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Deep Reinforcement Learning Enabled Bi-level Robust Parameter Optimization of Hydropower-dominated systems for Damping Ultra-low Frequency Oscillation

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Journal of Modern Power systems and Clean Energy 2023年第6期11卷 1770-1783页

作者： Guozhou Zhang Junbo Zhao Weihao Hu Di Cao Nan Duan Zhe Chen Frede Blaabjerg School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu 610054China IEEE Department of Electrical and Computer Engineering University of ConnecticutStorrsCT06269USA Lawrence Livermore National Laboratory LivermoreUSA Department of Energy Technology Aalborg University9220 AalborgDenmark

This paper proposes a robust and computationally efficient control method for damping ultra-low frequency oscillations(ULFOs) in hydropower-dominated systems. Unlike the existing robust optimization based control formulation that can only deal with a limited number of operating conditions, the proposed method reformulates the control problem into a bi-level robust parameter optimization model. This allows us to consider a wide range of system operating conditions. To speed up the bi-level optimization process, the deep deterministic policy gradient(DDPG) based deep reinforcement learning algorithm is developed to train an intelligent agent. This agent can provide very fast lower-level decision variables for the upper-level model, significantly enhancing its computational efficiency. Simulation results demonstrate that the proposed method can achieve much better damping control performance than other alternatives with slightly degraded dynamic response performance of the governor under various types of operating conditions.

关键词： Bi-level robust parameter optimization deep reinforcement learning deep deterministic policy gradient ultralow frequency oscillation damping control stability

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Continuously Optimizing Radar Placement With Model-Predictive Path Integrals

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IEEE Transactions on Aerospace and Electronic systems 2025年第3期61卷 6236-6251页

作者： Potter, Michael Tang, Shuo Ghanem, Paul Stojanovic, Milica Closas, Pau Akcakaya, Murat Wright, Ben Necsoiu, Marius Erdoğmuş, Deniz Everett, Michael Imbiriba, Tales Northeastern University Department of Electrical and Computer Engineering BostonMA02115 United States University of Pittsburgh Department of Electrical and Computer Engineering PittsburghPA15260 United States Kostas Research Institute BurlingtonMA01803 United States DEVCOM Army Research Laboratory San AntonioTX78204 United States University of Massachusetts Boston BostonMA02125 United States

Continuously optimizing sensor placement is essential for precise target localization in various military and civilian applications. While information theory has shown promise in optimizing sensor placement, many studies oversimplify sensor measurement models or neglect dynamic constraints of mobile sensors. To address these challenges, we employ a range measurement model that incorporates radar parameters and radar–target distance, coupled with model-predictive path integral control to manage complex environmental obstacles and dynamic constraints. We compare the proposed approach against stationary radars or simplified range measurement models based on the root-mean-squared error (RMSE) of the cubature Kalman filter estimator for the targets' state. In addition, we visualize the evolving geometry of radars and targets over time, highlighting areas of highest measurement information gain, demonstrating the strengths of the approach. The proposed strategy outperforms stationary radars and simplified range measurement models in target localization, achieving a 38%–74% reduction in the mean RMSE and a 33%–79% reduction in the upper tail of the 90% highest density interval over 500 Monte Carlo trials across all time steps. © 1965-2011 IEEE.

关键词： Mean square error

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A New Technique of Soluble NPK Nutrient Detection system Using Deep Learning-Based Recurrent Neural Networks (RNN) 12

A New Technique of Soluble NPK Nutrient Detection System Usi...

