IEEE Transactions on Industrial Cyber-Physical Systems最新文献

Digital Twin-Based Framework for Dynamic Stability Analysis of Grid-Tied Photovoltaic System 并网光伏系统动态稳定性分析的数字双元框架

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-10-03 DOI: 10.1109/TICPS.2025.3617450

Keshav Dutt;Nishant Kumar

{"title":"Digital Twin-Based Framework for Dynamic Stability Analysis of Grid-Tied Photovoltaic System","authors":"Keshav Dutt;Nishant Kumar","doi":"10.1109/TICPS.2025.3617450","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3617450","url":null,"abstract":"This paper presents a Digital Twin (DT) framework for real-time stability assessment of grid-tied photovoltaic (PV) systems under varying operating conditions. The proposed DT operates in parallel with the physical hardware, serving as a high-fidelity mathematical model that continuously synchronizes with sensor measurements from the actual system to support control and monitoring. A Rank-based Adaptive Artificial Electric Field Optimization (RAAEFO) algorithm is employed to update DT parameters, ensuring accurate alignment with hardware behavior. For system control, an Adaptive Robust Cascaded Second-Order Generalized Integrator (AR-CSOGI) based Unit Vector Integrated Chattering-Free Enhanced Sliding Mode Controller (UVI-CFESMC) is developed to achieve precise current tracking and robust performance under disturbances. The framework is implemented using an OPAL-RT (OP4512) platform for the DT and an NI sbRIO-9636 FPGA for the hardware prototype. Experimental evaluations under scenarios including voltage sag and solar irradiance variations demonstrate that the DT reliably monitors system performance and predicts stability margins. Stability assessment is performed using Lyapunov theory, incorporating both controller and system stability indicators. Results confirm that the proposed DT framework improves monitoring accuracy and ensures stable operation across dynamic conditions.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"559-566"},"PeriodicalIF":0.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145352039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Brain-Like Distributed Two-Layer SoC Balancing Control of Cyber-Physical Microgrid Clusters 类脑分布式两层SoC平衡控制的网络物理微电网集群

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-10-03 DOI: 10.1109/TICPS.2025.3617446

Tao Yang;Jingang Lai

{"title":"Brain-Like Distributed Two-Layer SoC Balancing Control of Cyber-Physical Microgrid Clusters","authors":"Tao Yang;Jingang Lai","doi":"10.1109/TICPS.2025.3617446","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3617446","url":null,"abstract":"As a typical cyber-physical system (CPS), AC microgrid (MG) clusters have attracted widespread attention due to the advantages such as high reliability, flexible scalability, and collaborative mutual support. A two-layer distributed SoC balancing control strategy is proposed for cyber-physical MG clusters containing multiple battery energy storage systems (BESSs). The strategy based on brain-like intelligence (BLI), aims to regulate the output voltage and frequency of all BESSs in each MG to their reference values, while also enabling active power sharing and state of charge (SoC) level balancing. The BLI controller, which is model-free, can swiftly learn and manage the complexities, nonlinearities, and uncertainties inherent in the MG model. The asymptotic convergence condition for the internal stability of the BLI controller has been established. Furthermore, a sparse two-layer communication network is created by connecting one or more BESSs from each MG in the lower network to form an upper network, and the secondary and tertiary response matching conditions for the closed-loop MG clusters are derived. Finally, the effectiveness and robustness of the proposed strategy is validated through multiple real-time simulation cases of the modified IEEE 34-bus system by using OPAL-RT.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"567-576"},"PeriodicalIF":0.0,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Framework for Distributed Personalized Optimization in Cyber-Physical Systems via Multi-Parameter Fractional Dynamics 基于多参数分数动力学的信息物理系统分布式个性化优化框架

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-09-29 DOI: 10.1109/TICPS.2025.3615894

Xintong Ni;Yiheng Wei;Meng Tao;Liang Hua;Jinde Cao

引用次数: 0

Teleoperated Cyber-Physical System for Cable-Driven Hyper-Redundant Flexible Manipulation 电缆驱动超冗余柔性操作的远程操作信息物理系统

