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Midwest Symposium on Circuits and systems (MWSCAS)

作者： Anoop Gopinath Trond Ytterdal Avinash Yadav John Lee Maher Rizkalla Mukesh Kumar Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis Indianapolis USA Department of Electronic Systems Norwegian University of Science and Technology Trondheim Norway Department of Electrical Engineering Indian Institute of Technology Indore Indore India

The noise margin during the write operation in SRAMs is investigated by implementing a negative bitline voltage scheme in this paper. Negative bitline improves the write static noise margin of the SRAM bitcells during a write operation; however, this can cause degraded hold static noise margin of unaccessed cells in the array, called column half-select. Applying a negative wordline voltage on unaccessed rows in an array under negative bitline shows that the degraded hold static noise margin of unaccessed cells can be improved. Fundamentally, the dependence of negative bitline on Vmin,hold of unaccessed cells is negated by applying negative wordline. This allows for a more aggressive scaling of Vmin,hold, resulting in a 77.8% reduction in static power. By applying a complementary negative wordline voltage to counter the half-select condition in columns, the write static noise margin of cells in accessed rows was also boosted by 23% without any degradation in hold static margins of unaccessed cells.

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Prosumers' Participation Through Aggregators in Multi-Carrier Energy systems

Prosumers' Participation Through Aggregators in Multi-Carrie...

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Annual North-American Power Symposium

作者： Dana Marina Gálvez García Guillermo Gutierrez-Alcaraz Jose Horacio Tovar-Hernández Mohammad Sadegh Javadi Department of Electrical Engineering Tecnológico Nacional de México/I. T. Morelia Morelia Mexico Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

In the context of the ongoing energy transition towards renewable sources and the decentralization of generation, multi-carrier energy systems emerge as a comprehensive solution that allows the synergic integration of different energy carriers, such as electricity, natural gas, heat, and storage, offering an effective response to the challenges posed by the variability of renewable generation and the fluctuation of energy demand. In addition, the inherent flexibility of these systems facilitates the management of the variability of renewable generation and adaptation to changes in energy demand, thus contributing to the stability and reliability of supply. In this context, the participation of prosumers who contribute their distributed generation and load flexibility through energy aggregators that effectively coordinate energy supply and demand in real-time ensures a constant balance in the energy system stands out. This paper explores the potential for various prosumer groups, facilitated by multi-carrier energy aggregators, to offer flexible services to electric distribution and natural gas grid utilities, given that natural gas is the prosumers' primary fuel for heating and cooking. The model is formulated as a two-level optimization problem. The upper level results in the emulation of the distribution system, while the lower level minimizes the flexible demand of prosumers. The interaction of the two levels is not through the price of electricity but through prosumer demand. The resulting optimization problem is a mixed-integer linear programming formulation. The results on the IEEE 33-bus distribution and 20-bus natural gas systems allow us to observe that the supply costs in the distribution and natural gas networks are efficiently reduced considering the coordination of prosumers' participation.

关键词： Renewable energy sources Energy consumption Costs Electricity Power system stability Propagation losses Stability analysis Natural gas Optimization Resistance heating

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Adaptive Low-Rank Gradient Descent

Adaptive Low-Rank Gradient Descent

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IEEE Conference on Decision and Control

作者： Ali Jadbabaie Anuran Makur Amirhossein Reisizadeh Laboratory for Information & Decision Systems Massachusetts Institute of Technology Cambridge MA USA Department of Computer Science School of Electrical & Computer Engineering Purdue University West Lafayette IN USA

Low-rank structures have been observed in several recent empirical studies in many machine and deep learning problems, where the loss function demonstrates significant variation only in a lower dimensional subspace. While traditional gradient-based optimization algorithms are computationally costly for high-dimensional parameter spaces, such low-rank structures provide an opportunity to mitigate this cost. In this paper, we aim to leverage low-rank structures to alleviate the computational cost of first-order methods and study Adaptive Low-Rank Gradient Descent (AdaLRGD). The main idea of this method is to begin the optimization procedure in a very small subspace and gradually and adaptively augment it by including more directions. We show that for smooth and strongly convex objectives and any target accuracy $\epsilon$ , AdaLRGD's complexity is $\mathcal{O}(r\ln(r/\epsilon))$ for some rank $r$ no more than dimension $d$ . This significantly improves upon gradient descent's complexity of $\mathcal{O}(d\ln(1/\epsilon))$ when $r\ll d$ . We also propose a practical implementation of AdaLRGD and demonstrate its ability to leverage existing low-rank structures in data.

