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63rd IEEE Conference on Decision and control, CDC 2024

作者： Liu, Tong Krstic, Miroslav Jiang, Zhong-Ping New York University Control and Networks Lab Department of Electrical and Computer Engineering Tandon School of Engineering BrooklynNY11201 United States University of California Department of Mechanical and Aerospace Engineering San DiegoCA92093-0411 United States

ISBN: (纸本)9798350316339

This paper studies the distributed feedback optimization problem for linear multi-agent systems without precise knowledge of local costs and agent dynamics. The proposed solution is based on a hierarchical approach that uses upper-level coordinators to adjust reference signals toward the global optimum and lower-level controllers to regulate agents' outputs toward the reference signals. In the absence of precise information on local gradients and agent dynamics, an extremum-seeking mechanism is used to enforce a gradient descent optimization strategy, and an adaptive dynamic programming approach is taken to synthesize an internal-model-based optimal tracking controller. The whole procedure relies only on measurements of local costs and input-state data along agents' trajectories. Moreover, under appropriate conditions, the closed-loop signals are bounded and the output of the agents exponentially converges to a small neighborhood of the desired extremum. A numerical example is conducted to validate the efficacy of the proposed method. © 2024 IEEE.

关键词： Dynamic programming

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Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

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Fluid Dynamics & Materials Processing 2023年第6期19卷 1369-1383页

作者： Xing Deng Feipeng Da Haijian Shao School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA

This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional *** work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells,namely,eosinophils,neutrophils,monocytes,and lymphocytes,known for their relationship with human body damage,inflammatory regions,and organ illnesses,in particular,and with the health of the immune system and other hazards,such as cardiovascular disease or infections,more in *** results of the experiments show that the deep learning models can automatically extract features from the blood cell images and properly classify them with an accuracy of 98%,97%,and 89%,respectively,with regard to the training,verification,and testing of the corresponding datasets.

关键词： Blood cell analysis deep learning models classification-detection

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Adaptive Fuzzy Logic controller For Maximum Power Point Tracking of DFIG Wind Turbine 24

Adaptive Fuzzy Logic Controller For Maximum Power Point Trac...

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24th International Middle East Power System Conference, MEPCON 2023

作者： Elnaghi, Basem E. Abdel-Wahab, M.N. Ismaiel, Ahmed M. Abdel-Kader, Fathy Elsayed Ahmed Mohammed, Reham H. Suez Canal University Electrical Power and Machine Department Ismailia Egypt Menoufia University Electrical Power and Machine Department menoufia Egypt Suez Canal University Computer and Control Engineering Department Ismailia Egypt

ISBN: (纸本)9798350358469

It is important to use a reliable maximum power point tracking (MPPT) approach to guarantee that wind production systems are fully beneficial. This paper is discussing the operation principle of adaptive fuzzy logic controllers (AFLC) in double fed induction generator wind turbine. The acquired findings attest to AFLC's superiority over traditional PI control systems. The adaptive fuzzy logic controller has more promising results as compared to old PI controller. The investigation has been done by using MATLAB/SIMULINK 2023a package. The proposed controller has less rising time than conventional PI controller by more the 40% and better power tracking by 32.21%. The results of using adaptive fuzzy logic controller revealed fast time response, high rate of convergence, minimal steady state error, and less overshoot compared to those achieved with conventional PI. These indicators are used to show that AFLC is feasible when compared to other controllers with the same WPP. © 2023 IEEE.

关键词： controllers

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On non-von Neumann flexible neuromorphic vision sensors

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npj Flexible Electronics 2024年第1期8卷 638-663页

作者： Hao Wang Bin Sun Shuzhi Sam Ge Jie Su Ming Liang Jin Institute for Future Shandong Key Laboratory of Industrial Control TechnologySchool of AutomationQingdao UniversityQingdao 266071China College of Electronic and Information Engineering Qingdao UniversityQingdao 266071China Department of Electrical and Computer Engineering and Institute for Functional Intelligent MaterialsNational University of SingaporeSingapore 117583Singapore

The structure andmechanismof thehuman visual system contain rich treasures,and surprising effects can be achieved by simulating the human visual *** this article,starting from the human visual system,we compare and discuss the discrepancies between the human visual system and traditional machine vision *** the wide variety and large volume of visual information,the use of nonvon Neumann structured,flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann ***,this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing ***,in terms of mimicking the retinal surface structure,this article introduces the fabrication approach for flexible sensor ***,this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.

