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IEEE Conference on Global Communications (GLOBECOM)

作者： Xi Zhang Qixuan Zhu Networking and Information Systems Laboratory Department of Electrical and Computer Engineering Texas A&M University College Station TX USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The massive ultra-reliable and low-latency communications (mURLLC) services are emerging as a new traffic type to support communications among massive numbers of mobile users (MUs) demanding the stringent delay and error-rate bounded quality-of-services (QoS) requirements in 6G. Correspondingly, the integrated sensing and communications (ISAC) technique can improve various QoS performances through spectrum/hardware sharing between target-sensing and data-communications. In addition, the massive multiple-input multiple-output (massive MIMO) and finite blocklength coding (FBC) have been also widely recognized as the powerful 6G techniques to efficiently support mURLLC. However, how to apply the ISAC technique to accurately sense and estimate the wireless channel state while transmitting the information from the base station to MUs to support mURLLC using massive MIMO and FBC has imposed many new difficulties not encountered before. To conquer these challenges, in this paper we propose the new ISAC performance metrics for statistical-QoS guaranteed mURLLC over 6G massive MIMO mobile networks using FBC. First, we establish system models for ISAC-based architectures. Second, we detect targeted MUs and estimate the channel state using the radar sensing echo. Third, we develop a new ISAC performance metric as a function of the data-communication rate and channel state estimation distortion. Finally, we use the numerical analyses to validate and evaluate our developed ISAC performances in supporting mURLLC-oriented QoS requirements.

关键词： 6G mobile communication Measurement Wireless sensor networks Wireless networks Channel estimation Quality of service Massive MIMO Integrated sensing and communication Distortion Testing

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Modelling the Effect of the DC Link Decoupling Capacitor of a Commutation Power Loop Using a Thevenin-Based Frequency Domain Approach

Modelling the Effect of the DC Link Decoupling Capacitor of ...

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Annual IEEE Conference on Applied Power Electronics Conference and Exposition (APEC)

作者： Ayooluwa Ajiboye Ayodhya Somiruwan Gamwari Rakesh Resalayyan Alireza Khaligh Department of Electrical and Computer Engineering Maryland Power Electronics Laboratory The Institute for Systems Research University of Maryland College Park USA

The high commutation speed of wide band-gap devices causes undesired voltage overshoots and oscillatory behavior observed across the drain-source port. The mitigation of these voltage overshoots and oscillations caused by the resonant interaction between the commutation loop parasitic inductance and the switch parasitic output capacitance requires additional design considerations. In this work, a Thevenin-based frequency domain approach for modelling the switch voltage overshoot and oscillations with respect to the commutation power loop is proposed. The switching transition and its associated slew rate is modelled using a clamped-ramp function. The two figures of merit used to quantify the effect of the circuit elements in the commutation power loop with respect to the resonant oscillations are the voltage overshoot and time to steady state. Using the clamped-ramp function and the two figures of merit, the effect of the parasitic inductance and the decoupling capacitor on the power loop is analyzed. The trends observed from the analyses are used to obtain recommendations regarding the sizing and placement of the decoupling capacitor in the power loop. The proposed Thevenin-based frequency domain model is experimentally validated by comparing the analytical results with both the LTspice simulations and the experimental waveforms for a SiC-based 400 V, 20 A double pulse test.

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Distributionally Robust Dispatch for Power System with Advanced Adiabatic Compressed Air Energy Storage Considering Frequency Security

SSRN

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SSRN 2024年

作者： Liu, Hanchen Chen, Laijun Cui, Sen Chen, Siyuan Mei, Shengwei State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China

