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arXiv 2021年

作者： Sun, Ke Esnaola, Iñaki Tulino, Antonia M. Poor, H. Vincent The Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom The Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States The DIETI Università degli Studi di Napoli Federico II Naples80138 Italy The ECE Department New York University Tandon School of Engineering BrooklynNY10003 United States

Information-theoretic stealth attacks are data injection attacks that minimize the amount of information acquired by the operator about the state variables, while simultaneously limiting the Kullback-Leibler divergence between the distribution of the measurements under attack and the distribution under normal operation with the aim of controling the probability of attack detection. For Gaussian distributed state variables, attack construction requires knowledge of the second order statistics of the state variables, which is estimated from a finite number of past realizations using a sample covariance matrix. Within this framework, the attack performance is studied for the attack construction with the sample covariance matrix. This results in an analysis of the amount of data required to learn the covariance matrix of the state variables used on the attack construction. The ergodic attack performance is characterized using asymptotic random matrix theory tools, and the variance of the attack performance is bounded. The ergodic performance and the variance bounds are assessed with simulations on IEEE test systems. © 2021, CC BY-NC-ND.

关键词： Covariance matrix

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Corrigendum to “A secure data transmission framework for IoT enabled healthcare” [Heliyon Volume 10, Issue 16, August 2024, Article e36269]

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Heliyon 2025年

作者： Sohail Saif Priya Das Suparna Biswas Shakir Khan Mohd Anul Haq Viacheslav Kovtun Department of Computer Applications Maulana Abul Kalam Azad University of Technology Haringhata 741249 India Department of Computer Science Chakdaha College Chakdaha 741222 India Department of Computer Science & Engineering Maulana Abul Kalam Azad University of Technology Haringhata 741249 India College of Computer and Information Sciences Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh 11432 Saudi Arabia University Centre for Research and Development Chandigarh University Mohali 140413 India Department of Computer Science College of Computer and Information Sciences Majmaah University Al-Majmaah 11952 Saudi Arabia Computer Control Systems Department Vinnytsia National Technical University Vinnytsia Ukraine

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Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots

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Sustainable Cities and Society 2021年 74卷 103197-103197页

作者： Mansour-Saatloo, Amin Ebadi, Ramin Mirzaei, Mohammad Amin Zare, Kazem Mohammadi-Ivatloo, Behnam Marzband, Mousa Anvari-Moghaddam, Amjad Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical Engineering Sahand University of Technology Tabriz Iran Northumbria University Electrical Power and Control Systems Research Group Ellison PlaceNewcastle upon TyneNE1 8ST United Kingdom Aalborg University Aalborg9220 Denmark Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia

There is little room for doubt that distributed generation systems including renewable energy, microgrids (MGs), combined heat and power (CHP) units and storage systems have been of particular importance in sustaining low-carbon and cost-effective operations due to the tremendous increase in greenhouse gas emissions in recent years. Additionally, hydrogen-based power technologies have earned a great deal of publicity that hydrogen can serve as a zero-emission fuel for electrical power and thermal energy production. In this regard, the current paper proposes an optimal energy management strategy for a combined hydrogen, heat, and power MG (CHHP-MG) with hydrogen fueling stations (HFSs) for hydrogen vehicles (HVs), electric vehicle parking lots (EVPLs) and fuel cell micro-CHP (FC-MCHP) units to meet power and heat requirements. In order to reduce the regular operating expense, the presented CHHP-MG could also communicate with both electricity and hydrogen markets. In addition, to compensate for the associated heat and hydrogen requirements, power-to-X technologies such as the power to heat (P2HT) and power to hydrogen (P2H) are integrated. In order to improve flexibility and build a low carbon MG, multi-energy storage (MES) system along with heat and power demand response (HPDR) programs will be taken into consideration. As the uncertainties associated with the predicted wind and photovoltaic power have a major impact on the energy management of the CHHP-MG, a multi-objective information gap decision theory (IGDT)-based robust approach is applied as an effective non-probabilistic modeling technique for handling such uncertainties. The empirical results show that the proposed model can efficiently handle the uncertainties and reduce the overall operation cost by 76.35%. © 2021 Elsevier Ltd

