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Prescribed-Time Mitigation of False Data Attacks in Microgrid Load Frequency control

IEEE Transactions on Smart Grid 2025年第4期16卷 3256-3268页

作者： Abouzeid, Said I. Chen, Y. Zaery, Mohamed Amrr, Syed Muhammad Abdelhameed, Esam H. Engineering Technology Research Center for Electric Vehicle Driving System and Safety School of Automation Engineering University of Electronic Science and Technology of China and Sichuan Province Sichuan Chengdu611731 China Aswan University Faculty of Energy Engineering Electrical Engineering Department Aswan Egypt K.A.CARE Energy Research and Innovation Center Saudi Arabia KFUPM Control and Instrumentation Engineering Department Saudi Arabia Saudi Arabia

Microgrid load frequency control (LFC) operation relies extensively on cyber networks which significantly increases their susceptibility to false data injection attacks (FDIAs) that can undermine microgrid’s stability. This paper proposes a multi-layer control framework that efficiently detects and mitigates false data injected in the actuator and measurements of the LFC. Firstly, an FDIAs detection layer based on an unknown input observer (UIO) utilizing an adaptive threshold has been proposed. An adaptive threshold aims to enhance detection sensitivity and reduce false alarms by distinguishing between actual attacks and temporal discrepancies in observer error caused by internal disturbances. Secondly, to ensure timely and accurate mitigation of FDIAs, an estimation layer utilizing a prescribed-time unknown input observer (PTUIO) has been designed. PTUIO is designed to be robust against unknown inputs and parameter uncertainty. The PTUIO employs periodic time-delayed output to estimate system states and FDIAs within a predefined time. Afterward, a two-layer robust and resilient LFC system was developed. The first layer ensures the rejection of unknown inputs, including load/generation disturbances and FDIAs based on PTUIO estimations. The second layer incorporates robust state feedback control, which stabilizes the microgrid and accurately tracks the frequency reference. The effectiveness of the proposed control system is confirmed through multiple scenarios by simulations and Hardware-in-the-loop (HIL), demonstrating its robustness and reliability in addressing challenges associated with internal disturbances, and FDIAs within the microgrid. © 2010-2012 IEEE.

关键词： Hardware-in-the-loop simulation

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Stability and bifurcation analysis of delayed tri-trophic food chain model in poisoned environment with fear effect and additional food

Stability and bifurcation analysis of delayed tri-trophic fo...

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作者： Ramasamy, Sivasamy Banjerdpongchai, David Park, PooGyeon Center of Excellence in Intelligent Control Automation of Process Systems Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Electrical Engineering Pohang University of Science and Technology Pohang Korea Republic of

One of the most important goals of theoretical ecologists is to find a strategy for controlling the chaos in ecological models to maintain healthy ecosystems. We investigate the influence of fear and the supply of additional food to predators in a delayed tri-trophic food chain model, where interference among the species is determined by Holling type-II functional response. The proposed model incorporates the fact that the growth rates of prey and middle predators are decreased due to the fear of middle and special predators, respectively. The additional food is supplied to both predators by either nature or external agencies. Furthermore, the poisoned prey in the predator's environment is taken into account. In the proposed model, we use two time delays: one for the growth term of the middle predator and another for the gestation delay of the special predator. We determine the conditions for the existence of ecologically feasible equilibrium points and their local and global stability. In addition, we establish the conditions for the existence of Hopf bifurcation around interior equilibrium to seek periodic behavior in nondelayed and delayed models. Numerical investigations are performed to justify the proposed theoretical findings through phase portraits, time series of solutions, and bifurcation diagrams. We observe that the chaotic dynamics of a tri-trophic food chain model can be controlled by the proper choice of the fear effect and by supplying additional food parameters. As a result, our findings provide more ecological insights into the dynamics of the delayed tri-trophic food chain model with the fear effect and additional food supply. © 2023 John Wiley & Sons, Ltd.