关键词： Neumann system starting

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A Multi-Layer Long Short-Term Memory Neural Network on Battery State-of-Health Estimation with Transfer Learning 3

A Multi-Layer Long Short-Term Memory Neural Network on Batte...

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3rd IEEE International Conference on Industrial Electronics for Sustainable Energy Systems, IESES 2023

作者： Tian, Jilun Zhang, Jiusi Jiang, Yuchen Luo, Hao Huang, Congsheng Chow, Mo-Yuen Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan North Carolina State University Department of Electrical and Computer Engineering RaleighNC27606 United States

ISBN: (纸本)9798350324754

Due to the important part of batteries in industrial systems, its safety analysis has causes widespread attention from researchers, and its effective maintenance decision-making is needed. Data-driven state-of-health (SOH) estimation can provide useful information by monitoring historical data during the aging process, but it can be failed in the cross-domain scenarios due to the different data distributions. To tackle this issue, we propose a long short-term memory (LSTM) neural network with an additional fully connected dense as a basic predictor, and apply the pretrain and fine-tuning training algorithm to realize the high-performance prediction. By validated in two real-world datasets, we find that blindly expanding the training set may have a negative impact on model accuracy, and the proposed TL-LSTM can achieve a great performance under the cross-domain tasks. © 2023 IEEE.

关键词： Long short-term memory

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A Cooperative Feature Removal Mechanism for Cell Outage Detection in Wireless Telecommunication Networks 19th

A Cooperative Feature Removal Mechanism for Cell Outage Det...

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19th International Conference on Critical Information Infrastructures Security, CRITIS 2024

作者： Wrona, Andrea Gentile, Simone De Santis, Emanuele Giuseppi, Alessandro Pietrabissa, Antonio Delli Priscoli, Francesco Department of Computer Control and Management Engineering "Antonio Ruberti" Sapienza University of Rome via Ariosto 25 Lazio Rome00185 Italy Department of Electrical and Information Engineering Polytechnic of Bari via Re David 200 Puglia Bari70125 Italy

ISBN: (纸本)9783031842597

In the domain of crisis management for telecommunications infrastructures, the autonomous detection of cell outages within cellular networks is of paramount importance for prompt identification and resolution in ensuring uninterrupted connectivity to users. Traditional methods usually involve data aggregation at the core network, which is responsible for identifying cell failures. Proposing a novel approach, we leverage a Machine Learning-based distributed and cooperative feature removal mechanism in order to preserve the privacy of data and avoid any degradation in classification performance. Simulations carried out on a dataset retrieved from a real 4G-LTE rollout demonstrate that the proposed approach, through a cooperation among agents, maintains or even slightly improves accuracy, precision, recall, and F1-score in outage prediction compared to other conventional methods, showcasing its efficacy for cell outage detection purposes while maintaining data privacy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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Rapid stabilization of stochastic quantum systems in a unified framework

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Chinese Physics B 2023年第7期32卷 216-225页

作者：温杰王芳敏史元浩贾建芳曾建潮 School of Electrical and Control Engineering North University of ChinaTaiyuan 030051China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijing 100084China School of Computer Science and Technology North University of ChinaTaiyuan 030051China

Rapid stabilization of general stochastic quantum systems is investigated based on the rapid stability of stochastic differential *** introduce a Lyapunov-LaSalle-like theorem for a class of nonlinear stochastic systems first,based on which a unified framework of rapidly stabilizing stochastic quantum systems is *** to the proposed unified framework,we design the switching state feedback controls to achieve the rapid stabilization of singlequbit systems,two-qubit systems,and N-qubit *** the unified framework,the state space is divided into two state subspaces,and the target state is located in one state subspace,while the other system equilibria are located in the other state *** the designed state feedback controls,the system state can only transit through the boundary between the two state subspaces no more than two times,and the target state is globally asymptotically stable in *** particular,the system state can converge exponentially in(all or part of)the state subspace where the target state is ***,the effectiveness and rapidity of the designed state feedback controls are shown in numerical simulations by stabilizing GHZ states for a three-qubit system.

