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arXiv 2023年

作者： Mao, Weihao Lu, Yang Chi, Chong-Yung Ai, Bo Zhong, Zhangdui Ding, Zhiguo The School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China The Institute of Communications Engineering Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Department of Electrical and Electronic Engineering University of Manchester Manchester United Kingdom

This paper investigates the system model and the transmit beamforming design for the Cell-Free massive multi-input multi-output (MIMO) integrated sensing and communication (ISAC) system. The impact of the uncertainty of the target locations on the propagation of wireless signals is considered during both uplink and downlink phases, and especially, the main statistics of the MIMO channel estimation error are theoretically derived in the closed-form fashion. A fundamental performance metric, termed communication-sensing (C-S) region, is defined for the considered system via three cases, i.e., the sensing-only case, the communication-only case and the ISAC case. The transmit beamforming design problems for the three cases are respectively carried out through different reformulations, e.g., the Lagrangian dual transform and the quadratic fractional transform, and some combinations of the block coordinate descent method and the successive convex approximation method. Numerical results present a 3-dimensional C-S region with a dynamic number of access points to illustrate the trade-off between communication and radar sensing. The advantage for radar sensing of the Cell-Free massive MIMO system is also studied via a comparison with the traditional cellular system. Finally, the efficacy of the proposed beamforming scheme is validated in comparison with zero-forcing and maximum ratio transmission schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

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Concept, Principle, and Modeling of Driving Risk Entropy Based on Human-Vehicle-Road Coupling Model for Autonomous Vehicle

SSRN

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SSRN 2024年

作者： Gao, Hongbo Yang, Hanqing Zhu, Juping Su, Huiping Wang, Ning Xie, Liping Li, Keqiang Department of Automation University of Science and Technology of China Hefei230026 China Institute of Advanced Technology University of Science and Technology of China Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Chongqing College of Mobile Communication Chongqing400044 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing100084 China

Driving risk entropy, based on entropy law, is an innovative concept proposed for intelligent driving systems. The concept deals with the driving risks caused by the human-vehicle-road system from the driving information obtained;however, driving risks are difficult to assess due to many influencing factors and great uncertainty. The risk entropy model of vehicles is visualized by introducing the concept of basic isotropic risk elliptic line (BIREL). Further incorporating the concept of information entropy, risk entropy models for vehicle interaction and vulnerable participants are established, and the risk entropy model for roads is developed using raster coordinates. Ultimately, a three-dimensional driving risk entropy model is constructed based on the human-vehicle-road coupling model, with appropriate weights assigned to each parameter through the DDPG algorithm. Experimental results demonstrate the effectiveness of the driving risk entropy model. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Combined Extension and Torsion of Hydrogels with Chemo-Mechanical Coupling: Revealing Negative Poynting Effect

SSRN

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SSRN 2024年

作者： Zheng, Chengxiang Hu, Minghui Wu, Tao Pasquale, Ciarletta Li, Qian Deng, Zichen School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'An710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Xi'An710072 China MOX Department di Mathematica Polytechnic di Milano piazza Leonardo da Vinci 32 Milano20133 Italy China Electronic Product Reliability and Environmental Testing Research Institute China Guangdong Provincial Key Laboratory of Electronic Information Products Reliability Technology China

In this paper, combined extension and torsion of hydrogel subject to a chemo-mechanical coupled loading is described in the framework of continuum mechanics, where the free energy density consists of the elastic, mixing and chemical contributions. A simplified, closed-form and exactly analytical solution to the mechanical response is obtained, which accounts for the coupling effect of external loading, chemical potential and microstructural parameters, such as crosslinking degree, Flory parameter, etc. In particular, the effect of free swelling and microscopic diffusion on deformation of the hydrogel is discussed, reaching some fundamental conclusions. The classic negative Poynting effect is revealed that the cylinder tends to shorten on twisting, and an inhomogeneous deformation, induced by torsion, along the radial direction is demonstrated. Furthermore, the dynamic competition between external loading and solvent environment is revealed and investigated, where the direct connection between internal micro-physical parameters and macroscopic deformation is demonstrated. The theoretical results presented in this paper may provide predictions and guidance for the mechanical analysis and design of hydrogel cylinder subject to extension and torsion in a solvent. © 2024, The Authors. All rights reserved.