关键词： Energy management

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Integrated carbon and nitrogen management for cost-effective environmental policies in China

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Science (New York, N.Y.) 2025年第6751期388卷 1098-1103页

作者： Xin Xu Xiuming Zhang Yiyang Zou Tianrun Chen Jingfang Zhan Luxi Cheng Wilfried Winiwarter Shaohui Zhang Peter M Vitousek Wim de Vries Baojing Gu State Key Laboratory of Soil Pollution Control and Safety Zhejiang University Hangzhou China. College of Environmental and Resource Sciences Zhejiang University Hangzhou China. International Institute for Applied Systems Analysis Laxenburg Austria. Ministry of Education Key Laboratory of Environment Remediation and Ecological Health Zhejiang University Hangzhou China. College of Computer Science and Technology Zhejiang University Hangzhou China. Policy Simulation Laboratory Zhejiang University Hangzhou China. Institute of Environmental Engineering University of Zielona Góra Zielona Góra Poland. School of Economics and Management Beihang University Beijing China. Department of Earth System Science Stanford University Stanford CA USA. Wageningen University and Research Earth Systems and Global Change Group Wageningen Netherlands. Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment Zhejiang University Hangzhou China.

Carbon and nitrogen are central elements in global biogeochemical cycles. To effectively manage carbon and nitrogen in China, we developed a comprehensive model for quantifying their fluxes, investigating their interplay across 16 human and natural subsystems. Between 1980 and 2020, nitrogen losses in China increased 2.3-fold and carbon emissions surged 6.5-fold. Integrated carbon and nitrogen management holds the potential for a 74% reduction in nitrogen losses to air and water and a 91% decrease in carbon emissions to the atmosphere by 2060. Compared with separate control of carbon or nitrogen, integrated management delivers an additional reduction of 1.8 million tons of nitrogen and 26.5 million tons of carbon by 2060, bringing out a 37% decrease in unit abatement cost and a net societal benefit of 1384 billion USD.

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Zeroth-order algorithms for stochastic distributed nonconvex optimization

arXiv

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arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

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control and decision method for overtaking problem in autonomous vehicles 16

Control and decision method for overtaking problem in autono...

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16th Mini Conference on Vehicle System Dynamics, Identification and Anomalies, VSDIA 2018

作者： Hegedűs, Tamás Németh, Balázs Bede, Zsuzsanna Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Stoczek utca. 2 BudapestH-1111 Hungary Systems and Control Laboratory Institute for Computer Science and Control Kende utca 13-17 BudapestH-1111 Hungary

In this paper we deal with an overtaking and lane change strategy for autonomous vehicles. The algorithm is divided into two main layers. The upper layer is responsible for the decision making (e.g lane changing). Before decision-making we predict the motion of other participants and divide the road into discrete sets in each interval, then we compute the probability of occupancy. Considering the state of the motion of ego vehicle we can compute the probability of collision. After assigning a graph points to discrete elements, the probability of collision is ordered to the graph edges, then we determine the route with the smallest cost. The decision-making algorithm is not able to control the vehicle, so it is necessary to design a traceable trajectory for the vehicle. Since we have a series of points to be reached for the future, this can be used as a reference vector for the trajectory design algorithm. One Model Predicitve controller (MPC) is responsible for the design of the trajectory so we can obtain limitations to several states to ensure comfort and security. Extending the algorithm, we can compute the longitudinal movement as well. In this paper the decision-making and the trajectory planning algorithm is presented, and the whole model validated in CarMaker. © 2019 Budapest University of Technology and Economics. All rights reserved.

关键词： Decision making

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An IoT Edge Computing System Architecture and its Application

An IoT Edge Computing System Architecture and its Applicatio...