关键词： Hopf bifurcation

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Methodology for Detecting Non-Technical Energy Losses Using an Ensemble of Machine Learning Algorithms

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Computer Modeling in engineering & Sciences 2025年第5期143卷 1381-1399页

作者： Irbek Morgoev Roman Klyuev Angelika Morgoeva Department of Computer Modeling and Design Automation Faculty of Information Technology and Electronic EngineeringNorth Caucasian Institute of Mining and Metallurgy(State Technological University)Vladikavkaz362021Russia Department of Automation and Control Moscow Polytechnic UniversityMoscow107023Russia

Non-technical losses(NTL)of electric power are a serious problem for electric distribution *** solution determines the cost,stability,reliability,and quality of the supplied *** widespread use of advanced metering infrastructure(AMI)and Smart Grid allows all participants in the distribution grid to store and track electricity *** the research,a machine learning model is developed that allows analyzing and predicting the probability of NTL for each consumer of the distribution grid based on daily electricity consumption *** model is an ensemble meta-algorithm(stacking)that generalizes the algorithms of random forest,LightGBM,and a homogeneous ensemble of artificial neural *** best accuracy of the proposed meta-algorithm in comparison to basic classifiers is experimentally confirmed on the test *** a model,due to good accuracy indicators(ROC-AUC-0.88),can be used as a methodological basis for a decision support system,the purpose of which is to form a sample of suspected NTL *** use of such a sample will allow the top management of electric distribution companies to increase the efficiency of raids by performers,making them targeted and accurate,which should contribute to the fight against NTL and the sustainable development of the electric power industry.

关键词： Non-technical losses smart grid machine learning electricity theft fraud ensemble algorithm hybrid method forecasting classification supervised learning

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Attention Markets of Blockchain-Based Decentralized Autonomous Organizations

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1370-1380页

作者： Juanjuan Li Rui Qin Sangtian Guan Wenwen Ding Fei Lin Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

The attention is a scarce resource in decentralized autonomous organizations(DAOs),as their self-governance relies heavily on the attention-intensive decision-making process of“proposal and voting”.To prevent the negative effects of pro-posers’attention-capturing strategies that contribute to the“tragedy of the commons”and ensure an efficient distribution of attention among multiple proposals,it is necessary to establish a market-driven allocation scheme for DAOs’***,the Harberger tax-based attention markets are designed to facilitate its allocation via continuous and automated trading,where the individualized Harberger tax rate(HTR)determined by the pro-posers’reputation is ***,the Stackelberg game model is formulated in these markets,casting attention to owners in the role of leaders and other competitive proposers as *** equilibrium trading strategies are also discussed to unravel the intricate dynamics of attention ***,utilizing the single-round Stackelberg game as an illustrative example,the existence of Nash equilibrium trading strategies is ***,the impact of individualized HTR on trading strategies is investigated,and results suggest that it has a negative correlation with leaders’self-accessed prices and ownership duration,but its effect on their revenues varies under different *** study is expected to provide valuable insights into leveraging attention resources to improve DAOs’governance and decision-making process.

关键词： Attention decentralized autonomous organizations Harberger tax Stackelberg game.

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A Multi-party Asymmetric Self-play Algorithm and Its Application in Multi-USV Adversarial Game Simulations 24

A Multi-party Asymmetric Self-play Algorithm and Its Applica...

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2024 International Conference on Machine Learning, Pattern Recognition and automation engineering, MLPRAE 2024

作者： Rao, Jinjun Wang, Cong Liu, Mei Lei, Jingtao Giernacki, Wojciech Department of Precision Mechanical Engineering School of Mechatronic Engineering and Automation Shanghai University China Institute of Robotics and Machine Intelligence Faculty of Automatic Control Robotics and Electrical Engineering Poznan University of Technology Poland

ISBN: (纸本)9798400709876

Aiming at the problem that the combination of self-play (SP) and deep reinforcement learning (DRL) only involves two-party games and the policy learning of each party is limited, a multi-party asymmetric self-play algorithm (MASP) is proposed. Firstly, by improving the ELO scoring system, the ELO scoring takes into account each party of the unmanned surface vehicle (USV) clusters, and the imbalance of the number of USV clusters, so that the frequency of exchanging strategies of all USV clusters in the confrontation process is equal. Secondly, it ensures that USV clusters have a balanced combat ability, and at the same time ensures that the combat ability of all parties is strong and weak and the gap is not too wide. In addition, the parameters are dynamically set to reduce the update frequency of the policy of the stronger party. The experimental results show that the MASP can make the USV clusters learn more effective policies, have a shorter game time, and obtain higher rewards and ELO scores in the simple 2v2 adversarial game scenario and the three-party game scenario of a warship escort mission. © 2024 ACM.