关键词： Torsional stress

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Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization

arXiv

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arXiv 2023年

作者： Du, Hongyang Zhang, Ruichen Liu, Yinqiu Wang, Jiacheng Lin, Yijing Li, Zonghang Niyato, Dusit Kang, Jiawen Xiong, Zehui Cui, Shuguang Ai, Bo Zhou, Haibo Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications China The School of Information and Communication Engineering University of Electronic Sciences and Technology of China Chengdu China The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Shenzhen China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China School of Electronic Science and Engineering Nanjing University Jiangsu Nanjing210093 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Generative Diffusion Models (GDMs) have emerged as a transformative force in the realm of Generative Artificial Intelligence (GenAI), demonstrating their versatility and efficacy across various applications. The ability to model complex data distributions and generate high-quality samples has made GDMs particularly effective in tasks such as image generation and reinforcement learning. Furthermore, their iterative nature, which involves a series of noise addition and denoising steps, is a powerful and unique approach to learning and generating data. This paper serves as a comprehensive tutorial on applying GDMs in network optimization tasks. We delve into the strengths of GDMs, emphasizing their wide applicability across various domains, such as vision, text, and audio generation. We detail how GDMs can be effectively harnessed to solve complex optimization problems inherent in networks. The paper first provides a basic background of GDMs and their applications in network optimization. This is followed by a series of case studies, showcasing the integration of GDMs with Deep Reinforcement Learning (DRL), incentive mechanism design, Semantic Communications (SemCom), Internet of Vehicles (IoV) networks, etc. These case studies underscore the practicality and efficacy of GDMs in real-world scenarios, offering insights into network design. We conclude with a discussion on potential future directions for GDM research and applications, providing major insights into how they can continue to shape the future of network optimization. © 2023, CC BY.

关键词： Reinforcement learning

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An Efficient Spatial-Temporal Trajectory Planner for Autonomous Vehicles in Unstructured Environments

arXiv

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arXiv 2022年

作者： Han, Zhichao Wu, Yuwei Li, Tong Zhang, Lu Pei, Liuao Xu, Long Li, Chengyang Ma, Changjia Xu, Chao Shen, Shaojie Gao, Fei State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

As a core part of autonomous driving systems, motion planning has received extensive attention from academia and industry. However, real-time trajectory planning capable of spatial-temporal joint optimization is challenged by nonholonomic dynamics, particularly in the presence of unstructured environments and dynamic obstacles. To bridge the gap, we propose a real-time trajectory optimization method that can generate a high-quality whole-body trajectory under arbitrary environmental constraints. By leveraging the differential flatness property of car-like robots, we simplify the trajectory representation and analytically formulate the planning problem while maintaining the feasibility of the nonholonomic dynamics. Moreover, we achieve efficient obstacle avoidance with a safe driving corridor for unmodelled obstacles and signed distance approximations for dynamic moving objects. We present comprehensive benchmarks with State-of-the-Art methods, demonstrating the significance of the proposed method in terms of efficiency and trajectory quality. Real-world experiments verify the practicality of our algorithm. We will release our codes for the research community.1 Copyright © 2022, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Optimizing Vaccine Allocation Strategies in Pandemic Outbreaks: An Optimal control Approach

arXiv

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arXiv 2021年

作者： Tonkens, Sander de Klaver, Paul Salazar, Mauro The Department of Mechanical and Aerospace Engineering University of California San Diego United States The Máxima Medisch Centrum Eindhoven Netherlands The Control Systems Technology section Department of Mechanical Engineering Eindhoven University of Technology Netherlands

Since early 2020, the world has been dealing with a raging pandemic outbreak: COVID-19. A year later, vaccines have become accessible, but in limited quantities, so that governments needed to devise a strategy to decide which part of the population to prioritize when assigning the available doses, and how to manage the interval between doses for multi-dose vaccines. In this paper, we present an optimization framework to address the dynamic double-dose vaccine allocation problem whereby the available vaccine doses must be administered to different age-groups to minimize specific societal objectives. In particular, we first identify an age-dependent Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model including an extension capturing partially and fully vaccinated people, whereby we account for age-dependent immunity and infectiousness levels together with disease severity. Second, we leverage our model to frame the dynamic age-dependent vaccine allocation problem for different societal objectives, such as the minimization of infections or fatalities, and solve it with nonlinear programming techniques. Finally, we carry out a numerical case study with real-world data from The Netherlands. Our results show how different societal objectives can significantly alter the optimal vaccine allocation strategy. For instance, we find that minimizing the overall number of infections results in delaying second doses, whilst to minimize fatalities it is important to fully vaccinate the elderly first. Copyright © 2021, The Authors. All rights reserved.