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2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Chen, Shichao Li, Qijie Zhang, Hua Zhu, Fenghua Xiong, Gang Tang, Ying Macau University of Science and Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences China Beijing University of Technology State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Aerospace Smart Manufacturing Technology Development Co. Ltd Platform Research and Development Department Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Engineering Research Center of Intelligent Systems and Technology Institute of Automation Cloud Computing Center Chinese Academy of Sciences Beijing China Rowan University Department of Electrical and Computer Engineering GlassboroNJ United States Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao China

ISBN: (纸本)9781728168531

As the number of devices connected to the Internet of things (IoT) surges, the amount of data explodes. Therefore it not only increases the bandwidth load of data transmission but also aggravates the computing and storage load of a cloud platform. At the same time, the traditional computing paradigm centered on cloud computing cannot meet the real-time requirements in many application scenarios. The emergence of edge computing can solve the problems of realtime data processing and network bandwidth occupation in the current IoT scene. In this paper, according to the characteristics of IoT, such as fragmented data, heterogeneous network, and limited energy consumption, the architecture of an IoT edge computing system is constructed to suit better an IoT scene. In addition, the application of edge computing key technologies such as virtualization, edge intelligence, computing offload, collaborative scheduling and micro-services in resource-constrained IoT scenarios is analyzed in detail. Finally, the functions and application of energy consumption monitoring and optimization to a central air-conditioning system are analyzed and summarized, which is a typical application of edge computing in the context of the IoT. © 2020 IEEE.

关键词： Edge computing

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Secure Platooning of Autonomous Vehicles Under Attacked GPS Data

arXiv

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arXiv 2020年

作者： He, Xingkang Hashemi, Ehsan Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooON Canada

In this paper, we study how to secure the platooning of autonomous vehicles when an unknown vehicle is under attack and bounded system uncertainties exist. For the attacked vehicle, its position and speed measurements from GPS can be manipulated arbitrarily by a malicious attacker. First, to find out which vehicle is under attack, two detectors are proposed by using the relative measurements (by camera or radar) and the local innovation obtained through measurements from neighboring vehicles. Then, based on the results of the detectors, we design a local state observer for each vehicle by applying a saturation method to the measurement innovation. Moreover, based on the neighbor state estimates provided by the observer, a distributed controller is proposed to achieve the consensus in vehicle speed and keep fixed desired distance between two neighboring vehicles. The estimation error by the observer and the platooning error by the controller are shown to be asymptotically upper bounded under certain *** effectiveness of the proposed methods is also evaluated in numerical simulations. Copyright © 2020, The Authors. All rights reserved.

关键词： Autonomous vehicles

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A Dynamical Game Approach for Integrated Stabilization and Path Tracking for Autonomous Vehicles

A Dynamical Game Approach for Integrated Stabilization and P...

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American control Conference

作者： Ehsan Hashemi Xingkang He Karl Henrik Johansson Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

A new game theory based framework is proposed for path tracking and stabilization of autonomous vehicles. In the developed framework, vehicle body and corner traction control strategies are formulated in terms of players in a differential game. An integrated stability and path tracking control based on a non-cooperative differential game is developed. It includes bidirectional slip effect and wheel dynamics, which reflect more accurate longitudinal and lateral dynamics in harsh maneuvers and scenarios with sudden changes in the path planners trajectories. The open-loop and closed-loop Nash equilibrium control strategies are obtained by solving a two-player linear-quadratic differential game for the dynamical system of the overall tracking error. The performance of the proposed control strategy is validated with software simulations in various driving conditions.

关键词： Autonomous Vehicles tracking path-tracking control control strategy Driving Conditions DYNAMICAL systems Players

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Network Analysis Identifies Circulating miR-155 as Predictive Biomarker of Type 2 Diabetes Mellitus Development in Obese Patients: A Pilot Study

Journal of Liquid Biopsy, The

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Journal of Liquid Biopsy, The 2023年 1卷 100070-100070页

作者： Catanzaro, G. Conte, F. Trocchianesi, S. Splendiani, E. Bimonte, V. D'Antonio, F. Paci, P. Morano, S. Migliaccio, S. Ferretti, E. Department of Experimental Medicine Sapienza University of Rome Rome Italy Institute for Systems Analysis and Computer Science "A. Ruberti" (IASI) National Research Council (CNR) Rome Italy Department of Movement Human and Health Sciences University of Foro Italico Rome Italy Department of Computer Control and Management Engineering Sapienza University Rome Italy

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