In response to climate change and the need to decrease carbon emissions, the penetration of renewable energies into power grids is growing dramatically. However, the high intermittence and low inertia of renewable energy pose significant risks to frequency security. The advanced adiabatic compressed air energy storage (AA-CAES) is a promising solution to enhancing grid frequency security due to its flexible and high inertia properties. Therefore, based on distributionally robust optimization, this paper proposes a dispatch strategy with the participation of AA-CAES to enhance frequency security. Firstly, a dispatch-friendly model of AA-CAES is proposed and can reflect the impacts of the part-load features on the dis-/charging efficiencies and capacities. Subsequently, a frequency response model with AA-CAES is presented to establish frequency security constraints, ensuring compliance with minimum inertia and maximum frequency deviation requirements. Furthermore, to cope with the randomness of renewable energy, this proposed model is formulated as a distributionally robust optimization problem with a "min-max-min" structure. In the day-ahead stage, the optimal on/off schedules for generators and AA-CAES can be determined according to the worst probability distribution in the second stage for providing sufficient grid inertia. In the intra-day stage, the generation and AA-CAES can be adjusted to minimize the frequency deviation. Finally, numerical studies are tested on the modified IEEE-39 bus system. The simulation results demonstrate the validity and feasibility of the proposed strategy with AA-CAES in supporting grid frequency security. © 2024, The Authors. All rights reserved.

关键词： Wind power

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Integrated Sensing, Communications, and Powering for Statistical-QoS Provisioning Over 6G Massive-MIMO Mobile Networks Using FBC

Integrated Sensing, Communications, and Powering for Statist...

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IEEE International Conference on Communications (ICC)

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

To satisfy the stringent quality-of-service (QoS) requirements of 6G mobile wireless networks on both channel state estimations and information transmissions, the integrated sensing and communication (ISAC) has been an enabling technique to sense and communicate by sharing the same frequency band and hardware. Simultaneous wireless information and power transfer (SWIPT) has also emerged to simultaneously deliver information and energy to a receiver. However, how to integrate ISAC with SWIPT to support the 6G traffic has imposed many new challenges not encountered before. To conquer these difficulties, in this paper we propose an integrated sensing, communications, and powering (ISACP) scheme for supporting statistical-QoS provisioning over 6G wireless networks using massive multiple-input and multiple-output (massive MIMO) communications. First, we establish system models for our ISACP scheme and define the Cramér-Rao bound and channel estimation distortion under our proposed ISACP scheme. Second, we develop the performance metrics of Cramér-Rao bound and channel estimation distortion to derive the capacity-distortion function to jointly measure the performance of integrated sensing, communication, and powering. Third, we integrate the capacity-distortion function with the finite blocklength coding (FBC) through deriving the ISACP-based ϵ-effective capacity to support the statistical delay and error-rate bounded QoS provisioning in 6G. Fourth, we maximize the energy-efficiency by controlling the optimal wireless power transfer for our ISACP scheme. Finally, we use numerical analyses to validate and evaluate our proposed ISACP scheme.

关键词： 6G mobile communication Wireless sensor networks Wireless networks Channel estimation Quality of service Integrated sensing and communication Distortion

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Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces 38

Taming "data-hungry" reinforcement learning? Stability in co...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Duan, Yaqi Wainwright, Martin J. Department of Technology Operations and Statistics Stern School of Business New York University New YorkNY10012 United States Laboratory for Information and Decision Systems Statistics and Data Science Center Department of Electrical Engineering and Computer Science Department of Mathematics Massachusetts Institute of Technology CambridgeMA02139 United States

We introduce a novel framework for analyzing reinforcement learning (RL) in continuous state-action spaces, and use it to prove fast rates of convergence in both off-line and on-line settings. Our analysis highlights two key stability properties, relating to how changes in value functions and/or policies affect the Bellman operator and occupation measures. We argue that these properties are satisfied in many continuous state-action Markov decision processes. Our analysis also offers fresh perspectives on the roles of pessimism and optimism in off-line and on-line RL. © 2024 Neural information processing systems foundation. All rights reserved.

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Out-of-distribution Object Detection through Bayesian Uncertainty Estimation

Out-of-distribution Object Detection through Bayesian Uncert...

