IEEE Transactions on Industrial Cyber-Physical Systems最新文献_第2页

FAVLG: A Lightweight Language-Driven Grasping Model for Networked ICPS via Parameter-Efficient Edge Execution 基于参数高效边缘执行的网络化ICPS轻量级语言驱动抓取模型

IF 7.4

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-09-09 DOI: 10.1109/TICPS.2026.3732649

Jiangtao Xu;Haitao Xu;Tao Xue;Tao Zhang

{"title":"FAVLG: A Lightweight Language-Driven Grasping Model for Networked ICPS via Parameter-Efficient Edge Execution","authors":"Jiangtao Xu;Haitao Xu;Tao Xue;Tao Zhang","doi":"10.1109/TICPS.2026.3732649","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3732649","url":null,"abstract":"In Industrial Cyber-Physical Systems (ICPS), deploying Embodied AI for language-driven robotic grasping holds immense potential. However, relying on cloud -based heavy Vision-Language Models (VLMs) imposes severe bandwidth and latency burdens on industrial communication networks, often violating strict Quality of Service (QoS) constraints for real-time perception-action loops. To bridge the gap between robotics and communications through low-latency local edge execution, this paper proposes FAVLG, a lightweight end-to-end grasp detection framework tailored for local edge deployment. Built upon the MobileCLIP backbone, the framework introduces a vision-language joint adaptation strategy for parameter-efficient fine-tuning. This strategy effectively bridges the domain gap and achieves explicit visual-textual interaction at the early stages of feature extraction. Consequently, our method eliminates the reliance on computationally intensive late-stage cross-modal fusion modules, substantially reducing computational overhead and enabling local edge deployment without heavy cloud network dependency. Furthermore, an attention module with grid topology priors is proposed to guide the model toward fine-grained focus and geometric edge refinement on critical grasping regions. Extensive experiments on the Grasp-Anything++ and OCID-VLG datasets demonstrate that FAVLG achieves highly competitive grasping performance while updating only 0.45% of the backbone parameters. Real-world robotic experiments further validate its feasibility, demonstrating its practical potential for low-latency and responsive local execution in networked ICPS.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"963-973"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130720","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

Intelligent Data-Driven Digital Twin for Predictive Health Monitoring of 3-Phase Grid-Connected PV Systems 面向三相并网光伏系统健康预测监测的智能数据驱动数字孪生

IF 7.4

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-09-14 DOI: 10.1109/TICPS.2026.3733868

Rituvic Pandey;Nishant Kumar

{"title":"Intelligent Data-Driven Digital Twin for Predictive Health Monitoring of 3-Phase Grid-Connected PV Systems","authors":"Rituvic Pandey;Nishant Kumar","doi":"10.1109/TICPS.2026.3733868","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3733868","url":null,"abstract":"Grid-connected photovoltaic (PV) inverters are increasingly exposed to dynamic irradiance variations, distorted grid voltages, and progressive passive-component degradation, which can reduce power quality, increase losses, and compromise long-term reliability. Conventional physics-based digital twins require detailed analytical models and continuous synchronization with the physical system, while many diagnostic methods remain offline or depend strongly on predefined component models. To address these limitations, this paper proposes a data-driven Digital Twin (DD-DT) framework for state estimation, internal parameter identification, and predictive health monitoring of a single-stage three-phase grid-connected PV inverter. A Cascaded Second- and Third-Order Generalized Integrator-Noise Suppression Block-Compact Generalized Integrator (CSTOGI-NSB-CGI) is used for robust voltage-template extraction under distorted grid conditions. An Echo State Network (ESN) is then employed as a reservoir-computing surrogate to learn nonlinear temporal relationships between measurable signals and hidden internal electrical states. The reconstructed states are further used to estimate critical component parameters, including interfacing inductance, capacitance, equivalent series resistance, and switch on-state resistance. Experimental validation under progressive interfacing-inductor and DC-link-capacitor degradation confirms close agreement between hardware and DD-DT responses, with relative prediction errors maintained within 3%, an overall average <inline-formula><tex-math>$text{NRMSE}$</tex-math></inline-formula> of 5.57%, and an average <inline-formula><tex-math>$R^{2}$</tex-math></inline-formula> of 0.876 across the reported test cases. The developed framework provides a scalable and computationally efficient basis for predictive maintenance of grid-connected PV inverter systems within Industrial Cyber-Physical Systems (ICPS).","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"1006-1015"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130704","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 Bayesian Game-Theoretic Framework for False Data Injection in Cyber-Physical Systems 网络物理系统中假数据注入的贝叶斯博弈论框架

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-03-25 DOI: 10.1109/TICPS.2026.3696598

Valeria Bonagura;Leonardo Badia;Chiara Foglietta;Federica Pascucci;Stefano Panzieri