关键词： rapid stabilization state feedback stochastic quantum systems switching control

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ℋ₂ state-feedback control for continuous semi-Markov jump linear systems with rational transition rates

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International Journal of control 2023年第1期96卷 1-11页

作者： de Almeida, M. Souza, M. Fioravanti, A.R. Costa, O.L.V. School of Mechanical Engineering University of Campinas Campinas Brazil School of Electrical and Computer Engineering University of Campinas Campinas Brazil Department of Telecommunications and Control Engineering Polytechnic School University of Sao Paulo Sao Paulo Brazil

This paper presents the (Formula presented.) State-Feedback control for Continuous Semi-Markov Jump Linear Systems where the transition rates are given by the ratio of polynomials of the sojourn time. We show that, for instance, Rayleigh-, Erlang- and a class of Weibull-distributed sojourn time can be described by such a model. We present general results on the stability and on the (Formula presented.) of Semi-Markov Jump Linear Systems and provide sum-of-squares conditions for norm calculation and state-feedback control design problems. We conclude the paper by presenting two numerical examples that point out the main features of our results and by discussing future directions and related problems. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

关键词： convex optimisation Linear systems stochastic systems sum-of-squares

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Characterization and Trading of Energy Level and Energy Shift Considering Virtual Power Plant

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1784-1789页

作者： Shuai Fan Jucheng Xiao Zuyi Li Guangyu He Key Laboratory of Control of Power Transmission and Conversion Ministry of EducationShanghai Jiao Tong UniversityShanghai200240China Department of Electrical and Computer Engineering Illinois Institute of TechnologyChicagoIL 60616USA

The capability of shifting the electricity generation or consumption to proper time of the day,also defined as energy shift(ES),is the key factor to ensure the power balance,especially under high penetration of variable renewable energy(VRE).However,the ES is not characterized and traded as an independent product in current market *** this letter,the marginal utility of an ES is assessed and leveraged to characterize the effective ES,while a novel market scheme is proposed considering the trading of both ES and energy level(EL).The proposed scheme can well integrate ES producers such as virtual power plants that cannot be rewarded sufficiently to actively participate in the current market because they are principally labeled as EL ***,the novel concept and mechanism are illustrated by a numerical study and verified to outperform the existing price schemes on integrating the ES resources and VRE.

关键词： Energy level energy shift variable renewable energy virtual power plant marginal utility

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Supremal and Robust control against Actuator Jamming Attacks in Cyber-Physical Systems

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2023年第9期9卷 1-13页

作者： Duo, Wenli Wang, Shouguang Zhou, MengChu You, Dan Wisniewski, Remigiusz Bazydlo, Grzegorz Albeshri, Aiiad Institute of Systems Engineering Macau University of Science and Technology Macau China School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Department of Computer Science King Abdulaziz University Jeddah Saudi Arabia

Cyber-physical systems, such as unmanned aerial vehicles and connected and autonomous vehicles, are vulnerable to cyber attacks, which can cause significant damage to society. This paper examines the attack issue in cyber-physical systems within the framework of discrete event systems. Specifically, we consider a scenario where a malicious intruder injects a jamming signal into an actuator channel. It disrupts the transmission of control commands and prevents an actuator from receiving them. This is termed an actuator jamming attack. In the paper, we first analyze the closed-loop system behavior under such an attack. An attack structure is constructed to illustrate how an intruder exploits a jamming attack to drive a system into unsafe states. Then, we study the supervisory control problem for a system exposed to such an attack. The problem is reduced to a basic supervisory control one in discrete event systems by introducing the concept of dynamically controllable language. A solution to this problem is explored, where we establish an existence condition for a supremal and robust supervisor that is capable of defending against actuator jamming attacks, and design an algorithm to derive it. Finally, the effectiveness of our method is illustrated by an intelligent automated guided vehicle system. IEEE

关键词： Discrete event simulation

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