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International Conference on Information Fusion

作者： Tianhao Zhang Shenglin Wang Nidhal Bouaynaya Radu Calinescu Lyudmila Mihaylova Automatic Control and Systems Engineering The University of Sheffield UK Department of Electrical and Computer Engineering Rowan University USA Department of Computer Science University of York UK

The superior performance of object detectors is often established under the condition that the test samples are in the same distribution as the training data. However, in many practical applications, out-of-distribution (OOD) instances are inevitable and usually lead to uncertainty in the results. In this paper, we propose a novel, intuitive, and scalable probabilistic object detection method for OOD detection. Unlike other uncertainty-modeling methods that either require huge computational costs to infer the weight distributions or rely on model training through synthetic outlier data, our method is able to distinguish between in-distribution (ID) data and OOD data via weight parameter sampling from proposed Gaussian distributions based on pre-trained networks. We demonstrate that our Bayesian object detector can achieve satisfactory OOD identification performance by reducing the FPR95 score by up to 8.19% and increasing the AUROC score by up to 13.94% when trained on BDD100k and VOC datasets as the ID datasets and evaluated on COCO2017 dataset as the OOD dataset.

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Progress of Brain Network Studies on Anesthesia and Consciousness: Framework and Clinical Applications

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engineering 2023年第1期20卷 77-95页

作者： Jun Liu Kangli Dong Yi Sun Ioannis Kakkos Fan Huang Guozheng Wang Peng Qi Xing Chen Delin Zhang Anastasios Bezerianos Yu Sun Key Laboratory for Biomedical Engineering of Ministry of Education of China Zhejiang UniversityHangzhou 310007China Department of Neurology Sir Run Run Shaw HospitalSchool of MedicineZhejiang UniversityHangzhou 310020China School of Electrical and Computer Engineering National Technical University of AthensAthens 15780Greece Department of Control Science and Engineering College of Electronics and Information EngineeringTongji UniversityShanghai 200092China Department of Anesthesiology The First Affiliated HospitalSchool of MedicineZhejiang UniversityHangzhou 310003China The N1 Institute for Health Center for Life SciencesNational University of SingaporeSingapore 117456Singapore

Although the relationship between anesthesia and consciousness has been investigated for decades, our understanding of the underlying neural mechanisms of anesthesia and consciousness remains rudimentary, which limits the development of systems for anesthesia monitoring and consciousness evaluation. Moreover, the current practices for anesthesia monitoring are mainly based on methods that do not provide adequate information and may present obstacles to the precise application of anesthesia. Most recently, there has been a growing trend to utilize brain network analysis to reveal the mechanisms of anesthesia, with the aim of providing novel insights to promote practical application. This review summarizes recent research on brain network studies of anesthesia, and compares the underlying neural mechanisms of consciousness and anesthesia along with the neural signs and measures of the distinct aspects of neural activity. Using the theory of cortical fragmentation as a starting point, we introduce important methods and research involving connectivity and network analysis. We demonstrate that whole-brain multimodal network data can provide important supplementary clinical information. More importantly, this review posits that brain network methods, if simplified, will likely play an important role in improving the current clinical anesthesia monitoring systems.

关键词： Anesthesia Brain network Connectivity Graph theoretical analysis Clinical monitoring system

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Hierarchical Caching for Digital Twins Communications Over mURLLC-Based 6G Distributed-Computing Mobile Networks Using FBC

Hierarchical Caching for Digital Twins Communications Over m...