{"title":"A Bayesian Game-Theoretic Framework for False Data Injection in Cyber-Physical Systems","authors":"Valeria Bonagura;Leonardo Badia;Chiara Foglietta;Federica Pascucci;Stefano Panzieri","doi":"10.1109/TICPS.2026.3696598","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3696598","url":null,"abstract":"We use Bayesian game theory to model the strategic interplay of a transmitter in a cyber-physical system (CPS) that is under false data injection (FDI) by a malicious agent, whose characteristics are partially known. The transmitter aims to minimize age of incorrect information (AoII), whereas the malicious agent seeks to maximize it. The uncertain representation of the transmission costs of the malicious agent complicates the equilibrium. Existing studies on false data injection in CPS largely assume complete knowledge of the adversary or concentrate on detection mechanisms. However, the problem of how incomplete information affects information timeliness—measured by the AoII—remains unresolved. We show how the attack can be effectively contained by reacting to the expected value of injection costs. The novelty of our approach lies in combining the AoII metric with Bayesian game-theoretic modeling under incomplete information to derive optimal defense strategies against FDI attacks. More in general, we provide insights into strategic countermeasures to mitigate the impact of malicious interventions and enhancing the overall resilience of CPSs.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"405-416"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11535016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148236134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-Learning Digital Twin for Offshore Floating Platform Dynamics and Productivity 海上浮动平台动态和生产力的自学习数字孪生

IF 7.4

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-06-15 DOI: 10.1109/TICPS.2026.3703363

Xiaoling Liang;Yueyi Chen;Bernard Voon Ee How;Shuzhi Sam Ge

{"title":"Self-Learning Digital Twin for Offshore Floating Platform Dynamics and Productivity","authors":"Xiaoling Liang;Yueyi Chen;Bernard Voon Ee How;Shuzhi Sam Ge","doi":"10.1109/TICPS.2026.3703363","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3703363","url":null,"abstract":"As offshore energy transitions to greener operations, turret-moored floating platforms increasingly function as advanced cyber-physical systems (CPSs) exposed to harsh seas and cyber-physical risks. This paper targets productivity and safety for turret-moored platforms with thruster-assisted heading control under time-varying environmental loads and potential cyber–physical anomalies. We develop an operational and control oriented self-learning digital twin that fuses physics based hydrodynamic modeling with online neural approximation to capture modeling errors and slow drifts during platform operation. Prediction residuals from the twin are used for lightweight anomaly monitoring, which provides early warning of abnormal sensor or actuator behavior and supports supervisory mitigation. Building on these predictions, an autonomous decision-support module optimizes the platform heading via a multi-factor performance index while adaptive controller maintains robust heading stabilization under bounded prediction residuals and advisory mismatch. Comprehensive simulations across three extreme multi-directional sea states and scaled basin experiments demonstrate substantial reductions in roll motion and improved heading regulation; the monitoring layer further provides actionable early warning for abnormal operation. The results show a practical pathway to monitoring, decision-making, and control for maritime energy CPSs.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"540-549"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148479768","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

Anomaly Detection for Stealthy FDIAs in Distributed Cyber-Physical Electric Vehicle Scheduling Systems 分布式网络物理电动车调度系统中隐身fdia的异常检测

IF 7.4

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-06-04 DOI: 10.1109/TICPS.2026.3700581

Saba Marandi;Danial Jafarigiv;Ribal Atallah;Mohsen Ghafouri;Chadi Assi

{"title":"Anomaly Detection for Stealthy FDIAs in Distributed Cyber-Physical Electric Vehicle Scheduling Systems","authors":"Saba Marandi;Danial Jafarigiv;Ribal Atallah;Mohsen Ghafouri;Chadi Assi","doi":"10.1109/TICPS.2026.3700581","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3700581","url":null,"abstract":"This paper presents a cyber-physical anomaly detection framework to safeguard distributed EV scheduling systems against stealthy training-time False Data Injection Attacks (FDIAs). First, a hybrid CNN–LSTM model that captures both spatial and temporal patterns in EV charging behavior is employed to forecast aggregated EV loads accurately. In the subsequent stage, the forecasted values are incorporated into a distributed convex optimization framework. The proposed ADMM-based formulation is designed at the aggregator level and explicitly integrates voltage regulation and power-loss constraints to ensure scalable and feasible scheduling across the grid. Then, systematic training-time FDIA scenarios are generated and injected into the historical data to analyze how corrupted forecasts propagate through the scheduling process and cause voltage deviations and local constraint violations. To mitigate these threats, an image-based anomaly detection model is proposed using a modified Residual Network (ResNet50) architecture tailored to structured EV scheduling data. These design enhancements improve the model's sensitivity to subtle spatio-temporal anomalies that conventional CNN, LSTM, and standard ResNet50 models fail to capture. The framework is validated using real-world EV charging data mapped to IEEE benchmarks, showing that stealthy FDIAs corrupt scheduling and cause voltage deviations, while the proposed detection model effectively identifies these malicious patterns with high accuracy.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"525-539"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148480557","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 Double-Loop Control Strategy by Coordinating EV Aggregators and Generator Sets for Emergency Power Shortage 针对紧急电力短缺的电动汽车聚合器与发电机组协调双环控制策略

