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Correction To: Photovoltaic system fault detection techniques: a review

Neural Computing and Applications 2024年第29期36卷 18547-18548页

作者： El-Banby, Ghada M. Moawad, Nada M. Abouzalm, Belal A. Abouzaid, Wessam F. Ramadan, E. A. Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf Egypt Department of Electrical Engineering of Computer and Control Systems Faculty of Engineering Kafrelsheikh University Kafrelsheikh Egypt

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Fuzzy Set-Membership Filtering for Discrete-Time Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2022年第6期9卷 1026-1036页

作者： Jingyang Mao Xiangyu Meng Derui Ding Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China Division of Electrical and Computer Engineering Louisiana State UniversityBaton RougeLA70803 USA IEEE School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia

In this article,the problem of state estimation is addressed for discrete-time nonlinear systems subject to additive unknown-but-bounded noises by using fuzzy set-membership ***,an improved T-S fuzzy model is introduced to achieve highly accurate approximation via an affine model under each fuzzy ***,compared to traditional prediction-based ones,two types of fuzzy set-membership filters are proposed to effectively improve filtering performance,where the structure of both filters consists of two parts:prediction and *** the locally Lipschitz continuous condition of membership functions,unknown membership values in the estimation error system can be treated as multiplicative noises with respect to the estimation ***-time recursive algorithms are given to find the minimal ellipsoid containing the true ***,the proposed optimization approaches are validated via numerical simulations of a one-dimensional and a three-dimensional discrete-time nonlinear systems.

关键词： Affine model membership functions set-membership filtering stability Takagi-Sugeno fuzzy modeling

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Constructive Function Approximation with Local Models

Constructive Function Approximation with Local Models

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Mediterranean Conference on control and Automation (MED)

作者： Christos N. Mavridis Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm

ISBN: (数字)9798350395440

ISBN: (纸本)9798350395457

We introduce a constructive function approximation approach as a general tool, particularly useful in adaptive and data-driven methods for perception and control. The key idea is to estimate of a collection of simple local models as opposed to a single and complex regression model trained in the entire input space. We use principles from the Online Deterministic Annealing (ODA) optimization framework to construct an adaptive partition of the input space, which enables the introduction of local function approximation models within each subset of the partition. We show that both the partitioning and the local model training algorithms are stochastic approximation algorithms that operate online, and with the same observations, as part of a two-timescale stochastic approximation scheme. This process constitutes a heuristic method to gradually increase the complexity of the function approximation framework in a task-agnostic manner, giving emphasis to regions of the input space where the regression error is high. As a result this framework has inherent explainability properties, and is suitable for continuous learning applications where regression improvement without retraining from scratch is crucial. Simulation results illustrate the properties of the proposed approach.

关键词： Training Adaptation models Simulation Stochastic processes Aerospace electronics Approximation algorithms Partitioning algorithms

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Event-triggered control of nonlinear systems under deception and Denial-of-Service attacks

Event-triggered control of nonlinear systems under deception...

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IEEE Conference on Decision and control

作者： Ruslan Seifullaev André M. H. Teixeira Anders Ahlén Department of Information Technology Division of Systems and Control Uppsala University Sweden Department of Electrical Engineering Division of Signals and Systems Uppsala University Sweden

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

We address the problem of event-triggered networked control of nonlinear systems under simultaneous deception and Denial-of-Service (DoS) attacks. By DoS attacks, we refer to disruptions in the communication channel that prevent sensor measurements from reaching the controller. When the system undergoes a deception attack, the controller receives a modified output, deviating from the sensor’s original measurement. We implement the input delay approach and the Lyapunov-Krasovskii technique to obtain sufficient conditions, expressed in terms of linear matrix inequalities (LMIs), that characterize the duration of the DoS interruptions under which input-to-state stability (ISS) of the closed-loop system is preserved. Furthermore, we explore scenarios involving simultaneous attacks, where the DoS is modeled as a stochastic Bernoulli process. The closed-loop system is then considered as a stochastic impulsive system. In a similar manner, we derive conditions to ensure mean-square ISS for this case. A numerical example illustrates the efficiency of the results.

关键词： Event detection Stochastic processes Denial-of-service attack Stability analysis Linear matrix inequalities Delays Trajectory Closed loop systems Nonlinear systems Numerical stability

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Maximizing social power in multiple independent Friedkin-Johnsen models

Maximizing social power in multiple independent Friedkin-Joh...