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Machine learning for battery quality classification and lifetime prediction using formation data

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Energy and AI 2024年第4期18卷 518-530页

作者： Jiayu Zou Yingbo Gao Moritz H.Frieges Martin F.Börner Achim Kampker Weihan Li Chair for Electrochemical Energy Conversion and Storage Systems Institute for Power Electronics and Electrical Drives(ISEA)RWTH Aachen UniversityCampus-Boulevard 8952074 AachenGermany Center for Ageing Reliability and Lifetime Prediction of Electrochemical and Power Electronic Systems(CARL)RWTH Aachen UniversityCampus-Boulevard 89AachenGermany Department of Computer Science RWTH Aachen University52056 AachenGermany Chair of Production Engineering of E-Mobility Components(PEM) RWTH Aachen UniversityBohr 1252072 AachenGermany Juelich Aachen Research Alliance JARA-EnergyGermany

Accurate classification of battery quality and prediction of battery lifetime before leaving the factory would bring economic and safety ***,we propose a data-driven approach with machine learning to classify the battery quality and predict the battery lifetime before usage only using formation *** extract three classes of features from the raw formation data,considering the statistical aspects,differential analysis,and electro-chemical *** correlation between over 100 extracted features and the battery lifetime is analysed based on the ageing *** learning models are developed to classify battery quality and predict battery lifetime by features with a high correlation with battery *** validation results show that the quality classification model achieved accuracies of 89.74% and 89.47% for the batteries aged at 25℃ and 45℃,***,the lifetime prediction model is able to predict the battery end-of-life with mean per-centage errors of 6.50% and 5.45%for the batteries aged at 25℃ and 45℃,*** work highlights the potential of battery formation data from production lines in quality classification and lifetime prediction.

关键词： Battery Formation Quality classification Life prediction Machine learning

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Formal safety verification of unknown continuous-time systems: A data-driven approach 24

Formal safety verification of unknown continuous-time system...

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24th ACM International Conference on Hybrid systems Computation and Control, HSCC 2021, held as part of the 14th Cyber Physical systems and Internet-of-Things Week, CPS-IoT Week 2021

作者： Lavaei, Abolfazl Nejati, Ameneh Jagtap, Pushpak Zamani, Majid Institute for Dynamic Systems and Control Eth Zurich Switzerland Department of Electrical Engineering Technical University of Munich Germany Department of Electrical Engineering Kth Royal Institute of Technology Sweden Department of Computer Science University of Colorado Boulder United States

ISBN: (纸本)9781450383394

This work studies formal verification of continuous-time continuous-space systems with unknown dynamics against safety specifications. The proposed framework is based on a data-driven construction of barrier certificates using which the safety of unknown systems is verified via a finite set of data collected from trajectories of systems with a priori guaranteed confidence. In the proposed scheme, we first cast the original safety problem as a robust convex program (RCP). Since the unknown model appears in one of the constraints of the proposed RCP, we provide the scenario convex program (SCP) corresponding to the original RCP by collecting finite numbers of data from systems' evolutions. We then establish a probabilistic closeness between the optimal value of SCP and that of RCP. Accordingly, we formally quantify the safety guarantee of unknown systems based on the number of data and the required level of safety confidence. Motivations. In the past few years, formal methods have become a promising approach to analyze dynamical systems against high-level logic properties, e.g., those expressed as linear temporal logic (LTL) formulae, in a reliable way. In this regard, barrier certificates, as a discretization-free approach, have received significant attention as a useful tool for formal analysis of complex dynamical systems. In particular, barrier certificates are Lyapunov-like functions defined over the state space of systems subjected to a set of inequalities on both the function itself and its time derivative along the flow of the system. The existence of such a function provides a formal certificate for the safety of the system [1, 2]. To employ the proposed approaches in the setting of barrier certificates, one needs to know precise models of dynamical systems and, hence, those approaches are not applicable where the model is unknown. Although there are some identification techniques in the relevant literature to first learn the model and then provide the analys

关键词： Continuous time systems

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Convergence of energy-based learning in linear resistive networks

arXiv

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arXiv 2025年

作者： Huijzer, Anne-Men Chaffey, Thomas Besselink, Bart van Waarde, Henk J. Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Groningen Netherlands CogniGron - Groningen Cognitive Systems and Materials Center Netherlands Control Group Department of Engineering University of Cambridge United Kingdom School of Electrical and Computer Engineering University of Sydney Australia

Energy-based learning algorithms are alternatives to backpropagation and are well-suited to distributed implementations in analog electronic devices. However, a rigorous theory of convergence is lacking. We make a first step in this direction by analysing a particular energy-based learning algorithm, Contrastive Learning, applied to a network of linear adjustable resistors. It is shown that, in this setup, Contrastive Learning is equivalent to projected gradient descent on a convex function, for any step size, giving a guarantee of convergence for the *** Codes 65K10, 68T05, 93B30, 93D99 © 2025, CC BY-SA.