关键词： Deep reinforcement learning

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Target Capturing in an Ellipsoidal Region for a Swarm of Double Integrator Agents

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 801-811页

作者： Antonio Bono Luigi D'Alfonso Giuseppe Fedele Veysel Gazi IEEE Department of Informatics ModelingElectronics and Systems EngineeringUniversity of CalabriaRende 87036Italy Dept.Electrical and Electronics Eng. Faculty of EngineeringMarmara UniversityIstanbul 34722 Department of Control and Automation Engineering Faculty of Electrical and Electronics EngineeringYildiz Technical UniversityEsenler 34220Turkey

In this paper we focus on the target capturing problem for a swarm of agents modelled as double integrators in any finite space *** agent knows the relative position of the target and has only an estimation of its velocity and *** that the estimation errors are bounded by some known values,it is possible to design a control law that ensures that agents enter a user-defined ellipsoidal ring around the moving *** know the relative position of the other members whose distance is smaller than a common detection ***,in the case of no uncertainty about target data and homogeneous agents,we show how the swarm can reach a static configuration around the moving *** simulations are reported to show the effectiveness of the proposed strategy.

关键词： Agents-based systems cooperative control swarms target-capturing

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Event-Triggered Moving Block Train Platooning Scheme Under Communication Loss Constraint 4

Event-Triggered Moving Block Train Platooning Scheme Under C...

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4th International Conference on Robotics, automation, and Artificial Intelligence, RAAI 2024

作者： Chandra, Jonathan Tamba, Tua A. Christian, Raymond Parahyangan Catholic University Center for Control Automation and Systems Engineering Faculty of Engineering Technology Dept. of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798331520038

This paper addresses the challenges of efficient coordination and safety assurance of moving block train platooning system. Conventional railway signaling method which relies on static block systems often fail to adapt to high frequency scenarios and thereby limiting the railway system's operational flexibility and scalability. The moving block signaling approach through communication-based train control (CBTC) technology has recently been proposed and viewed as a potential solution alternative to address such limitations. To enhance railway system opearational performance and safety, this paper proposes a control strategy combining sliding mode control (SMC) and event-triggered control (ETC) for a multi-agent system representation of train convoy operating under moving block signaling scheme. The proposed SMC is used to ensure robust tracking and coordination of the train convoy in the presence of inter-train communication loss, while ETC scheme is used to minimize communication and computation overhead in each train by updating the individual train's control actions only when deemed necessary. The proposed approach improves coordination, safety, and resource efficiency within complex, multi-agent train systems. Simulation results demonstrate the effectiveness of the combined control strategy in maintaining inter-train spacing even when data transmission loss/drop occur on several time instances. © 2024 IEEE.

关键词： CBTC event triggering multi-agent system sliding mode control Train control

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Stable and Safe Navigation Scheme for Mobile Robots Under Moving Obstacle Presence 4

Stable and Safe Navigation Scheme for Mobile Robots Under Mo...