关键词： Vaccines

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Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Gri...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Junyi Zhai Xinliang Dai Yuning Jiang Ying Xue Veit Hagenmeyer Colin N. Jones Xiao-Ping Zhang College of New Energy China University of Petroleum (UPC) China Karlsruhe Institute of Technology (KIT) Institute for Automation and Applied Informatics Germany Automatic Control Laboratory École Polytechnique Fédérale de Lausanne (EPFL) Switzerland School of Electric Power Engineering South China University of Technology (SCUT) China Department of Electronic Electrical and Systems Engineering University of Birmingham (UBir) Birmingham United Kingdom

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses significant challenges in dealing with the resulting optimal power flow (OPF) problem. In this paper, a recently proposed nonconvex distributed optimization algorithm — Augmented Lagrangian based Alternating Direction Inexact Newton method (ALADIN), is tailored to solve the nonconvex AC/DC OPF problem for emerging voltage source converter (VSC) based multiterminal high voltage direct current (VSC-MTDC) meshed AC/DC hybrid systems. The proposed scheme decomposes this AC/DC hybrid OPF problem and handles it in a fully distributed way. Compared to the existing state-of-art Alternating Direction Method of Multipliers (ADMM), which is in general, not applicable for nonconvex problems, ALADIN has a theoretical convergence guarantee. Applying these two approaches to VSC-MTDC coupled with an IEEE benchmark AC power system illustrates that the tailored ALADIN outperforms ADMM in convergence speed and numerical robustness.

关键词：

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Crowdsourced GNSS Satellite SNR in Degraded Environments for Dependability Improvement 22

Crowdsourced GNSS Satellite SNR in Degraded Environments for...

引用

22nd International Conference on Electromagnetics in Advanced Applications, ICEAA 2021

作者： Sun, Hao Lu, Debiao Cai, Baigen Xiao, Yu Beijing Jiaotong Univ. Beijing Eng. Research Center of Emc and Gnss Technology for Rail Transport School of Electronic and Information Engineering Frontiers Science Center for Smart High-speed Railway System Beijing China Beijing Jiaotong University State Key Laboratory of Rail Traffic Control and Safety School of Electronic and Information Engineering Frontiers Science Center for Smart High-speed Railway System Beijing China Aalto University School of Electrical Engineering Department of Communications and Networking Espoo Finland

ISBN: (纸本)9781665413862

Global Navigation Satellite systems (GNSS) localization uses time of arrival (TOA) to measure the distance between satellite and rover antenna. The key for TOA technique is the signal propagation should be straight geometrically. However, when the train runs in harsh environments, the GNSS signal quality can be degraded due to obstacles. GNSS signals are usually blocked by buildings and other obstacles, resulting in reflection and reflection, which leads to multipath positioning errors of LOS and NLOS. In the case of LOS multipath error, the GNSS receiver tracks the direct and reflected / diffracted composite signal, and the reflected / diffracted signal affects the correlation function tracking loop of the direct signal in GNSS. In the case of NLOS multipath error, GNSS receiver directly tracks reflected or diffracted signal because there is no direct satellite signal. In both cases, the multipath signal will have a large noise error range which is reflected in the change of SNR. In the GNSS solution, various GNSS receivers are used to obtain the SNR of each satellite to achieve the fully coverage of the satellite signal reception quality. Thus with limited GNSS receiver observation results, of the crowdsourcing of NLOS signal inspection will deliver the observation results in a more convenient way. In the open environment scenario, the relationship between elevation angle and SNR can be fitted by a linear function. However, in GNSS signal reception degraded environments (urban canyon etc.), The SNR at the elevation angle of the occlusion boundary will be drastically reduced. This will give us the boundary of the occlusion range. Based on this principle, we can map the environmental characteristics of different sections of the railway. The railway environment can generally be divided into open scenario, road cutting scenario, half sky scenario, urban canyon scenario and tunnel scenario. 5 typical scenario all have distinct environmental characteristics. By matching