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12th International electrical engineering Congress, iEECON 2024

作者： Tipwong, Wallop Sirikham, Adisorn Konpang, Jessada Kirdpipat, Putthiphong Chongjarearn, Yutana Preutisrunyanont, Oradee Rajamangala University Of Technology Krungthep Department Of Electrical And Telecommunication Engineering Bangkok Thailand Thammasat School Of Engineering Thammasat University Faculty Of Engineering Department Of Electrical And Computer Engineering Pathum Thani Thailand Dhurakij Pundit University Department Of Robotic Engineering And Automation System Bangkok Thailand

ISBN: (纸本)9798350383591

Modern agriculture relies heavily on effective process monitoring, control, and remote data collection, making accurate and cost-effective sensors crucial for innovation. This research focuses on the development of a spectroscopy-based device for real-time and remote monitoring of nutrient levels in hydroponic systems. The device utilizes IoT architecture, incorporating principles of light absorbance to quantify concentrations of essential nutrients during crop growth. Three deep learning techniques, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) were adopted for data analysis. Results demonstrate that tailored implementation of deep learning can significantly enhance the performance of sensor network system (SNS). Specifically, the RNN format achieved an impressive 98% model accuracy during both training and testing phases. The technological advancements in addressing contract variation and photometric levels contribute to increased accuracy as more sensors become available. The findings serve as a comprehensive guide for collecting extensive agricultural data, encompassing environmental factors throughout the entire cultivation period, using state-of-the-art remote control sensor equipment. This work provides a practical, efficient, and cost-effective solution for precise nutrient control and continuous data monitoring in agricultural production. © 2024 IEEE.

关键词： Cost effectiveness

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Tunable VO_(2) cavity enables multispectral manipulation from visible to microwave frequencies

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Light(Science & Applications) 2024年第3期13卷 510-518页

作者： Hang Wei Jinxin Gu Tao Zhao Zhiyuan Yan He-Xiu Xu Shuliang Dou Cheng-Wei Qiu Yao Li Center for Composite Materials and Structure Harbin Institute of TechnologyHarbin 150001China National University of Singapore Department of Electrical&Computer EngineeringSingapore 117583Singapore School of Chemical Engineering and Technology Harbin Institute of TechnologyHarbin 150001China Suzhou Laboratory Suzhou 215123China

Optical materials capable of dynamically manipulating electromagnetic waves are an emerging field in memories,optical modulators,and thermal ***,their multispectral design preliminarily attracts much attention,aiming to enhance their efficiency and integration of ***,the multispectral manipulation based on these materials is challenging due to their ubiquitous wavelength dependence restricting their capacity to narrow *** this article,we cascade multiple tunable optical cavities with selective-transparent layers,enabling a universal approach to overcoming wavelength dependence and establishing a multispectral platform with highly integrated *** on it,we demonstrate the multispectral(ranging from 400 nm to 3 cm),fast response speed(0.9 s),and reversible manipulation based on a typical phase change material,vanadium *** platform involves tandem VO_(2)-based Fabry–Pérot(F-P)cavities enabling the customization of optical responses at target bands *** can achieve broadband color-changing capacity in the visible region(a shift of~60 nm in resonant wavelength)and is capable of freely switching between three typical optical models(transmittance,reflectance,and absorptance)in the infrared to microwave regions with drastic amplitude tunability exceeding *** work represents a state-of-art advance in multispectral optics and material science,providing a critical approach for expanding the multispectral manipulation ability of optical systems.

关键词： spectral microwave visible

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Single Photon LiDAR Compression: An Overview 66

Single Photon LiDAR Compression: An Overview

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2023 IEEE 66th International Midwest Symposium on Circuits and systems, MWSCAS 2023

作者： Al-Shabili, Abdullah H Weerasooriya, Hashan K Weligampola, Harshana Chennuri, Prateek Abshire, Pamela Chan, Stanley School of Electrical and Computer Engineering Purdue University West LafayetteIN United States University of Maryland Department of Electrical and Computer Engineering Institute of System Research College ParkMD United States

ISBN: (纸本)9798350302103

Real-time mapping of the surroundings plays a pivotal role in ensuring the success of autonomous vehicles. Among the technologies showing promise for depth mapping is Single Photon Light Detection and Ranging (SPL) which offers impressive long-range capabilities, superior depth resolution, and energy-efficient laser sources. However, the adoption of high-resolution, high frame-rate SPL systems results in significant data volumes, often reaching several Gbit/s. This creates a throughput bottleneck that impedes real-time applications and necessitates the development of effective compression schemes. This paper addresses the challenges associated with SPL compression and provides a comprehensive overview of recent advancements in this domain. The review encompasses various compression methods, including algorithmic and/or hardware-based approaches, spatial and/or temporal compression techniques. We also discuss future directions, such as integrating deep learning and fusion techniques with other sensing modalities. © 2023 IEEE.