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4th International Conference on Robotics, automation, and Artificial Intelligence, RAAI 2024

作者： Gunarso, Michael A. Tamba, Tua A. Faculty of Engineering Technology Parahyangan Catholic University Center for Control Automation and Systems Engineering Dept. of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798331520038

This paper reports a controller design methodology for a differential drive wheeled mobile robot (DDWMR) model which considers both safety and stability properties of the robot's operation. The proposed methodology first constructs a stabilizing controller using control Lyapunov Function (CLF) concept and then generates a polynomial function-type reference trajectory to seamlessly connect the initial and final poses of the DDWMR. Subsequently, a control Barrier Function (CBF) based scheme is used to ensure the safety of the DDWMR movement in avoiding moving obstacles while driving on the constructed reference trajectory. By the proposed CLF-CBF integration, the proposed approach offers an efficient solution for autonomous navigation of DDWMR in the presence of moving obstacles while also addresses the challenges posed by its nonholonomic constraint. The effectiveness of the proposed approach is shown through simulations which demonstrate the robot's ability to perform safe and stable collision-free movement and navigation. © 2024 IEEE.

关键词： control Barrier function control Lyapunov function DDWMR moving obstacle Path planning

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PSMFNet:Lightweight Partial Separation and Multiscale Fusion Network for Image Super-Resolution

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Computers, Materials & Continua 2024年第10期81卷 1491-1509页

作者： Shuai Cao Jianan Liang Yongjun Cao Jinglun Huang Zhishu Yang Institute of Intelligent Manufacturing GDASGuangdong Key Laboratory of Modern Control TechnologyGuangzhou510030China School of Mechanical&Automotive Engineering South China University of TechnologyGuangzhou511442China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China School of Faculty of Intelligent Manufacturing Wuyi UniversityJiangmen529020China

The employment of deep convolutional neural networks has recently contributed to significant progress in single image super-resolution(SISR)***,the high computational demands of most SR techniques hinder their applicability to edge devices,despite their satisfactory reconstruction *** methods commonly use standard convolutions,which increase the convolutional operation cost of the *** this paper,a lightweight Partial Separation and Multiscale Fusion Network(PSMFNet)is proposed to alleviate this ***,this paper introduces partial convolution(PConv),which reduces the redundant convolution operations throughout the model by separating some of the features of an image while retaining features useful for image ***,it is worth noting that the existing methods have not fully utilized the rich feature information,leading to information loss,which reduces the ability to learn feature *** by self-attention,this paper develops a multiscale feature fusion block(MFFB),which can better utilize the non-local features of an *** can learn long-range dependencies from the spatial dimension and extract features from the channel dimension,thereby obtaining more comprehensive and rich feature *** the role of the MFFB is to capture rich global features,this paper further introduces an efficient inverted residual block(EIRB)to supplement the local feature extraction ability of PSMFNet.A comprehensive analysis of the experimental results shows that PSMFNet maintains a better performance with fewer parameters than the state-of-the-art models.

关键词： Deep learning single image super-resolution lightweight network multiscale fusion

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Polyphonic sound event localization and detection based on Multiple Attention Fusion ResNet

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Mathematical Biosciences and engineering 2024年第2期21卷 2004-2023页

作者： Zhang, Shouming Zhang, Yaling Liao, Yixiao Pang, Kunkun Wan, Zhiyong Zhou, Songbin Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Institute of Intelligent Manufacturing Guangdong Academy of Science Guangdong Key Laboratory of Modern Control Technology Guangzhou510030 China

Sound event localization and detection have been applied in various fields. Due to the polyphony and noise interference, it becomes challenging to accurately predict the sound event and their occurrence locations. Aiming at this problem, we propose a Multiple Attention Fusion ResNet, which uses ResNet34 as the base network. Given the situation that the sound duration is not fixed, and there are multiple polyphonic and noise, we introduce the Gated Channel Transform to enhance the residual basic block. This enables the model to capture contextual information, evaluate channel weights, and reduce the interference caused by polyphony and noise. Furthermore, Split Attention is introduced to the model for capturing cross-channel information, which enhances the ability to distinguish the polyphony. Finally, Coordinate Attention is introduced to the model so that the model can focus on both the channel information and spatial location information of sound events. Experiments were conducted on two different datasets, TAU-NIGENS Spatial Sound Events 2020, and TAU-NIGENS Spatial Sound Events 2021. The results demonstrate that the proposed model significantly outperforms state-of-the-art methods under multiple polyphonic and noise-directional interference environments and it achieves competitive performance under a single polyphonic environment. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License.

关键词： Deep learning

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