关键词： Contrastive Learning

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Trust-Aware Resilient Control and Coordination of Connected and Automated Vehicles

arXiv

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arXiv 2023年

作者： Ahmad, H.M. Sabbir Sabouni, Ehsan Xiao, Wei Cassandras, Christos G. Li, Wenchao Division of Systems Engineering Department of Electrical & Computer Engineering Boston University BostonMA United States Computer Science & Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA United States

We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to navigate through a conflict area. Adversarial attacks such as Sybil attacks can cause safety violations resulting in collisions and traffic jams. In addition, uncooperative (but not necessarily adversarial) CAVs can also induce similar adversarial effects on the traffic network. We propose a decentralized resilient control and coordination scheme that mitigates the effects of adversarial attacks and uncooperative CAVs by utilizing a trust framework. Our trust-aware scheme can guarantee safe collision free coordination and mitigate traffic jams. Simulation results validate the theoretical guarantee of our proposed scheme, and demonstrate that it can effectively mitigate adversarial effects across different traffic scenarios. © 2023, CC0.

关键词： Traffic congestion

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Performance Evaluation of Strict Fractional Frequency Reuse and Frequency Reuse Factor-3 in 5G Networks 5

Performance Evaluation of Strict Fractional Frequency Reuse ...

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5th International Conference on Information Technology for Education and Development, ITED 2022

作者： Musa, Abdulwaheed Adekola, Faruk Obasanjo Faruk, Nasir Kwara State University Electrical and Computer Engineering Department Malete Nigeria Institute for Intelligent Systems University of Johannesburg South Africa Directorate of Information and Communication Technology Sule Lamido University Kafin Hausa Jigawa State Nigeria

ISBN: (纸本)9781509064229

The need for high speed data traffic on mobile devices has risen because of the permeating use of gadgets, such as mobile smart phones, notepads and tablets that are constantly running on data. In order to meet these requirements, mobile network providers must set up both tiny cells, high-capacity and very dense, base stations (BSs). This is to cover not only a vast area but also including hotspots with quick, adaptable, and robust supply. The overall spectral efficiency of 5G networks must be improved, and the operations and deployment costs must be decreased. This paper evaluates and compares the performance of Strict Fractional Frequency Reuse (FFR) and Frequency Reuse Factor-3 (FRF-3) according to the cell throughput and cell spectral efficiency with the theoretical peak throughput and peak spectral efficiency as specified in NR 3GPP specifications. The results from the simulation revealed that the FFR performs much better than the FRF-3, however, it is still not efficient in relation to the peak values. © 2022 IEEE.

关键词： 5G mobile communication systems

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Optimal Control of Connected Automated Vehicles with Event-Triggered Control Barrier Functions: a Test Bed for Safe Optimal Merging

arXiv

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arXiv 2023年

作者： Sabouni, Ehsan Sabbir Ahmad, H.M. Xiao, Wei Cassandras, Christos G. Li, Wenchao Division of Systems Engineering Department of Electrical & Computer Engineering Boston University BostonMA United States Computer Science & Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA United States

We address the problem of controlling Connected and Automated Vehicles (CAVs) in conflict areas of a traffic network subject to hard safety constraints. It has been shown that such problems can be solved through a combination of tractable optimal control problems and Control Barrier Functions (CBFs) that guarantee the satisfaction of all constraints. These solutions can be reduced to a sequence of Quadratic Programs (QPs) which are efficiently solved on line over discrete time steps. However, guaranteeing the feasibility of the CBF-based QP method within each discretized time interval requires the careful selection of time steps which need to be sufficiently small. This creates computational requirements and communication rates between agents which may hinder the controller’s application to real CAVs. In this paper, we overcome this limitation by adopting an event-triggered approach for CAVs in a conflict area such that the next QP is triggered by properly defined events with a safety guarantee. We present a laboratory-scale test bed we have developed to emulate merging roadways using mobile robots as CAVs which can be used to demonstrate how the event-triggered scheme is computationally efficient and can handle measurement uncertainties and noise compared to time-driven control while guaranteeing safety. © 2023, CC BY.

关键词： Merging

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical Research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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