关键词： compression compressive learning compressive sensing deep learning depth imaging Single Photon LiDAR (SPL)

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A Holistic State Estimation Framework for Active Distribution Network with Battery Energy Storage system

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Journal of Modern Power systems and Clean Energy 2022年第3期10卷 627-636页

作者： Shaojian Song Huangjiao Wei Yuzhang Lin Cheng Wang Antonio Gómez-Expósito IEEE School of Electrical Engineering Guangxi UniversityNanning 530004China Department of Electrical and Computer Engineering University of MassachusettsLowellMA 01852USA State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power UniversityBeijing 102206China Laboratory of Engineering for Energy and Environmental Sustainability University of SevilleSpain

Battery energy storage systems(BESSs)are expected to play a crucial role in the operation and control of active distribution networks(ADNs).In this paper,a holistic state estimation framework is developed for ADNs with BESSs integrated.A dynamic equivalent model of BESS is developed,and the state transition and measurement equations are *** on the equivalence between the correction stage of the iterated extended Kalman filter(IEKF)and the weighted least squares(WLS)regression,a holistic state estimation framework is proposed to capture the static state variables of ADNs and the dynamic state variables of BESSs,especially the state of charge(SOC).A bad data processing method is also *** simulation results show that the proposed holistic state estimation framework improves the accuracy of state estimation as well as the capability of bad data detection for both ADNs and BESSs,providing comprehensive situational awareness for the whole system.

关键词： Active distribution network(ADN) anomaly detection battery energy storage system(BESS) Kalman filtering situational awareness state estimation state of charge(SOC)

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A Wireless and Battery-Free Wearable Pressure Sensing system for Human-Machine Interaction and Health Monitoring

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2023年第6期2卷 439-447页

作者： Lee, Sang Won Pei, Xiaochang Rajendran, Jerome Esfandyarpour, Rahim University of California at Irvine Henry Samueli School of Engineering Department of Electrical Engineering and Computer Science Laboratory for Integrated Nano Bio Electronics Innovation IrvineCA92697 United States

Wearable devices have received tremendous interest in healthcare monitoring due to their significant advantages in terms of flexibility, noninvasiveness, wireless capability, and portability. However, they still face challenges, including the need for external power sources, bulky measuring instruments, and a lack of a wireless data transport system. Herein, we propose a PEDOT:PSS/MXene pressure sensing platform based on 2-D e-textile and screen-printed interdigitated electrodes (IDEs). Both materials improve the electrical conductivity, sensitivity, stability, flexibility, and mechanical durability of the pressure sensor. A near-field communication (NFC) readout system provides real-time wireless monitoring by transmitting signals from the sensor to a smartphone app, without external batteries. The pressure sensor has sensitivity, a wide detection range, excellent repeatability and stability, fast response/recovery time, and long-term durability. Long-term usability was verified through the bending test up to 21400 cycles. The flexible pressure sensor successfully monitored wrist pulse, physical movements, and various muscle movements in the body. Repeatable, stable, reliable, and regular signals were obtained wirelessly through the NFC readout system. Our sensing platform could be a promising solution for healthcare monitoring, rehabilitation therapy, and early medical diagnosis. In addition, it suggests a new platform for helping people with disabilities to communicate with others through human-machine interaction. © 2022 IEEE.