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International Conference on Distributed Computing systems Workshop

作者： Xi Zhang Qixuan Zhu Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

ISBN: (数字)9798350354713

ISBN: (纸本)9798350354720

The massive ultra-reliable and low-latency communications (mURLLC) services are emerging as a new traffic type to support massive numbers of mobile users (MUs) demanding the stringent delay and error-rate bounded quality-of-services (QoS) requirements over 6G. Among multiple 6G mURLLC services, digital twins (DT) has been widely envisioned as a major intelligent application to support efficient interactions between physical and virtual objects. Moreover, multi-tier caching, which is one of the key distributed computing techniques, stores the frequently-demanded data items at different wireless network tiers to efficiently reduce mURLLC streaming delay and data move. However, how to efficiently cache mURLLC-based DT data items at different caching tiers of wireless networks and how to statistically upper-bound both delay and error-rate for DT communications remain challenging problems. To overcome these difficulties, in this paper we propose a multi-tier caching mechanism to support DT communications over 6 G mobile networks. First, we propose the DT data adaptive collection scheme applying finite blocklength coding (FBC) to dynamically encode a physical object into its virtual representation according to the current network and wireless channel statuses. Second, we develop inter-tier and intra-tier collaborative caching mechanisms, where DT data items are selectively cached at different wireless network caching tiers according to their popularities including: router tier, massive-multiple-input-multiple-output (MIMO) basestation tier, and mobile device tier. Third, our proposed intertier collaborative caching mechanisms maximize the aggregate $\epsilon$ effective capacity across all three caching tiers, and our proposed intra-tier collaborative caching mechanisms minimize the sum of data transmission delay for all DT data items cached in each caching tier. Finally, we numerically validate and evaluate our developed multi-tier hierarchical caching schemes over 6G DTe

关键词： 6G mobile communication Wireless networks Aggregates Collaboration Distributed databases Quality of service Encoding

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The Fundamental Limitations of Learning Linear-Quadratic Regulators

The Fundamental Limitations of Learning Linear-Quadratic Reg...

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IEEE Conference on Decision and control

作者： Bruce D. Lee Ingvar Ziemann Anastasios Tsiamis Henrik Sandberg Nikolai Matni Department of Electrical and Systems Engineering University of Pennsylvania Automatic Control Laboratory ETH Zurich Division of Decision and Control Systems KTH Royal Institute of Technology

We present a local minimax lower bound on the excess cost of designing a linear-quadratic controller from offline data. The bound is valid for any offline exploration policy that consists of a stabilizing controller and an energy bounded exploratory input. The derivation leverages a relaxation of the minimax estimation problem to Bayesian estimation, and an application of van Trees inequality. We show that the bound aligns with system-theoretic intuition. In particular, we demonstrate that the lower bound increases when the optimal control objective value increases. We also show that the lower bound increases when the system is poorly excitable, as characterized by the spectrum of the controllability gramian of the system mapping the noise to the state and the $\mathcal{H}_{\infty}$ norm of the system mapping the input to the state. We further show that for some classes of systems, the lower bound may be exponential in the state dimension, demonstrating exponential sample complexity for learning the linear-quadratic regulator.

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Model Predictive control of Oxygen Excess Ratio in Proton Exchange Membrane Fuel Cell: A Comparative Study

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IFAC-PapersOnLine 2024年第13期58卷 241-246页

作者： Hao Fu Jiong Shen Feng Wu Linjun Shi Xiao Wu Junli Zhang Kwang Y. Lee Department of electrical and power engineering Hohai University Nanjing 211100 China Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education Southeast University Nanjing 210096 China Department of Electrical & Computer Engineering Baylor University Waco TX 76798 USA

The oxygen excess ratio (OER) is closely coupled with the entire efficiency of proton exchange membrane fuel cell (PEMFC). However, it is challenging to apply OER regulations owing to unpredictability and frequent load fluctuations. This article employs a feedforward model predictive control to track the optimal OER and reduce the detrimental effect of external current. According to the simulation outcomes, the proposed control performs superior in terms of integral absolute error, disturbance rejection, and tracking trajectory in OER tracking with variable external current than the conventional model predictive control.

关键词： Proton Exchange Membrane Fuel cell Oxygen excess ratio Model predictive control Load fluctuation Disturbance rejection

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