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European control Conference (ECC)

作者： Lingfei Wang Yu Xing Claudio Altafini Karl H. Johansson Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical Engineering Division of Automatic Control Linköping University Linköping Sweden

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper investigates the problem of maximizing social power for a group of agents, who participate in multiple meetings described by independent Friedkin-Johnsen models. A strategic game is obtained, in which the action of each agent (or player) is her stubbornness over all the meetings, and the payoff is her social power on average. It is proved that, for all but some strategy profiles on the boundary of the feasible action set, each agent's best response is the solution of a convex optimization problem. Furthermore, even with the non-convexity on boundary profiles, if the underlying networks are given by a fixed complete graph, the game has a unique Nash equilibrium. For this case, the best response of each agent is analytically characterized, and is achieved in finite time by a proposed algorithm.

关键词： Network topology Europe Games Nash equilibrium Cost function Convex functions

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Simulation of Arc Erosion on the Main Contact of On-Load Tap Changer 4th

Simulation of Arc Erosion on the Main Contact of On-Load Tap...

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4th International Symposium on Insulation and Discharge Computation for Power Equipment, IDCOMPU 2023

作者： Zhou, Yuanxiang Dai, Yasong Chen, Jianning Li, Yuhang Hou, Xuzhao Zhang, Zhen State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China The Wind Solar Storage Division of State Key Laboratory of Power System and Generation Equipment School of Electrical Engineering Xinjiang University Urumqi830047 China

ISBN: (纸本)9789819974047

Long-term operation and switching of transformer on-load tap-changers can cause degradation and deterioration of the main contact material, even leading to contact arcing damage in severe cases. However, the arcing mechanism of the main contact during the switching has not been clarified yet. A magneto-hydrodynamic simulation method of main contact arcing has been proposed. The geometry of the main contact in transformer oil is simplified, and the simulation model of the arc temperature field of the main contact in transformer oil coupled with electric, magnetic, thermal and fluid fields is proposed. The dynamic evolution of the arc temperature has been investigated at peak currents of 2100 A, 1500 A, 600 A and 300 A, respectively. The results show that with the increase of the spacing between contacts, the temperature at arc core rises rapidly and then decreases slowly, and the temperature can reach 50177 K at 2100A. Due to the electron bombardment at the anode surface, the temperature at anode surface is higher than that at cathode surface under different chopped currents. The highest temperatures at anode and cathode surface can reach 4142.5 K and 4081.7 K respectively. © Beijing Paike Culture Commu. Co., Ltd 2024.

关键词： Deterioration

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State Estimation for Integrated Energy systems: Motivations, Advances, and Future Work

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IEEE Transactions on Power systems 2024年第4期40卷 3057-3073页

作者： Zhao, Junbo Srivastava, Ankur Guo, Ye Cetenovic, Dragan Lin, Yuzhang Levi, Victor Yin, Guanxiong Huang, Manyun Zhang, Tingting Li, Zhigang Chen, Yanbo Exposito, Antonio G. Zhang, Wen Zheng, Weiye Chakrabarti, Saikat Li, Yang Sharma, Ankush Kamwa, Innocent Guo, Qinglai Terzija, Vladimir Mili, Lamine University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Tsinghua University Tsinghua-Berkeley Shenzhen Institute Shenzhen518055 China The University of Manchester Department of Eee ManchesterM13 9PL United Kingdom University of Kragujevac Faculty of Technical Sciences Čačak Čačak32000 Serbia New York University Department of Electrical and Computer Engineering NY11201 United States Tsinghua University Department of Electrical Engineering Beijing100084 China Hohai University College of Energy and Electrical Engineering Nanjing210098 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250061 China The Chinese University of Hong Kong-Shenzhen School of Science and Engineering Shenzhen518172 China North China Electric Power University School of Electrical and Electronic Engineering Beijing102206 China University of Sevilla Spain Sevilla41092 Spain South China University of Technology School of Electrical Power Engineering Guangzhou510641 China Indian Institute of Technology Kanpur Department of Electrical Engineering Kanpur208016 India Northeast Electric Power University School of Electrical Engineering Jilin132012 China Laval University Department of Electrical and Computer Engineering QuebecQCG1V 0A6 Canada Tsinghua University State Key Laboratory of Power Systems Department of Electrical Engineering Beijing100084 China Newcastle University School of Engineering Newcastle upon TyneNE1 7RU United Kingdom Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering Falls ChurchVA22043 United States

