the nanomotors into autonomous nanorobots with complex structures, and demonstrate multi-degree-of-freedom motion and sophisticated functions. Our photothermal shock-actuation concept fundamentally addresses the nanotribology challenges and expands the nanorobotic horizon from fluids to dry solid surfaces. © 2023, CC BY.

关键词： Nanorobotics

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