关键词： Pressure sensors

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Towards constrained grid-forming control 59

Towards constrained grid-forming control

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59th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2023

作者： Gros, Dominic Lyu, Xue University of Wisconsin-Madison Department of Electrical and Computer Engineering United States University of Wisconsin-Madison University Pacific Northwest National Laboratory Department of Electrical and Computer Engineering United States

ISBN: (纸本)9798350328141

Grid-forming converters are commonly envisioned to replace conventional synchronous generators as the cornerstone of future power systems. However, compared to synchronous generators, power converters and their power sources (e.g., renewable generation, energy storage) are subject to significant physical constraints (e.g., current limits, modulation limits). Grid-forming controls are commonly designed neglecting these constraints and subsequently augmented with limiters for a subset of constraints. In this work, we propose a systematic approach to constrained grid-forming control of two-level voltage source converters interfacing photovoltaics. We first formulate grid-forming control objectives and constraints of voltage source converters and photovoltaics in a one-step optimal grid-forming control problem. Next, we leverage primal-dual dynamics to obtain a dynamic feedback controller that approximates the solution of the one-step optimal grid-forming control problem. Finally, electromagnetic transient simulations are used to illustrate the results. © 2023 IEEE.

关键词： Electromagnetic simulation

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Cell-Free MIMO Perceptive Mobile Networks: Cloud Vs. Edge Processing

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IEEE Transactions on Vehicular Technology 2025年第6期74卷 9520-9532页

作者： Jeong, Seongah Kang, Jinkyu Simeone, Osvaldo Shamai, Shlomo University of Seoul School of Advanced Fusion Studies Department of Intelligent Semiconductor Engineering Seoul02504 Korea Republic of Myongji University Department of Information and Communication Engineering Gyeonggi-do Korea Republic of LondonWC2B 4BG United Kingdom Technion Department of Electrical and Computer Engineering Haifa3200003 Israel

Perceptive mobile networks (PMNs) implement sensing and communication by reusing existing cellular infrastructure. Thanks to the cooperation among distributed access points, cell-free multiple-input multiple-output (MIMO) systems support the deployment of multistatic radar sensing, while providing high spectral efficiency for data communication services. To this end, in a cell-free MIMO system, distributed access points (APs) communicate over fronthaul links with a central processing unit (CPU) in the cloud. This work proposes four different types of PMN uplink solutions based on cell-free MIMO systems, in which the sensing and decoding functionalities are carried out at either the cloud or the edge. Accordingly, we develop and compare joint cloud-based decoding and sensing (CDCS), hybrid cloud-based decoding and edge-based sensing (CDES), hybrid edge-based decoding and cloud-based sensing (EDCS) and edge-based decoding and sensing (EDES). In all cases, we target a unified design problem formulation for fronthaul quantization to maximize the achievable rate under sensing and fronthaul capacity constraints. Via numerical results, the four implementation scenarios are compared as a function of the available fronthaul resources by highlighting the relative merits of edge- and cloud-based sensing and communications. This study provides guidelines on the optimal functional allocation in fronthaul-constrained networks implementing integrated sensing and communications. © 2025 IEEE.

关键词： Multistatic radars

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New tunable phase oscillator structure

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International Journal of Electronics Letters 2024年第1期12卷 41-48页

作者： Elwakil, A.S. Psychalinos, Costas Maundy, Brent Department of Electrical and Computer Engineering University of Sharjah Sharjah United Arab Emirates Department of Electrical and Software Engineering University of Calgary Calgary AB Canada Electronics Laboratory Department of Physics University of Patras Rio Patras Greece

In this Letter, we introduce and experimentally verify a very simple tunable-phase oscillator structure based on cascaded standard filter sections. In particular, a standard inverting second-order low-pass filter is cascaded with a first-order bi-linear filter in a closed loop resulting in a third-order structure that can be made marginally stable. The phase difference between the outputs of the two filter sections is a design parameter that is tunable independent of the oscillation frequency or start-up gain. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： all-pass filters low-pass filters multi-phase oscillators Sinusoidal oscillators tunable phase

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