IF 7.4

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-07-17 DOI: 10.1109/TICPS.2026.3714778

Kun Yan;Ankang Song;Zhenyong Zhang

{"title":"A Double-Loop Control Strategy by Coordinating EV Aggregators and Generator Sets for Emergency Power Shortage","authors":"Kun Yan;Ankang Song;Zhenyong Zhang","doi":"10.1109/TICPS.2026.3714778","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3714778","url":null,"abstract":"Frequency stability is a core guarantee for the safe operation of the grid, but the volatility of renewable energy generation and the continuous growth of load demand significantly increase the difficulty of grid frequency regulation. Sudden large-scale power shortages will trigger an emergency power shortage, and traditional identification methods based on rate-of-change-of-frequency (ROCOF) thresholds are prone to assessment errors. Furthermore, the frequency regulation response of generator sets lags, and the parallel frequency regulation mode of EV aggregators and generator sets fails to meet the stringent real-time requirements. Therefore, this paper first characterizes the frequency dynamics of emergency power shortages through mathematical derivations and constructs a multidimensional assessment criterion to identify them. Then, we design a double-loop control strategy to account for differences in frequency-response speed between the generator sets and the EV aggregators. Generator sets act as the outer loop to achieve high-power steady-state frequency regulation, while EV aggregators act as the inner loop to quickly compensate for remaining frequency deviations. The bounded stability of the system under bounded disturbances is analyzed using Lyapunov theory. The results of simulation experiments show that the proposed strategy offers significant advantages in both accuracy and response speed, and demonstrates good robustness.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"708-718"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148746918","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

Targeted Algorithmic Purpose-Driven Cyber Attacks in Distributed Multi-Agent Optimization 分布式多智能体优化中的目标算法驱动网络攻击

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-03-09 DOI: 10.1109/TICPS.2026.3672066

Mahan Fakouri Fard;Mingxi Liu

引用次数: 0

A Model-Based Decision Support for Field-to-Cloud Communication of Cyber-Physical Production Systems 基于模型的信息物理生产系统场到云通信决策支持

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-03-16 DOI: 10.1109/TICPS.2026.3674578

Dominik Hujo-Lauer;Birgit Vogel-Heuser;Bernhard Rupprecht;Marius Krüger

{"title":"A Model-Based Decision Support for Field-to-Cloud Communication of Cyber-Physical Production Systems","authors":"Dominik Hujo-Lauer;Birgit Vogel-Heuser;Bernhard Rupprecht;Marius Krüger","doi":"10.1109/TICPS.2026.3674578","DOIUrl":"https://doi.org/10.1109/TICPS.2026.3674578","url":null,"abstract":"Novel approaches for processing data in Cyber-Physical Production Systems (CPPS) usually require high computing capacities accessible through powerful cloud platforms like AWS or Azure. Two of the most relevant requirements to enable the use of cloud platforms in industrial automation are real-time capability and security. Addressing these requirements necessitates extensive knowledge of field-, edge-, and cloud-level technology, which is rarely available. A generalized architecture design could overcome the skill shortage in companies but conflicts with an optimized system design, which can only be attained through application- and order-specific designs. A model-based decision support is presented, enabling the definition of relevant requirements for deploying field-to-cloud communication solutions. The presented decision support combines a quality function based on system requirements from industrial automation and a domain-specific language extension, allowing automation engineers to handle the requirements necessary for the system’s design. Two representative use cases are implemented to evaluate the approach and to demonstrate its benefits.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"4 ","pages":"201-212"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11435471","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

XGBoost-Based Real-Time Intrusion Detection With Blockchain Logging for Secure EV Charging 基于xgboost的实时入侵检测与区块链日志安全充电

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-04-10 DOI: 10.1109/TICPS.2026.3682237

Gaurav Kumar;Suresh Mikkili

引用次数: 0

A Novel Distributed Cooperative Dynamic Feedback Control of Low-Inertia Cyber-Physical Microgrids 一种新型低惯量网络物理微电网分布式协同动态反馈控制

IF 7.4

IEEE Transactions on Industrial Cyber-Physical Systems Pub Date : 2026-01-01 Epub Date: 2026-09-07 DOI: 10.1109/TICPS.2026.3731127

Jiannan Dai;Jingang Lai

引用次数: 0