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-09-26 DOI: 10.1109/TICPS.2025.3614603

Yunxuan Ma;Xiaojun Zhu;Haolin Fei;Yiyang He;Xueqian Wang;Yu Liu

{"title":"Teleoperated Cyber-Physical System for Cable-Driven Hyper-Redundant Flexible Manipulation","authors":"Yunxuan Ma;Xiaojun Zhu;Haolin Fei;Yiyang He;Xueqian Wang;Yu Liu","doi":"10.1109/TICPS.2025.3614603","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3614603","url":null,"abstract":"Increased space missions rely on ground-based cyber-physical systems (CPS) to facilitate remote interventions during satellite anomalies. When solar panel deployment failures occur, integrating real-time sensing, computation, and precise robotic control becomes essential for recovery operations. To this end, this paper introduces a cable-driven hyper-redundant flexible manipulator (CHFM) for teleoperated intervention through ground control. To achieve continuous configuration control of the CHFM in constrained environments, we propose a novel planning approach to facilitate end-arm synchronization. Based on this planning strategy, a comprehensive teleoperation CPS architecture is developed, integrating operating, computing and processing, visualization, safety detection, and network modules. Experimental results demonstrate the system’s ability to navigate through narrow satellite panel slits, verifying both the system’s operational reliability and the effectiveness of the proposed planning method. The results indicate significant improvements in the accuracy of task completion for complex remote manipulation.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"588-596"},"PeriodicalIF":0.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145352041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Accelerated Attentive Deep Learning-Based Approach to Early Detect Attacks in Cyber-Physical Microgrids 基于加速细心深度学习的网络物理微电网攻击早期检测新方法

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-09-25 DOI: 10.1109/TICPS.2025.3614597

Ahmad M. Abu Nassar;Walid G. Morsi

{"title":"A New Accelerated Attentive Deep Learning-Based Approach to Early Detect Attacks in Cyber-Physical Microgrids","authors":"Ahmad M. Abu Nassar;Walid G. Morsi","doi":"10.1109/TICPS.2025.3614597","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3614597","url":null,"abstract":"The integration of renewable energy resources (RERs) and electric vehicles (EVs) into microgrids enables the provision of ancillary services for frequency and voltage regulation, thus improving the stability and efficiency. However, such integration requires a set of communication networks to exchange information among the microgrid components, which makes the microgrid assets prone to cyber vulnerability threats. Unlike in previous work, in which existing approaches wait until the impacts appear on the system to be able to detect the attacks, this paper introduces a new approach that combines the opening image technique and attentive deep learning to early detect the cyberattacks applied to a cyber-physical microgrid embedded with RERs and EVs. Furthermore, this paper investigated the effect of smart meters’ data granularity on the attack detection accuracy. The results have shown that the use of a high time resolution of 1-sec increases the detection accuracy reaching 99.91%. The training process of the proposed approach has been accelerated using Graphics Processing Unit (GPU), which demonstrated low computational time by significantly reducing both the training and testing time by 93% and 70% respectively.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"537-548"},"PeriodicalIF":0.0,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145351995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Reconstruction-Based Resilient MPC for Industrial Cyber-Physical Systems Under Deception Attacks 欺骗攻击下基于鲁棒重建的工业网络物理系统弹性MPC

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-09-24 DOI: 10.1109/TICPS.2025.3614157

Ning He;Dangtong He;Yuxiang Li

引用次数: 0

Towards a Supervised Topic Model Based on Searching of Semantic Center of Mass 基于语义质心搜索的监督主题模型研究

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-08-25 DOI: 10.1109/TICPS.2025.3602430

Gangli Liu;Yi Dai;Ling Feng

引用次数: 0

Augmenting Decision-Making of Human-in-the-Loop Operators for Resilient Cyber-Power Systems 弹性网络电力系统中人在环算子的增强决策

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-08-11 DOI: 10.1109/TICPS.2025.3597906