This paper summarizes the technical activities of a three-year-long IEEE Task Force (TF) on State Estimation (SE) for Integrated Energy systems (IES). It presents the formal definition and characteristics of IES, along with the comprehensive discussion on Electric Power systems (EPS) model, and static and dynamic models associated with heating and natural gas systems. The paper also identifies the barriers of SE for IES, such as estimation modeling, observability analysis, and measurement requirements, together with addressing multi-scale dynamics. An extensive comparative analysis between Integrated Energy systems-State Estimation (IES-SE) and more established Electric Power System-State Estimation (EPS-SE) is presented. The paper also provides future research needs and directions related to IES-SE. © 1969-2012 IEEE.

关键词： Power system analysis

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A LESO Based Backstepping controller Considering Coal Seam Hardness for Rotary Speed in Coal Mine Tunnel Drilling Process

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Journal of systems Science & Complexity 2024年第5期37卷 1789-1808页

作者： CHEN Luefeng LIU Xiao WU Min LU Chengda PEDRYCZ Witold HIROTA Kaoru School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R2G7Canada The Tokyo Institute of Technology Yokohama 226-8502Japan

In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of *** this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary ***,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is *** an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam *** on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary ***,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.

关键词： Backstepping extended state observer hydraulic tunnel drilling machine rotary speed

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Predicting Learning Interactions in Social Learning Networks: A Deep Learning Enabled Approach

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IEEE/ACM Transactions on Networking 2023年第5期31卷 2086-2100页

作者： Sahay, Rajeev Nicoll, Serena Zhang, Minjun Yang, Tsung-Yen Joe-Wong, Carlee Douglas, Kerrie A. Brinton, Christopher G. Elmore Family School of Electrical and Computer Engineering Purdue University West LafayetteIN47907 United States Autonomy and Underwater Systems Division Saab Inc West LafayetteIN47907 United States STR WoburnMA01801 United States GoForward Inc. San FransiscoCA94104 United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ08544 United States Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States School of Engineering Education Purdue University West LafayetteIN47907 United States

We consider the problem of predicting link formation in Social Learning Networks (SLN), a type of social network that forms when people learn from one another through structured interactions. While link prediction has been studied for general types of social networks, the evolution of SLNs over their lifetimes coupled with their dependence on which topics are being discussed presents new challenges for this type of network. To address these challenges, we develop a series of autonomous link prediction methodologies that utilize spatial and time-evolving network architectures to pass network state between space and time periods, and that models over three types of SLN features updated in each period: neighborhood-based (e.g., resource allocation), path-based (e.g., shortest path), and post-based (e.g., topic similarity). Through evaluation on six real-world datasets from Massive Open Online Course (MOOC) discussion forums and from Purdue University, we find that our method obtains substantial improvements over Bayesian models, linear classifiers, and graph neural networks, with AUCs typically above 0.91 and reaching 0.99 depending on the dataset. Our feature importance analysis shows that while neighborhood and path-based features contribute the most to the results, post-based features add additional information that may not always be relevant for link prediction. The code and four of the datasets used in this work are available at https://***/Jess-jpg-txt/sln-learning. © 2023 IEEE.

关键词： Social networking (online)

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Neuromimetic Dynamic Networks with Hebbian Learning

Neuromimetic Dynamic Networks with Hebbian Learning

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American control Conference (ACC)

作者： Zexin Sun John Baillieul Division of Systems Engineering Boston University Boston MA Department of Mechanical Engineering Electrical and Computer Engineering Division of Systems Engineering at Boston University Boston MA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Continuing work on what we have called neuromimetic control system designs is reported. The focus here is on control system models in which the dynamics of networks of neuron-like states are governed by hybrid con-tinuous/discrete, linear/nonlinear models. The models studied support Hebbian-like learning of network structure, and formal analysis grounded in graph theory and classical control allows us to prove that the biological model exhibits boundedness, stability, and structural controllability. The results make contact with previous results involving sym-cactus graphs. Simulations using a 14-node generalized sym-cactus network with two input types validate the model's effectiveness in capturing key neural dynamics.

关键词： Analytical models Biological system modeling controllability Stability analysis Graph theory Hebbian theory

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