关键词： Satellites

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Performance analysis of multirate systems: A direct frequency-domain identification approach

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Mechanical systems and Signal Processing 2025年 235卷

作者： Max van Haren Lennart Blanken Tom Oomen Department of Mechanical Engineering Control Systems Technology Section Eindhoven University of Technology Groene Loper 5 Eindhoven 5612 AE The Netherlands Sioux Technologies Esp 130 Eindhoven 5633 AA The Netherlands Delft Center for Systems and Control Delft University of Technology Mekelweg 2 Delft 2628 CN The Netherlands

Frequency-domain performance analysis of intersample behavior in sampled-data and multirate systems is challenging due to the lack of a frequency-separation principle, and systematic identification techniques are lacking. The aim of this paper is to develop an efficient technique for identifying the full intersample performance in the frequency-domain for closed-loop multirate systems, in particular the Performance Frequency Gain (PFG). Through local modeling techniques, aliased frequency components are effectively disentangled when identifying the PFG, which is directly facilitated by frequency-lifting the multirate system to a multivariable time-invariant representation. The developed method accurately and directly identifies the PFG in a single identification experiment. Finally, the developed method is experimentally validated on a prototype motion system, showing accurate identification of frequency-domain representations for the multirate system, including the PFG.

关键词： System identification Sampled-data systems Multirate systems Frequency-domain models Time-invariant representations Local modeling

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Editorial: Characterization and application of magneto-sensitive soft materials

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Frontiers in Materials 2023年 10卷

作者： Zhang, Zhili Li, Decai Yu, Miao Niu, Xiaodong Li, Weihua Institute of Magnetic Fluids School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing China State Key Laboratory of Tribology Tsinghua University Beijing China Key Laboratory for Optoelectronic Technology and Systems Ministry of Education College of Optoelectronic Engineering Chongqing University Chongqing China Department of Mechanical Engineering College of Engineering Shantou University Shantou China School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong WollongongNSW Australia

Magnetic fluids are nanocolloids made up of nanometer-sized ferromagnetic particles dispersing in a carrier liquid (typically comprises three parts: base carrier liquid, surfactant, and ferromagnetic particles). Since the particles are easier to agglomerate, ferromagnetic particles are typically coated with surfactants to prevent agglomeration. Magnetic nanoparticles are uniformly disseminated in the carrier liquid with the assistance of surfactants, which play a crucial role in the magnetic fluid composition. Li et al. systematically studied the coating state and colloidal stability of oleic acid (OA) and 3-(N,N-Dimethylmyristylammonio) propanesulfonate (DP) coated magnetite nanoparticles in the polar and apolar carrier liquid. The total Gibbs interfacial energy was analyzed based on Van Oss-Chaudhry-Good and DLVO theory to describe the behaviors of coated particles in solvents. Zang et al. studied the effect of different fatty acids as surfactants on the rheological properties of magnetic fluids. The results showed that the mixed fatty acids showed greater viscosity growth and a greater slope of the viscosity growth curve than the magnetic fluids dispersed with a single acid. This indicates that the mixed fatty acids have more stable rheological properties. The viscousity-temperature performance of kerosene-base magnetic fluids at low temperatures can be improved by adjusting the ratio of mixed fatty acids. The most typical application of magnetic liquids is sealing, which has the outstanding advantages of zero leakage, long life and low resistance. Magnetic fluid seals as a class of non-contact sealing technology have been a research focus. In order to solve the problem of the pole shoes in the ferrofluid seal are easily damaged under the situation of the large radial beating of the main shaft. Liu et al. proposed a new structure of the ferrofluid seal that use a redial-changed ring magnet as the magnetic source. Considering that the ring magnets have problems o

关键词： magnetic fluids (MF) magnetorheological fluids (MRF) magneto-sensitive soft materials non-contact sealing torsional vibration damper intelligent material energy absorber

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