Hussain M. Mustafa;Niloy Patari;Sagnik Basumallik;Anurag K. Srivastava

{"title":"Augmenting Decision-Making of Human-in-the-Loop Operators for Resilient Cyber-Power Systems","authors":"Hussain M. Mustafa;Niloy Patari;Sagnik Basumallik;Anurag K. Srivastava","doi":"10.1109/TICPS.2025.3597906","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3597906","url":null,"abstract":"Human operators in Industrial Cyber-Physical Systems (ICPS), such as electric power systems, are responsible for critical, real-time decision-making in control centers. They often rely on Decision Support Tools (DSTs), but multi-modal feedback can lead to cognitive and information overload, especially during extreme events. As human involvement increases, ICPS are evolving into Cyber-Physical Human Systems (CPHS) and Cyber-Physical Social Systems (CPSS), where human cognition and machine intelligence are tightly integrated. This work investigates human-machine cooperation using the Cyber-Physical Transmission Resiliency Assessment Metric (CP-TRAM), a DST that integrates physical and cyber alerts to support collaborative decision-making. We developed a laboratory-based human-in-the-loop setup simulating a power grid control room, where CP-TRAM and the Cyber-Power Alarm Tool visualize real-time alarms due to physical and cyber events. An industry-grade operator training software, PowerSimulator, is used to create training scenarios on a synthetic model of Washington state’s power system-the Cascadia Network. This model is connected to a hardware-in-the-loop (HIL) testbed, forming a combined hardware, software, and human-integrated environment for training and evaluation. To assess effectiveness, we simulate a cyber-induced physical event based on the MITRE ATT&CK ICS framework and compare operator performance with and without these tools. The study includes 40 participants—18 professional operators and 22 students. We use eye-tracking based metrics to compute a cognitive overload score, validating how CP-TRAM enhances detection and response to cyber events. Results show improved speed and accuracy of decision-making, confirming the DST’s effectiveness under high-stress conditions.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"525-536"},"PeriodicalIF":0.0,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-Threshold Denoising Convolutional Transformers for Machining Process Monitoring in Cyber-Physical Manufacturing Systems 基于双阈值去噪卷积变压器的信息物理制造系统加工过程监控

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-07-31 DOI: 10.1109/TICPS.2025.3594641

Yuxin Sun;Yadong Xu;Leping Zhang;Chao Liu;Haifeng Ma;Zhenhua Xiong

{"title":"Dual-Threshold Denoising Convolutional Transformers for Machining Process Monitoring in Cyber-Physical Manufacturing Systems","authors":"Yuxin Sun;Yadong Xu;Leping Zhang;Chao Liu;Haifeng Ma;Zhenhua Xiong","doi":"10.1109/TICPS.2025.3594641","DOIUrl":"https://doi.org/10.1109/TICPS.2025.3594641","url":null,"abstract":"Chatter can severely degrade machining quality, shorten tool life, and reduce productivity, making its effective detection critical for precision and stability in cyber-physical manufacturing. Existing detection methods often struggle with significant noise from dynamic disturbances in real-world environments, limiting their industrial applicability. To address this issue, we propose a dual-threshold denoising convolutional transformer for robust online chatter detection in complex machining processes. Firstly, a dual-threshold denoising module utilizing two threshold functions effectively extracts features while adaptively purifying signals even under noisy conditions. Following noise suppression, a multi-scale convolution module enhanced with a receptive field block captures discriminative features across varied spatial scales and heterogeneous receptive fields. A channel recalibration module then optimizes feature channels through attention mechanisms. Finally, a bidirectional conformer module adeptly captures both forward and backward temporal dependencies. Experimental results demonstrate that our method achieves an average accuracy of 91.60% while maintaining robust performance even under severely noisy conditions (SNR = −6 dB), thereby underscoring its superior efficacy and practical viability in industrial applications.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"3 ","pages":"507-514"},"PeriodicalIF":0.0,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144880547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IEEE Transactions on Industrial Cyber-Physical Systems Publication Information IEEE工业信息物理系统学报

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2025-07-18 DOI: 10.1109/TICPS.2025.3590506

引用次数: 0